I'm writing a toy Lisp and use an SSA representation. The translation into (T)SSA and CSSA was straight forward, since I found a lot of online course material describing the process, but I have problem with implementing a non-naive translation out of SSA.
I have found two articles describing the process which are often referenced to: Translating Out of Static Single Assignment Form and Revisiting Out-of-SSA. I decided to go with Out-of-SSA method and there was no problem implementing the algorithms for interference checking since pseudo code is provided.
But in section IV:C Virtualization of the φ-nodes the process of φ-elimination is only described at a high level and I can't figure out how to do the implementation.
Can anyone point me to some material describing this process in more depth, preferably with examples and/or pseudo code?
If not, is there a simpler algorithm that provides reasonable results? Perhaps method I/II of Translating Out of SSA and then the described CSSA-based coalescing?

MS-ISAC CYBERSECURITY ADVISORY
MS-ISAC ADVISORY NUMBER: 2024-042
DATE(S) ISSUED: 04/17/2024
SUBJECT: Oracle Quarterly Critical Patches Issued April 16, 2024
OVERVIEW: Multiple vulnerabilities have been discovered in Oracle products, the most severe of which could allow for remote code execution.
SYSTEMS AFFECTED:

• Autonomous Health Framework, versions prior to 23.11.1, prior to 24.2
• Management Cloud Engine, version 24.1.0.0.0
• MySQL Cluster, versions 7.5.33 and prior, 7.6.29 and prior, 8.0.36 and prior, 8.2.0 and prior, 8.3.0 and prior
• MySQL Connectors, versions 8.3.0 and prior
• MySQL Enterprise Backup, versions 8.0.36 and prior, 8.3.0 and prior
• MySQL Enterprise Monitor, versions 8.0.37 and prior
• MySQL Server, versions 8.0.36 and prior, 8.2.0 and prior, 8.3.0 and prior
• OPatch, versions prior to 12.2.0.1.42
• OPatchAuto, versions prior to 12.2.0.1.42
• Oracle Access Manager, version 12.2.1.4.0
• Oracle Agile PLM, version 9.3.6
• Oracle Agile Product Lifecycle Management for Process, version 6.2.4.2
• Oracle Application Testing Suite, version 13.3.0.1
• Oracle Banking APIs, versions 19.1.0.0.0, 19.2.0.0.0, 21.1.0.0.0, 22.1.0.0.0, 22.2.0.0.0
• Oracle Banking Branch, versions 14.5.0.0.0, 14.6.0.0.0, 14.7.0.0.0
• Oracle Banking Cash Management, versions 14.5.0.0.0, 14.6.0.0.0, 14.7.0.0.0
• Oracle Banking Deposits and Lines of Credit Servicing, version 2.12.0.0.0
• Oracle Banking Digital Experience, versions 19.1.0.0.0, 19.2.0.0.0, 21.1.0.0.0, 22.1.0.0.0, 22.2.0.0.0
• Oracle Banking Enterprise Default Management, versions 2.7.0.0.0, 2.12.0.0.0
• Oracle Banking Liquidity Management, versions 14.5.0.0.0, 14.6.0.0.0, 14.7.0.0.0, 14.7.0.3.0
• Oracle Banking Loans Servicing, version 2.12.0.0.0
• Oracle Banking Origination, versions 14.5.0.0.0, 14.6.0.0.0, 14.7.0.0.0
• Oracle Banking Party Management, version 2.7.0.0.0
• Oracle Banking Platform, versions 2.7.0.0.0, 2.12.0.0.0
• Oracle Banking Virtual Account Management, versions 14.5.0.0.0, 14.6.0.0.0, 14.7.0.0.0
• Oracle BI Publisher, versions 7.0.0.0.0, 12.2.1.4.0
• Oracle Big Data Spatial and Graph, version 3.0.5
• Oracle Business Intelligence Enterprise Edition, versions 7.0.0.0.0, 12.2.1.4.0
• Oracle Coherence, versions 12.2.1.4.0, 14.1.1.0.0
• Oracle Commerce Guided Search, version 11.3.2
• Oracle Commerce Platform, versions 11.3.0, 11.3.1, 11.3.2
• Oracle Communications Billing and Revenue Management, versions 12.0.0.4-12.0.0.8, 15.0.0.0
• Oracle Communications BRM - Elastic Charging Engine, versions 12.0.0.4-12.0.0.8, 15.0.0.0
• Oracle Communications Cloud Native Core Binding Support Function, versions 23.4.0-23.4.2
• Oracle Communications Cloud Native Core Console, version 23.4.0
• Oracle Communications Cloud Native Core Network Data Analytics Function, version 24.1.0
• Oracle Communications Cloud Native Core Network Exposure Function, version 23.4.1
• Oracle Communications Cloud Native Core Network Function Cloud Native Environment, versions 23.2.0, 23.3.1, 23.4.0
• Oracle Communications Cloud Native Core Network Repository Function, version 23.4.1
• Oracle Communications Cloud Native Core Network Slice Selection Function, versions 23.2.0, 23.3.0
• Oracle Communications Cloud Native Core Policy, versions 23.4.0-23.4.2
• Oracle Communications Cloud Native Core Security Edge Protection Proxy, versions 23.3.0, 23.4.0
• Oracle Communications Cloud Native Core Service Communication Proxy, versions 23.1.0, 23.2.2, 23.3.0, 23.4.0
• Oracle Communications Cloud Native Core Unified Data Repository, versions 22.4.0, 23.1.0, 23.2.0, 23.3.2
• Oracle Communications Diameter Signaling Router, version 9.0.0.0
• Oracle Communications Element Manager, versions 9.0.0-9.0.2
• Oracle Communications Fraud Monitor, versions 5.0, 5.1, 5.2
• Oracle Communications Network Integrity, version 7.3.6.4
• Oracle Communications Offline Mediation Controller, versions 12.0.0.1-12.0.0.8
• Oracle Communications Operations Monitor, versions 5.0, 5.1, 5.2
• Oracle Communications Service Catalog and Design, version 8.0.0.1.0
• Oracle Communications Session Report Manager, versions 9.0.0-9.0.2
• Oracle Communications Unified Inventory Management, versions 7.4.0-7.4.2, 7.5.0, 7.5.1
• Oracle Communications User Data Repository, version 14.0.0.0.0
• Oracle Communications WebRTC Session Controller, versions 7.2.0.0.0-7.2.1.0.0
• Oracle Data Integrator, version 12.2.1.4.0
• Oracle Database Server, versions 19.3-19.22, 21.3-21.13
• Oracle Documaker, versions 12.6, 12.7
• Oracle E-Business Suite, versions 12.2.3-12.2.13
• Oracle Enterprise Data Quality, version 12.2.1.4.0
• Oracle Enterprise Manager Base Platform, version 13.5.0.0
• Oracle Enterprise Manager for Fusion Middleware, version 13.5.0.0
• Oracle Essbase, version 21.5.4.0.0
• Oracle Financial Services Revenue Management and Billing, versions 2.8.0.0.0, 2.9.0.0.0, 2.9.0.1.0, 3.0.0.0.0, 3.1.0.0.0, 3.2.0.0.0, 4.0.0.0, 5.0.0.0
• Oracle FLEXCUBE Private Banking, version 12.1.0.0.0
• Oracle Fusion Middleware MapViewer, version 12.2.1.4.0
• Oracle Global Lifecycle Management NextGen OUI Framework, version 12.2.1.4.0
• Oracle GoldenGate, versions 19.1.0.0.0-19.22.0.0.240124, 21.3-21.13
• Oracle GoldenGate Stream Analytics, versions 19.1.0.0.0-19.1.0.0.8
• Oracle GoldenGate Studio, version 12.2.0.4.0
• Oracle GoldenGate Veridata, versions 12.2.1.4.0-12.2.1.4.230922
• Oracle GraalVM Enterprise Edition, versions 20.3.13, 21.3.9
• Oracle GraalVM for JDK, versions 17.0.10, 21.0.2, 22
• Oracle Healthcare Data Repository, versions 8.1.0.0, 8.1.1.0, 8.1.2.0, 8.1.3.0, 8.1.3.2, 8.1.3.4
• Oracle Hospitality Cruise Shipboard Property Management System, versions 20.3.3, 20.3.4, 23.1.0, 23.1.1
• Oracle Hospitality Simphony, versions 19.1.0-19.5.4
• Oracle HTTP Server, versions 12.2.1.4.0, 14.1.1.0.0
• Oracle Hyperion Infrastructure Technology, version 11.2.16.0.0
• Oracle Identity Manager, version 12.2.1.4.0
• Oracle Identity Manager Connector, version 12.2.1.3.0
• Oracle Internet Directory, version 12.2.1.4.0
• Oracle Java SE, versions 8u401, 8u401-perf, 11.0.22, 17.0.10, 21.0.2, 22
• Oracle Life Sciences Empirica Signal, versions 9.1.0.53, 9.2.0.53
• Oracle Managed File Transfer, version 12.2.1.4.0
• Oracle Middleware Common Libraries and Tools, versions 12.2.1.4.0, 14.1.1.0.0
• Oracle Outside In Technology, versions 8.5.6, 8.5.7
• Oracle Retail Assortment Planning, versions 15.0.3, 16.0.3
• Oracle Retail Customer Management and Segmentation Foundation, version 19.0.0.9
• Oracle Retail Integration Bus, versions 14.1.3.2, 15.0.3.1, 16.0.3, 19.0.1
• Oracle Retail Merchandising System, versions 14.1.3, 15.0.3, 16.0.3, 19.0.1
• Oracle Retail Sales Audit, versions 14.1.3.1, 15.0.3.1, 16.0.3, 19.0.1
• Oracle Retail Service Backbone, versions 14.1.3.2, 15.0.3.1, 16.0.3, 19.0.1
• Oracle Retail Xstore Point of Service, versions 19.0.5, 20.0.4, 21.0.3, 22.0.1, 23.0.1
• Oracle SD-WAN Edge, version 9.1.1.7.0
• Oracle Smart View for Office, version 11.2.16.0.0
• Oracle SOA Suite, version 12.2.1.4.0
• Oracle Solaris, version 11
• Oracle Solaris Cluster, version 4
• Oracle StorageTek Tape Analytics (STA), version 2.5
• Oracle TimesTen In-Memory Database, versions prior to 22.1, prior to 22.1.1.19.0, prior to 22.1.1.23.0
• Oracle Transportation Management, versions 6.5.2, 6.5.3
• Oracle Utilities Application Framework, versions 4.3.0.3.0-4.3.0.6.0, 4.4.0.0.0, 4.4.0.2.0, 4.4.0.3.0, 4.5.0.0.0, 4.5.0.1.1, 4.5.0.1.2
• Oracle Utilities Network Management System, versions 2.3.0.2, 2.4.0.1, 2.5.0.1, 2.5.0.2, 2.6.0.0, 2.6.0.0.4, 2.6.0.1
• Oracle VM VirtualBox, versions prior to 7.0.16
• Oracle Web Services Manager, version 12.2.1.4.0
• Oracle WebCenter Content, version 12.2.1.4.0
• Oracle WebCenter Enterprise Capture, version 12.2.1.4.0
• Oracle WebCenter Portal, version 12.2.1.4.0
• Oracle WebLogic Server, versions 12.2.1.4.0, 14.1.1.0.0
• Oracle ZFS Storage Appliance Kit, version 8.8
• OSS Support Tools, versions 2.12.44, 2.12.45, 23.1.23.1.17, 24.1.24.1.16
• PeopleSoft Enterprise CRM Client Management, version 9.2
• PeopleSoft Enterprise HCM Benefits Administration, version 9.2
• PeopleSoft Enterprise PeopleTools, versions 8.59, 8.60, 8.61
• Primavera Gateway, versions 19.12.0-19.12.18, 20.12.0-20.12.13, 21.12.0-21.12.11
• Primavera P6 Enterprise Project Portfolio Management, versions 19.12.0-19.12.22, 20.12.0-20.12.21, 21.12.0-21.12.18, 22.12.0-22.12.12, 23.12.0-23.12.2
• Primavera Unifier, versions 19.12.0-19.12.16, 20.12.0-20.12.16, 21.12.0-21.12.17, 22.12.0-22.12.12, 23.12.0-23.12.3
• Siebel Applications, versions 24.2 and prior

RISK: Government:

• Large and medium government entities: High
• Small government entities: High

Businesses:

• Large and medium business entities: High
• Small business entities: High

Home users: Low
RECOMMENDATIONS: We recommend the following actions be taken:

• Apply appropriate patches or appropriate mitigations provided by Oracle to vulnerable systems immediately after appropriate testing. (M1051: Update Software)
  
  • Safeguard 7.1: Establish and Maintain a Vulnerability Management Process: Establish and maintain a documented vulnerability management process for enterprise assets. Review and update documentation annually, or when significant enterprise changes occur that could impact this Safeguard.
  • Safeguard 7.2: Establish and Maintain a Remediation Process: Establish and maintain a risk-based remediation strategy documented in a remediation process, with monthly, or more frequent, reviews.
  • Safeguard 7.4: Perform Automated Application Patch Management: Perform application updates on enterprise assets through automated patch management on a monthly, or more frequent, basis.
  • Safeguard 7.5 : Perform Automated Vulnerability Scans of Internal Enterprise Assets: Perform automated vulnerability scans of internal enterprise assets on a quarterly, or more frequent, basis. Conduct both authenticated and unauthenticated scans, using a SCAP-compliant vulnerability scanning tool.
  • Safeguard 7.7: Remediate Detected Vulnerabilities: Remediate detected vulnerabilities in software through processes and tooling on a monthly, or more frequent, basis, based on the remediation process.
  • Safeguard 12.1: Ensure Network Infrastructure is Up-to-Date: Ensure network infrastructure is kept up-to-date. Example implementations include running the latest stable release of software and/or using currently supported network-as-a-service (NaaS) offerings. Review software versions monthly, or more frequently, to verify software support.
  • Safeguard 18.1: Establish and Maintain a Penetration Testing Program: Establish and maintain a penetration testing program appropriate to the size, complexity, and maturity of the enterprise. Penetration testing program characteristics include scope, such as network, web application, Application Programming Interface (API), hosted services, and physical premise controls; frequency; limitations, such as acceptable hours, and excluded attack types; point of contact information; remediation, such as how findings will be routed internally; and retrospective requirements.
  • Safeguard 18.2: Perform Periodic External Penetration Tests: Perform periodic external penetration tests based on program requirements, no less than annually. External penetration testing must include enterprise and environmental reconnaissance to detect exploitable information. Penetration testing requires specialized skills and experience and must be conducted through a qualified party. The testing may be clear box or opaque box.
  • Safeguard 18.3: Remediate Penetration Test Findings: Remediate penetration test findings based on the enterprise’s policy for remediation scope and prioritization.
• Vulnerability scanning is used to find potentially exploitable software vulnerabilities to remediate them. (M1016: Vulnerability Scanning)
  
  • Safeguard 16.13: Conduct Application Penetration Testing: Conduct application penetration testing. For critical applications, authenticated penetration testing is better suited to finding business logic vulnerabilities than code scanning and automated security testing. Penetration testing relies on the skill of the tester to manually manipulate an application as an authenticated and unauthenticated user.
• Apply the Principle of Least Privilege to all systems and services, and run all software as a non-privileged user (one without administrative rights) to diminish the effects of a successful attack. (M1026: Privileged Account Management)
  
  • Safeguard 4.7: Manage Default Accounts on Enterprise Assets and Software: Manage default accounts on enterprise assets and software, such as root, administrator, and other pre-configured vendor accounts. Example implementations can include: disabling default accounts or making them unusable.
  • Safeguard 5.4: Restrict Administrator Privileges to Dedicated Administrator Accounts: Restrict administrator privileges to dedicated administrator accounts on enterprise assets. Conduct general computing activities, such as internet browsing, email, and productivity suite use, from the user’s primary, non-privileged account.
  • Safeguard 5.5: Establish and Maintain an Inventory of Service Accounts: Establish and maintain an inventory of service accounts. The inventory, at a minimum, must contain department owner, review date, and purpose. Perform service account reviews to validate that all active accounts are authorized, on a recurring schedule at a minimum quarterly, or more frequently
• Remind all users not to visit untrusted websites or follow links/open files provided by unknown or untrusted sources. (M1017: User Training)
  
  • Safeguard 14.1: Establish and Maintain a Security Awareness Program: Establish and maintain a security awareness program. The purpose of a security awareness program is to educate the enterprise’s workforce on how to interact with enterprise assets and data in a secure manner. Conduct training at hire and, at a minimum, annually. Review and update content annually, or when significant enterprise changes occur that could impact this Safeguard.
  • Safeguard 14.2: Train Workforce Members to Recognize Social Engineering Attacks: Train workforce members to recognize social engineering attacks, such as phishing, pre-texting, and tailgating.
• Use capabilities to prevent suspicious behavior patterns from occurring on endpoint systems. This could include suspicious process, file, API call, etc. behavior. (M1040 : Behavior Prevention on Endpoint)
  
  • Safeguard 13.2 : Deploy a Host-Based Intrusion Detection Solution: Deploy a host-based intrusion detection solution on enterprise assets, where appropriate and/or supported.
  • Safeguard 13.7 : Deploy a Host-Based Intrusion Prevention Solution: Deploy a host-based intrusion prevention solution on enterprise assets, where appropriate and/or supported. Example implementations include use of an Endpoint Detection and Response (EDR) client or host-based IPS agent.
• Use capabilities to detect and block conditions that may lead to or be indicative of a software exploit occurring. (M1050: Exploit Protection)
  

Safeguard 10.5: Enable Anti-Exploitation Features: Enable anti-exploitation features on enterprise assets and software, where possible, such as Microsoft® Data Execution Prevention (DEP), Windows® Defender Exploit Guard (WDEG), or Apple® System Integrity Protection (SIP) and Gatekeeper™.
REFERENCES:

Oracle: https://www.oracle.com/security-alerts/cpuapr2024.html

Hello python 👋! Back in January, I've compiled a list of the most watched PyCon talks from 2023. I've received tons of positive feedback via DM, upvotes, and comments, so I decided to put together another compilation.
This time around, I've gathered not only PyCon, but all Python 2023 talks across +100 conferences (here's the list) that include PyCon (all locations), PyData (all locations), EuroPython, Conf42, and many more to give you a complete overview of the landscape. The list is gigantic and includes over 850 talks!
What's more, I've created a Google Sheets version of this post that gives more convenient sorting and filtering options.
If it turns to be useful, don't forget to share the list with friends / colleagues!

1. "Tutorials - Mario Munoz: Web Development With A Python-backed Frontend: Featuring HTMX and Tailwind" ⸱ +12k views ⸱ 02h 26m 00s
2. "Thomas Bierhance: Polars - make the switch to lightning-fast dataframes" ⸱ +11k views ⸱ 00h 29m 49s
3. "Mariatta Wijaya: Welcome to PyCon US 2023" ⸱ +11k views ⸱ 00h 29m 29s
4. "Scaling Python for Machine Learning: Beyond Data Parallelism • Holden Karau • GOTO 2023" ⸱ +10k views ⸱ 00h 39m 19s
5. "Tutorials - Matt Harrison: Getting Started with Polars" ⸱ +10k views ⸱ 02h 14m 28s
6. "Keynote Speaker - Ned Batchelder" ⸱ +7k views ⸱ 00h 47m 02s
7. "Gábor Szárnyas - DuckDB: The Power of a Data Warehouse in your Python Process" ⸱ +7k views ⸱ 00h 55m 27s
8. "Talks - Samuel Colvin: How Pydantic V2 leverages Rust's Superpowers" ⸱ +6k views ⸱ 00h 45m 55s
9. "Delta-rs, Apache Arrow, Polars, WASM: Is Rust the Future of Analytics?" ⸱ +6k views ⸱ 00h 31m 03s
10. "Tutorials - Simon Willison: Data analysis with SQLite and Python" ⸱ +5k views ⸱ 02h 45m 54s
11. "Talks - Hynek Schlawack: Subclassing, Composition, Python, and You" ⸱ +5k views ⸱ 00h 45m 42s
12. "Writing Python Bindings for C++ Libraries: Easy-to-use Performance - Saksham Sharma - CppCon 2023" ⸱ +5k views ⸱ 01h 01m 30s
13. "Pedro Holanda - DuckDB: Bringing analytical SQL directly to your Python shell" ⸱ +5k views ⸱ 00h 29m 31s
14. "Tutorials - Lisa Carpenter: How to create beautiful interactive GUIs and web apps" ⸱ +5k views ⸱ 01h 58m 05s
15. "Tutorials - Reuven M. Lerner: Comprehending comprehensions" ⸱ +5k views ⸱ 02h 17m 33s
16. "Keynote Speaker - Guido van Rossum" ⸱ +5k views ⸱ 00h 30m 51s
17. "PyData Heidelberg #11 - TimeSeries Forecasting & LLM Langchain" ⸱ +4k views ⸱ 02h 39m 06s
18. "Keynote Speaker - James Powell" ⸱ +4k views ⸱ 00h 25m 43s
19. "Use Spark from anywhere: A Spark client in Python powered by Spark Connect" ⸱ +4k views ⸱ 00h 56m 58s
20. "Cython 3 – Python at the speed of C — Stefan Behnel" ⸱ +4k views ⸱ 00h 31m 15s
21. "Patrick Blöbaum: Performing Root Cause Analysis with DoWhy, a Causal Machine-Learning Library" ⸱ +4k views ⸱ 00h 44m 38s
22. "Max Mergenthaler and Fede Garza - Quantifying Uncertainty in Time Series Forecasting" ⸱ +4k views ⸱ 00h 37m 25s
23. "Talks - Bruce Eckel: Rethinking Objects" ⸱ +4k views ⸱ 00h 32m 06s
24. "Rust for Python data engineers — Karim Jedda" ⸱ +4k views ⸱ 00h 27m 30s
25. "Matt Harrison - An Introduction to Pandas 2, Polars, and DuckDB PyData Global 2023" ⸱ +4k views ⸱ 01h 22m 15s
26. "Tutorials - Ted Patrick: Writing Serverless Python Web Apps with PyScript" ⸱ +3k views ⸱ 02h 55m 29s
27. "Tutorials - Trey Hunner: Intro to Python for Brand New Programmers" ⸱ +3k views ⸱ 02h 16m 41s
28. "Dr. Thomas Wiecki: Bayesian Marketing Science - Solving Marketing's 3 Biggest Problems" ⸱ +3k views ⸱ 00h 30m 35s
29. [**"Gaël Varoquaux: Prepping Tables for Machine Learning Gets Easier PyData Südwest]"** ⸱ +3k views ⸱ 00h 57m 54s
30. "Talks - Reuven M. Lerner: Generators, coroutines and nanoservices" ⸱ +3k views ⸱ 00h 26m 28s
31. "Talks - Brett Cannon: Python's syntactic sugar" ⸱ +3k views ⸱ 00h 31m 11s
32. "Bruno Vollmer: BLE and Python - How to build a simple BLE project on Linux with Python" ⸱ +3k views ⸱ 00h 29m 40s
33. "Vasileios Mourtakos - A data engineering framework in Python" ⸱ +3k views ⸱ 00h 35m 55s
34. "Talks - Eric Snow: A Per-Interpreter GIL: Concurrency and Parallelism with Subinterpreters" ⸱ +3k views ⸱ 00h 30m 29s
35. "Talks - Łukasz Langa: Working Around the GIL with asyncio" ⸱ +2k views ⸱ 00h 44m 26s
36. "Hajime Takeda - Media Mix Modeling:How to Measure the Effectiveness of Advertising" ⸱ +2k views ⸱ 00h 30m 37s
37. "Tutorials - Mike Müller: The How and Why of Object-oriented Programming in Python" ⸱ +2k views ⸱ 02h 45m 34s
38. "Shahriyar Rzayev: Building Hexagonal Python Services" ⸱ +2k views ⸱ 01h 29m 50s
39. "Performance tips by the FastAPI Expert — Marcelo Trylesinski" ⸱ +2k views ⸱ 00h 24m 59s
40. "Solving Multi-Objective Constrained Optimisation Problems using Pymoo — Pranjal Biyani" ⸱ +2k views ⸱ 00h 44m 23s
41. "Carsten Binnig: Towards Learned Database Systems" ⸱ +2k views ⸱ 00h 43m 34s
42. "Talks - Brandt Bucher: Inside CPython 3.11's new specializing, adaptive interpreter" ⸱ +2k views ⸱ 00h 23m 01s
43. "Carl Kadie - A Perfect, Infinite-Precision, Game Physics in Python PyData Seattle 2023" ⸱ +2k views ⸱ 00h 36m 26s
44. "From crontab to celery with no regrets by Marco Pavanelli" ⸱ +2k views ⸱ 00h 32m 03s
45. "Talks - Al Sweigart: An Overview of the Python Code Tool Landscape 2023" ⸱ +2k views ⸱ 00h 26m 58s
46. "Reinventing Machine Learning with Transformers and Hugging Face by Keynote speaker Julien Simon" ⸱ +2k views ⸱ 01h 08m 52s
47. "Empower your Spring Applications with Python Features on GraalVM by Johannes Link @ Spring I/O 2023" ⸱ +2k views ⸱ 00h 53m 00s
48. "Marysia Winkels - Data Storytelling through Visualization" ⸱ +2k views ⸱ 00h 30m 57s
49. "What polars does for you — Ritchie Vink" ⸱ +2k views ⸱ 00h 27m 45s
50. "Beyond Toy Datasets: Timeseries Forecasting for Real Business Problems - Robert Haase" ⸱ +2k views ⸱ 00h 33m 55s
51. "PyData Online - An AI assistant for football analytics - Petar Veličković (Google DeepMind)" ⸱ +2k views ⸱ 01h 02m 40s
52. "Talks - Mark Shannon: How we are making CPython faster. Past, present and future." ⸱ +2k views ⸱ 00h 29m 11s
53. "JIm Dowling - Build a production ML system with only Python on free serverless services" ⸱ +2k views ⸱ 01h 22m 35s
54. "Writing a Python interpreter from scratch, in half an hour — Tushar Sadhwani" ⸱ +2k views ⸱ 00h 43m 38s
55. "Dominika Basaj & Barbara Rychalska - Creating behavioral profiles of your customer" ⸱ +2k views ⸱ 00h 26m 55s
56. "Stephan Sahm: Accelerate Python with Julia" ⸱ +2k views ⸱ 01h 27m 14s
57. "Why Delta Lake is the Best Storage Format for Pandas Analyses" ⸱ +2k views ⸱ 00h 28m 25s
58. "Tutorials - Geir Arne Hjelle: Introduction to Decorators: Power Up Your Python Code" ⸱ +2k views ⸱ 02h 21m 20s
59. "Jeroen Overschie - How to create a Devcontainer for your Python project 🐳" ⸱ +2k views ⸱ 00h 36m 01s
60. "Wesley Boelrijk - Lowering the barrier for ML monitoring" ⸱ +2k views ⸱ 00h 36m 53s
61. "Talks - Dan Craig: Testing Spacecraft with Pytest" ⸱ +2k views ⸱ 00h 30m 12s
62. "Keynote Speaker - Margaret Mitchell" ⸱ +2k views ⸱ 00h 42m 29s
63. "Talks - Moshe Zadka: pyproject.toml, packaging, and you" ⸱ +2k views ⸱ 00h 30m 06s
64. "Tutorials - Juhi, Dana: Intro to Hugging Face: Fine-tuning BERT for NLP tasks" ⸱ +2k views ⸱ 02h 09m 52s
65. "Tutorials - Patrick Arminio: Build a production ready GraphQL API using Python" ⸱ +2k views ⸱ 02h 23m 14s
66. "Ryan Curtin - Lightweight, low-overhead, high-performance: machine learning directly in C++" ⸱ +2k views ⸱ 00h 43m 10s
67. "Python with Spark Connect" ⸱ +2k views ⸱ 00h 33m 27s
68. "David Qiu - Jupyter AI — Bringing Generative AI to Jupyter PyData Seattle 2023" ⸱ +1k views ⸱ 00h 39m 29s
69. "Polars: A highly optimized dataframe library Matt Harrison Conf42 Machine Learning 2023" ⸱ +1k views ⸱ 00h 20m 31s
70. "Nico Kreiling: Raised by Pandas, striving for more: An opinionated introduction to Polars" ⸱ +1k views ⸱ 00h 29m 47s
71. "Jiang et al. - Automated Machine Learning & Tuning with FLAML PyData Seattle 2023" ⸱ +1k views ⸱ 01h 21m 54s
72. "Alexander CS Hendorf: 5 Things about fastAPI I wish we had known beforehand" ⸱ +1k views ⸱ 00h 32m 31s
73. "Duarte Carmo - MLOps for the rest of us- A poor man's guide to putting models in production" ⸱ +1k views ⸱ 00h 26m 04s
74. [**"Ines Montani (spaCy) - Large Language Models from Prototype to Production PyData Südwest]"** ⸱ +1k views ⸱ 00h 39m 55s
75. "Robin Raymond: Rusty Python - A Case Study" ⸱ +1k views ⸱ 00h 28m 47s
76. "Tutorials - Leah Berg, Ray: Feature Engineering is for Everyone!" ⸱ +1k views ⸱ 02h 16m 35s
77. "Giles Weaver & Ian Ozsvald - Pandas 2, Dask or Polars? Tackling larger data on a single machine" ⸱ +1k views ⸱ 00h 16m 22s
78. "Talks - Glyph: How To Keep A Secret" ⸱ +1k views ⸱ 00h 26m 19s
79. "Maximilian M. - SHAPtivating Insights: unravelling blackbox AI models" ⸱ +1k views ⸱ 00h 35m 02s
80. "Vahan Huroyan - Recent Developments in Self-Supervised Learning for Computer Vision" ⸱ +1k views ⸱ 00h 36m 25s
81. "Lucas Durand - Building an Interactive Network Graph to Understand Communities PyData Seattle 2023" ⸱ +1k views ⸱ 01h 26m 14s
82. "Big PyData BBQ #5: LLMs feat. Ines Montani (spaCy) & Alejandro Saucedo (Zalando)" ⸱ +1k views ⸱ 03h 48m 21s
83. "Stop using print! Understanding and using the "logging" module — Reuven M. Lerner" ⸱ +1k views ⸱ 00h 29m 32s
84. "Joris Van den Bossche & Patrick Hoefler: Pandas 2.0 and beyond" ⸱ +1k views ⸱ 00h 37m 07s
85. "Structured output with large language models / Uri Goren (Argmax)" ⸱ +1k views ⸱ 00h 25m 09s
86. "PyData Chicago April 2023 Meetup Design and Analysis of (Backtest) Experiments with R and Python" ⸱ +1k views ⸱ 00h 50m 19s
87. "Sponsor Presentation - Python & Bloomberg: An Open Source Duo" ⸱ +1k views ⸱ 00h 57m 08s
88. "Soumith Chintala - Keynote: AI & the stuff built for AI - are they actually useful for data science?" ⸱ +1k views ⸱ 00h 31m 54s
89. "The Future of Microprocessors — Sophie Wilson" ⸱ +1k views ⸱ 00h 56m 45s
90. "Jia Yu - How Apache Sedona is Revolutionizing Geospatial Data Analysis PyData Seattle 2023" ⸱ +1k views ⸱ 00h 46m 12s
91. "Lightning Talks - April 21, 5pm" ⸱ +1k views ⸱ 01h 04m 16s
92. "How to Leverage the Full Potential of LLMs for Your Business with Langchain - Leon Ruddat" ⸱ +1k views ⸱ 00h 34m 40s
93. "Jay Chia & Sammy Sidhu: Daft - The Distributed Python Dataframe for Complex Data" ⸱ +1k views ⸱ 00h 23m 01s
94. "Talks - A. Jesse Jiryu Davis: Consistency and isolation for Python programmers" ⸱ +1k views ⸱ 00h 24m 23s
95. ""Python deployment with Docker and Poetry" - Cristian Heredia (PyBay 2023)" ⸱ +1k views ⸱ 00h 12m 24s
96. "Peterson & Qin - Contextual Multi-Arm Bandit and its applications to digital experiments PyData" ⸱ +1k views ⸱ 00h 44m 54s
97. "Tutorials - Ron Nathaniel: How To Troubleshoot and Monitor Applications using OpenTelemetry" ⸱ +1k views ⸱ 02h 01m 57s
98. "Keynote Speaker - Python Steering Council" ⸱ +1k views ⸱ 00h 20m 42s
99. "An unbiased evaluation of environment management and packaging tools — Anna-Lena Popkes" ⸱ +1k views ⸱ 00h 43m 14s
100. "Vincent Gosselin - Turning your Data/AI algorithms into full web apps in no time with Taipy" ⸱ +1k views ⸱ 00h 38m 18s
101. "Malte Tichy - Knowing what you don’t know matters- Uncertainty-aware model rating" ⸱ +1k views ⸱ 00h 30m 05s
102. "Talks - Andrew Godwin: Reconciling Everything" ⸱ +1k views ⸱ 00h 30m 16s
103. "Vincent Warmerdam - Bulk Labelling Techniques" ⸱ +1k views ⸱ 00h 32m 55s
104. "Hugo Bowne-Anderson - Full-stack Machine Learning and Generative AI for Data Scientists" ⸱ +1k views ⸱ 01h 28m 30s
105. "J.J. Allaire - Keynote: Dashboards with Jupyter and Quarto PyData NYC 2023" ⸱ +1k views ⸱ 00h 40m 15s
106. "Alejandro Saucedo - Industrial Strength DALLE-E:Scaling Complex Large Text & Image Models" ⸱ +1k views ⸱ 00h 28m 07s
107. "Subclassing, Composition, Python, and You — Hynek Schlawack" ⸱ +1k views ⸱ 00h 44m 59s
108. "Tutorials -Zac Hatfield-Dodds, Ryan Soklaski: Introduction to Property-Based Testing" ⸱ +1k views ⸱ 01h 31m 20s
109. [**"Furkan M. Torun - Become a Data Storyteller with Streamlit! PyData Prague 2023-11-20]"** ⸱ +1k views ⸱ 00h 23m 26s
110. "Anna-Lena Popkes: An unbiased evaluation of environment management and packaging tools" ⸱ +1k views ⸱ 00h 43m 53s
111. "PyData Chicago March 2023 Meetup Monte Carlo with QMCPy for Vector Functions of Integrals" ⸱ +1k views ⸱ 00h 46m 35s
112. "James Powell - Simple Simulators with pandas and Generator Coroutines PyData NYC 2023" ⸱ +1k views ⸱ 01h 21m 43s
113. "Polars is the Pandas killer / Igor Mintz (Viz.ai)" ⸱ +1k views ⸱ 00h 21m 46s
114. "Diving into Event-Driven Architectures with Python — Marc-André Lemburg" ⸱ +1k views ⸱ 00h 30m 59s
115. "Using Embeddings and Deep Neural Networks as a technique for AutoML Demand Forecasting PyData SW" ⸱ +1k views ⸱ 00h 36m 06s
116. "Leland McInnes - Data Mapping for Data Exploration PyData Seattle 2023" ⸱ +1k views ⸱ 00h 38m 16s
117. "Eduardo Blancas - Using embedded SQL engines for plotting massive datasets on a laptop" ⸱ +1k views ⸱ 00h 27m 00s
118. "Large Language Models: From Prototype to Production — Ines Montani" ⸱ +1k views ⸱ 00h 40m 20s
119. "Tutorials - Pavithra Eswaramoorthy, Dharhas Pothina: Data of Unusual Size: Interactive Visualization" ⸱ +1k views ⸱ 03h 06m 45s
120. "Moritz Meister - Data Validation for Feature pipelines: Using Great Expectations and Hopsworks" ⸱ +1k views ⸱ 00h 27m 40s
121. "Inge van den Ende-Leveraging conformal prediction for calibrated probabilistic time series forecasts" ⸱ +1k views ⸱ 00h 31m 33s
122. "Nick Sorros - A Tour of Large Language Models" ⸱ +1k views ⸱ 00h 46m 38s
123. "Thomas Frauholz: From notebook to pipeline in no time with LineaPy" ⸱ +1k views ⸱ 00h 43m 17s
124. "EuroPython 2023 Opening Session" ⸱ +1k views ⸱ 00h 20m 58s
125. "Optimizing Ad Conversions with DS / Yael Kiselman (DigitalTurbine)" ⸱ +1k views ⸱ 00h 51m 44s
126. "Harizo Rajaona - A Tour of the Many DataFrame Frameworks" ⸱ +1k views ⸱ 00h 34m 59s
127. "Andrei Alekseev - Why does everyone need to develop a machine learning package?" ⸱ +1k views ⸱ 00h 28m 07s
128. "Ties de Kok - Going beyond ChatGPT: introduction to prompt engineering & LLMs PyData Seattle 2023" ⸱ +1k views ⸱ 00h 59m 56s
129. "PyData Boston Sept session 1: Mike Woodward - Data sci done wrong: how/why scientists make mistakes." ⸱ +1k views ⸱ 00h 27m 14s
130. "Joe Cheng - Shiny: Data-centric web applications in Python PyData Seattle 2023" ⸱ +1k views ⸱ 00h 43m 56s
131. "Tutorials - Cheuk Ting Ho: Power up your work with compiling and profiling" ⸱ +1k views ⸱ 01h 33m 02s
132. "Talks -Algorithmic ideas, engineering tricks, and trivia behind CPython's new sorting algorithm" ⸱ +1k views ⸱ 00h 29m 39s
133. "Talks - Dawn Wages: Supercharge your Python Development Environment with VS Code + Dev Container" ⸱ +1k views ⸱ 00h 31m 01s
134. "Egor Romanov - Performance of Vector Databases" ⸱ +1k views ⸱ 00h 43m 09s
135. "Alexander CS Hendorf - Ten Years of Community Organizer PyData NYC 2023" ⸱ +1k views ⸱ 00h 42m 41s
136. "Talks - Nicholas H.Tollervey, Paul Everitt: Build Yourself a PyScript" ⸱ +1k views ⸱ 00h 39m 28s
137. "Emil Rijcken - FuzzyTM: a Python package for fuzzy topic models" ⸱ +1k views ⸱ 00h 28m 12s
138. "Nikolas Markou - Artificial Intelligence for Vision: A walkthrough of recent breakthroughs" ⸱ +1k views ⸱ 00h 42m 10s
139. "Would Rust make you a better Pythonista? — Alexys Jacob" ⸱ +1k views ⸱ 00h 47m 23s
140. "Simon Pressler: Getting started with JAX" ⸱ +1k views ⸱ 00h 29m 49s
141. "Sponsor Presentation - How to build stunning Data Science Web applications in Python" ⸱ +1k views ⸱ 00h 54m 10s
142. "Pavel Pleskov - All about ML competitions!" ⸱ +1k views ⸱ 01h 03m 13s
143. "Laszlo Sragner - Code Smells in Data Science: What can we do about them? PyData London 2023" ⸱ +1k views ⸱ 00h 39m 19s
144. "Talks - Jodie Burchell: Vectorize using linear algebra and NumPy to make your Python code fast" ⸱ +1k views ⸱ 00h 28m 32s
145. "Comparing Elixir and Python when working with Simple Neural Networks - A. Neto & L. C. Tavano" ⸱ +1k views ⸱ 00h 38m 11s
146. "Talks - Valerio Maggio: Pythonic functional (iter)tools for your data challenges" ⸱ +1k views ⸱ 00h 32m 38s
147. "Topaz Gilad - Classification Through Regression:Unlock the True Potential of Your Labels" ⸱ +1k views ⸱ 00h 28m 13s
148. "Running Python packages in the browser with Pyodide — Roman Yurchak" ⸱ +1k views ⸱ 00h 27m 49s
149. "J.J. Allaire - Publishing Jupyter Notebooks with Quarto PyData Seattle 2023" ⸱ +1k views ⸱ 00h 40m 47s
150. "ipyvizzu-story- a open-source tool to build create+share animated data stories w/ python in jupyter" ⸱ +1k views ⸱ 01h 25m 54s
151. Due to Reddit post length limit, see the remaining talks in this post or google sheet.

Introduction:
Java, an evergreen cornerstone of software development, has provided power for numerous apps and web projects over its 30-plus-year existence. But with rapid technological innovations transforming its future prospects are increasingly uncertain. Java coaching centre in Chennai, aimed at nurturing the next generation of Java developers, plays a crucial role in ensuring its relevance and adaptation to evolving trends and advancements. Here, we discuss trends and advancements expected to influence it over time.
Trends Driving the Future of Java:

1. Cloud-Native Development:

As cloud computing gains traction, Java developers are becoming drawn to creating applications that run natively in the cloud. To do this, they are increasingly using technologies like Kubernetes and Docker. These tools empower Java apps with scalability, resilience, and flexibility when deployed in cloud environments.

1. Microservices Architecture:

Java is widely used for microservices architecture, where companies prefer systems that are easier to change, grow, and keep up. Java frameworks like Spring Boot and Quarkus make it possible for developers to quickly build apps based on microservices.

1. Machine Learning and AI Integration:

Java is rapidly emerging as a leader in machine learning and artificial intelligence (AI). Tools like Deeplearning4j (a library) and Apache Spark (a framework) allow Java programmers to incorporate AI into their applications for cutting-edge advancements.

1. Native Compilation:

The rise of native compilation technologies such as GraalVM is transforming the world of Java programming. These technologies optimize performance, lower resource usage, and facilitate seamless execution of Java applications in cloud environments by compiling Java code into native machine code.

1. Modularization with Project Jigsaw:

Project Jigsaw, introduced with Java 9, seeks to make the Java platform more adaptable, manageable, and safe by breaking it up into smaller, manageable pieces. As modularization increases within an ecosystem, Java programmers will enjoy better control of their dependencies as well as enhanced data protection measures as they fine tune their code performance for improved efficiency.
Conclusion:
As such, Java's future looks promising and full of promise, driven by technological progress and changing industry needs. With the continuous advancement of Java technology, developers can anticipate improved support for cloud-native development, microservices architecture, machine learning integration and AI integration. Furthermore, with projects such as Project Jigsaw and native compilation adapting to contemporary software development requirements; Java stands as an innovator destined to continue making an impactful statement into its next decade and beyond. As we look towards its long-term significance and flexibility it will continue to shape software development for years and will influence its influence upon software industry development over the time of its evolution.

Motivation

I was writing a Math paper for my mummy's students, and we felt the need to add more questions from previous exam papers that we had created. I had kept them in a directory where the name of each file (a MS Word document) contained the date on which the test was taken. To search for questions belonging to a specific topic, for instance quadratic equations, I had to randomly open any of the files and see it had questions on the topic. If the topics would have separate files or if they were mentioned in the file name, the search would have been a lot easier. I quickly thought of a tool that could solve this problem, and search the contents of the file, and knowing little about Elasticsearch and Apache Lucene, I knew that I needed a full-text-search tool.

Implementation

• An inverted index is a common data-structure used by full-text-search applications, so I decided to build one in Java.
• I used Apache PdfBox and POI libraries that are used to read PDF and Microsoft Office files, followed by text-cleaning and preprocessing. The resulting index could be persisted in the directory by serializing its Java object. The index also contains its own metadata to check for its validity in cases where the contents of the directory were changed after the index was built.
• Wrapped the entire tool in a CLI with picocli, and produced an executable with Launch4j for Windows, which is demonstrated in the image below.

Project: https://github.com/shubham0204/full-text-search
I would like the Reddit community to review the project and provide suggestions on improving the project, code or the tools used. Here are some points on which I worked:

1. Use GraalVM to produce native executables for the fulltextsearch tool
2. Explored RoaringBitmap which is a compressed bitset format used in achieving smaller Set which I've been using to store document indices in the inverted index. I read some threads, but couldn't make out its exact use and superiority to HashSet.
3. How do we achieve more granular search results? Currently, the tool only shows filenames where the tokens in the query were found. How do we pin-point the exact portion of the text where the token is found within the document?
4. Explored the concepts of FatJaUberJar and adjusting heap sizes with JVM options for a less memory-bloated Java application.

Why Java?

I've am an Android developer since 2017 and started with Java + XML, eventually shifting to Kotlin in 2019. I recently discovered apple/pkl which is written mostly in Java, and also realized the scale at which the framework Spring is being used in modern enterprises. These incidents, along with my current internship project, sparked the need to build in Java once again.

I posted here last week to finally introduce Janitorr hitting version 1.0 and received a lot of positive feedback.
At the time, support for Emby had just been added and I had implemented user requests for tag-based media deletion as well as disk space thresholds.
However, the most requested feature that people said would finally turn Janitorr useful to them is having support for viewing stats. So I went to work and implemented optional support for JellyStat.
Now, if JellyStat is enabled, file age gets overwritten with the last active view (via JellyStat API) that was longer than 60 seconds. The idea is to make viewing duration a user chosen option eventually.
Additionally, I moved away from strictly JVM requiring code and implemented a GraalVM native image into the build pipeline. Both images are still made available. At idle, the application now consumes around 50MB of RAM and and less than 1% of CPU resources on an older quad core. This was needed to run it with minimal overheard on seedboxes and other weaker, smaller servers.
Why delete in the first place?
I personally have some servers with smaller storage not in my home. They are limited and won't be upgraded, but my users can still request as much media as they want. Half of it sits around unused and I don't want to manually maintain it for them.
To recap what Janitorr brings to the table:

• Dry-run mode to investigate changes before committing to any deletion
• Remote deletion, disk space aware deletion as well as tag based delete schedules supported
• Exclude items from deletion via tags in SonarRadarr
• Configure expiration times for your media in the *arrs and optionally, if media can be found in JellyStat
• Show a collection, containing rule matched media, on the Jellyfin home screen for a specific duration before deletion. Think: "Leaving soon"
• Unmonitor and delete media from *arr
• Season by season removal for TV shows
• Clear requests from Jellyseerr and clean up leftover metadata in Jellyfin so no orphaned files are left

See the other thread on my X (@tisonkuncz, I don't know, seems attaching the link get moderated) how I get frustrated with GraalVM's Native Image especially when combining it with JNI(rs) and Docker Image. Toolchain sucks. Maybe even a slim JRE made better.
So, why not just rewrite it in Rust and get rid of all these things?
https://github.com/korandoru/hawkeye/discussions/117
Rust's ownership and mutability support helps me a lot to change 3399 LoC Java into 1445 LoC Rust. Also the "ignore" and "git2" crate helps a lot for what I was struggling implement in Java (or try with jni-rs and hit the "Rust toolchain x GraalVM Native Image x Docker Image" hell).
It's notable that I release the Docker image in Alpine. While I first made a ~30MB image with distroless and NativeImage, it grows to about ~50MB finally. I still need alpine because "git config --global --add safe.directory" is yet to workaround (using "ignore" crate instead of "git2" can have some pitfalls).
And it's an interesting journey how you can ship a crate depending on libc to alpine (musl).
I'm somewhat rushing in this rewrite so there is still a lot of rooms to improve the experience, performance, and code style. But I'm confident that the most frequent user journey is held and works well.
Enjoy :D

cargo install hawkeye 

or

- name: Check License Header uses: korandoru/hawkeye@v5 

Hello,
I'm looking for simple logging framework/library to use with GraalVM. Prefering library which i can easily to configure output by using code instead of configuration files. If there are similar library than Go's Zerolog I'm eager to hear about it.
Any suggestions?

Hi /java! I'm building a newsletter called Tech Talks Weekly where once a week I send out all the recently uploaded tech conference talks across engineering conferences (see a recent issue and subscribe if this sounds useful).
As a part of my venture, I've put together a list of all Java talks from 2023 conferences ordered by the number of views for your convenience. The talks are coming from conferences like Devoxx, GOTO, Sprint I/O, WASM I/O, NDC, GeeCON and more.
The list is huge and contains +230 talks as 2023 has been a really productive year in Java community. We had lots of exciting updates including the new LTS release (Java 21) bringing massive improvements like virtual threads or pattern matching to name a few.
Without further ado, here's the list:

1. "Asynchronous Programming in Java: Options to Choose from By Venkat Subramaniam" ⸱ +27k views ⸱ 02h 39m 22s
2. "Anatomy of a Spring Boot App with Clean Architecture by Steve Pember @ Spring I/O 2023" ⸱ +25k views ⸱ 00h 49m 53s
3. "Java in the Cloud with GraalVM • Alina Yurenko • GOTO 2023" ⸱ +25k views ⸱ 00h 42m 01s
4. "Structured Concurrency in Java: The What & Why • Balkrishna Rawool • GOTO 2023" ⸱ +23k views ⸱ 00h 41m 00s
5. "Spring I/O 2023 - Keynote" ⸱ +23k views ⸱ 01h 04m 38s
6. "Bootiful Spring Boot 3 by Josh Long" ⸱ +23k views ⸱ 00h 42m 09s
7. "Know your Java? By Venkat Subramaniam" ⸱ +21k views ⸱ 02h 39m 20s
8. "Bootiful Spring Boot 3 by Josh Long @ Spring I/O 2023" ⸱ +21k views ⸱ 00h 49m 44s
9. "Bootiful Spring Boot 3 x by Josh Long" ⸱ +20k views ⸱ 00h 44m 32s
10. "Java 21 By Brian Goetz" ⸱ +19k views ⸱ 00h 48m 25s
11. "Next-Generation Cloud Native Apps with Spring Boot 3 • Thomas Vitale • GOTO 2023" ⸱ +14k views ⸱ 00h 46m 09s
12. "Java Language update By Brian Goetz" ⸱ +13k views ⸱ 01h 02m 04s
13. "Going Native: Fast and Lightweight Spring Boot Applications with GraalVM by Alina Yurenko" ⸱ +12k views ⸱ 00h 47m 22s
14. "Do you really need Hibernate by Simon Martinelli @ Spring I/O 2023" ⸱ +11k views ⸱ 00h 54m 27s
15. "Observability of Your Application by Marcin Grzejszczak & Tommy Ludwig @ Spring I/O 2023" ⸱ +10k views ⸱ 00h 47m 31s
16. "Things I Wish I Knew When I Started Testing Spring Boot Applications by Philip Riecks @ Spring I/O" ⸱ +10k views ⸱ 00h 33m 09s
17. "Building Optimized Java Microservices with Micronaut 4 & GraalVM • Graeme Rocher • GOTO 2023" ⸱ +10k views ⸱ 00h 49m 22s
18. "Spring Modulith – Spring for the Architecturally Curious Developer by Oliver Drotbohm" ⸱ +10k views ⸱ 00h 49m 48s
19. "Enterprise Security with Spring Authorization Server 1.0 by Rob Winch @ Spring I/O" ⸱ +9k views ⸱ 00h 51m 24s
20. "Multitenant Mystery Only Rockers in the Building by Thomas Vitale @ Spring I/O 2023" ⸱ +9k views ⸱ 00h 50m 39s
21. "Bootiful Spring Boot 3 By Josh Long" ⸱ +8k views ⸱ 00h 50m 41s
22. "With Java 21, Your Code Runs Even Faster But How is that Possible? By Per Minborg" ⸱ +8k views ⸱ 00h 32m 06s
23. "Everything new in Spring Security 6 baked with a Spring Boot 3 recipe by Laur Spilca @ Spring I/O" ⸱ +8k views ⸱ 00h 50m 57s
24. "Action Jackson! Effective JSON processing in Spring Boot Applications by Joris Kuipers @ Spring I/O" ⸱ +8k views ⸱ 00h 46m 33s
25. "Preparing web applications for Loom by Mark Thomas @ Spring I/O 2023" ⸱ +7k views ⸱ 00h 35m 32s
26. "Spring Framework 6: Strategic Themes By Juergen Hoeller, Sébastien Deleuze" ⸱ +7k views ⸱ 00h 49m 53s
27. "Battle of the frameworks : Quarkus vs SpringBoot by Giorgos Andrianakis & Christos Sotiriou" ⸱ +7k views ⸱ 00h 39m 49s
28. "Know your Java? by Venkat Subramaniam" ⸱ +7k views ⸱ 00h 37m 41s
29. "Spring Security: The Good Parts by Daniel Garnier-Moiroux" ⸱ +7k views ⸱ 00h 45m 09s
30. "To Java 21 and Beyond! by Billy Korando @ Spring I/O 2023" ⸱ +6k views ⸱ 00h 51m 48s
31. "Java Meets AI: A Hands On Guide to Building LLM Powered Applications with LangChain4j By Lize Raes" ⸱ +6k views ⸱ 00h 50m 48s
32. "Introduction and pitfalls of Java's new concurrency model by David Vlijmincx" ⸱ +6k views ⸱ 00h 38m 12s
33. "[VDIASI23] - Ana-Maria Mihălceanu - A Glance At The Java Performance Toolbox" ⸱ +6k views ⸱ 00h 44m 00s
34. "Debugging applications with IntelliJ IDEA by Anton Arhipov @ Spring I/O 2023" ⸱ +6k views ⸱ 00h 45m 24s
35. "Spring Framework 6.1: Infrastructure Revisited by Juergen Hoeller @ Spring I/O 2023" ⸱ +5k views ⸱ 00h 49m 53s
36. "A Java 8 lambda is all you need for distributed background jobs! by Ronald Dehuysser" ⸱ +5k views ⸱ 00h 44m 25s
37. "Data Oriented Programming in Java 21 by Nicolai Parlog" ⸱ +5k views ⸱ 00h 48m 28s
38. "Developer Experience with Spring Boot on Kubernetes by Thomas Vitale @ Spring I/O 2023" ⸱ +5k views ⸱ 00h 38m 35s
39. "Taming performance issues into the wild: a practical guide to JVM profiling By Francesco Nigro, Mari" ⸱ +5k views ⸱ 02h 39m 23s
40. "Java 21 💣💥 By Nicolai Parlog" ⸱ +4k views ⸱ 02h 36m 56s
41. "Project Loom: Modern Scalable Concurrency for the Java Platform By Alan Bateman" ⸱ +4k views ⸱ 00h 51m 12s
42. "Java at AWS: Lessons Learned from Upgrading and Modernizing a Massive JVM Codebase By Yishai Galat" ⸱ +4k views ⸱ 00h 55m 45s
43. "REST next level: Crafting domain-driven web APIs by Julien Topçu @ Spring I/O 2023" ⸱ +4k views ⸱ 00h 51m 26s
44. "Build resilient systems with Spring Cloud Contract and Testcontainers by Olga & Oleg @ Spring I/O 23" ⸱ +4k views ⸱ 00h 51m 35s
45. ""A JVM threading model for the containerized times" by Luiz Hespanha and Flavio Brasil" ⸱ +4k views ⸱ 00h 30m 43s
46. "[VDBUH2023] - Nicolai Parlog - Data-Oriented Programming in Java (20)" ⸱ +4k views ⸱ 00h 51m 47s
47. "Dynamic OpenAPIs with Spring Cloud Gateway by Iván López @ Spring I/O 2023" ⸱ +4k views ⸱ 00h 47m 37s
48. "Vector Similarity Search in Spring with Redis Stack by Brian Sam-Bodden @ Spring I/O 2023" ⸱ +4k views ⸱ 00h 54m 36s
49. "Ask the Java Architects By Sharat Chander, Alan Bateman, Stuart Marks, Viktor Klang, Brian Goetz" ⸱ +4k views ⸱ 00h 50m 37s
50. "Let's make a contract: the art of designing a Java API by Mario Fusco" ⸱ +3k views ⸱ 00h 39m 27s
51. "Unit Test Your Java Architecture With ArchUnit by Roland Weisleder" ⸱ +3k views ⸱ 00h 43m 08s
52. "Java Renaissance • Georges Saab • YOW! 2023" ⸱ +3k views ⸱ 00h 46m 37s
53. "From k9s to OpenTelemetry:A guide to observability for your Spring apps in K8s by Matthias Haeussler" ⸱ +3k views ⸱ 00h 48m 05s
54. "Java Patterns and Practices for Serverless Applications By Adam Bien" ⸱ +3k views ⸱ 00h 56m 56s
55. "Spring Boot ❤️ Testcontainers by Iván López" ⸱ +3k views ⸱ 00h 45m 18s
56. "Building Spring Boot based modular libraries for 120 teams our findings by Jacek & Fabio" ⸱ +3k views ⸱ 00h 50m 19s
57. "Sailing Modern Java by Piotr Przybyl" ⸱ +3k views ⸱ 00h 46m 45s
58. "[VDCLUJ2023] Elias Nogueira - Modern Testing Tools for Java Developers" ⸱ +3k views ⸱ 00h 56m 57s
59. "What's new in Spring Batch 5 by Mahmoud Ben Hassine @ Spring I/O 2023" ⸱ +3k views ⸱ 00h 47m 17s
60. "Tips, tricks and gotchas when writing unit tests with Mockito by Jesse Kershaw" ⸱ +2k views ⸱ 00h 16m 09s
61. "Let's make a contract: the art of designing a Java API by Mario Fusco" ⸱ +2k views ⸱ 00h 47m 17s
62. "Building and Deploying Java Client Desktop Applications With JDK 21 and Beyond By Kevin Rushforth" ⸱ +2k views ⸱ 00h 40m 49s
63. "The Panama Dojo: Black Belt Programming with Java 21 and the FFM API By Per Minborg" ⸱ +2k views ⸱ 00h 52m 06s
64. "Architecturally evident Spring applications with jMolecules by Oliver Drotbohm @ Spring I/O 2023" ⸱ +2k views ⸱ 00h 50m 10s
65. "Java Next - From Amber to Loom, from Panama to Valhalla by Nicolai Parlog" ⸱ +2k views ⸱ 00h 46m 30s
66. "Java 8 (and 9!) in Anger • Trisha Gee • YOW! 2016" ⸱ +2k views ⸱ 00h 49m 02s
67. "All your APIs are mine - Secure them now by Andreas Falk @ Spring I/O 2023" ⸱ +2k views ⸱ 00h 44m 25s
68. "Spring Boot in a Polyglot Cloud-Native World with Dapr by Mauricio Salatino @ Spring I/O 2023" ⸱ +2k views ⸱ 00h 51m 23s
69. "Deep diving in Spring Security with the latest trends and additions By Laur Spilca" ⸱ +2k views ⸱ 02h 32m 51s
70. "Spring Infrastructure Deep Dive: Virtual Threads, Checkpoint Restore, Native Images By Juergen Hoell" ⸱ +2k views ⸱ 02h 32m 14s
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72. "Develop and test your AWS-powered Spring Boot application locally by Anca Ghenade @ Spring I/O 2023" ⸱ +2k views ⸱ 00h 47m 36s
73. "Functional Programming in Spring with Arrow, Lenses & Effects • Jacob Bass • YOW! 2019" ⸱ +2k views ⸱ 00h 28m 32s
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75. "Effectively running Java applications on AWS By Maximilian Schellhorn, Dennis Kieselhorst" ⸱ +2k views ⸱ 02h 51m 20s
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78. "The Art of Java Language Pattern Matching by Simon Ritter" ⸱ +2k views ⸱ 00h 41m 34s
79. "JavaFX Notebook By Kevin Rushforth" ⸱ +2k views ⸱ 00h 49m 55s
80. "Observing Spring for GraphQL in Action by Brian Clozel & Rossen Stoyanchev @ Spring I/O 2023" ⸱ +2k views ⸱ 00h 49m 49s
81. "Building Lean Spring Boot Applications for the Cloud by Patrick Baumgartner" ⸱ +2k views ⸱ 00h 40m 43s
82. "Bootiful AOT with Spring Boot 3 By Josh Long, Alina Yurenko" ⸱ +2k views ⸱ 02h 46m 22s
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84. "Bootiful Spring Boot 3 Josh Long Devoxx Ukraine 2023" ⸱ +1k views ⸱ 00h 38m 00s
85. "Spring is bootiful but so is your domain by Michael Plöd @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 47m 52s
86. "Java 21 and Beyond: A Roadmap of Innovations by Ana-Maria Mihalceanu" ⸱ +1k views ⸱ 00h 45m 15s
87. "The Java Cloud-Native Stack for Microservices and Serverless Architecture by Markus Kett" ⸱ +1k views ⸱ 00h 45m 44s
88. "Dockerfiles, Buildpacks, Jib and more what's the best way to run your Java code in Containers?" ⸱ +1k views ⸱ 00h 31m 29s
89. "Awesome Java applications with GraalVM and Java microservices frameworks by Аlina Yurenko" ⸱ +1k views ⸱ 00h 38m 35s
90. "Spring Modulith – Spring for the Architecturally Curious Developer by Oliver Drotbohm" ⸱ +1k views ⸱ 00h 47m 52s
91. "Who needs Hibernate when there is SQL? By Simon Martinelli" ⸱ +1k views ⸱ 02h 31m 00s
92. "Serverless Java with Spring Boot" ⸱ +1k views ⸱ 00h 51m 25s
93. "Java 11 to 21 Evolution! Mohamed Taman Devoxx Ukraine 2023" ⸱ +1k views ⸱ 01h 02m 10s
94. "Write your own Java Profiler in 240 lines of pure Java By Johannes Bechberger" ⸱ +1k views ⸱ 00h 45m 56s
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96. "Keeping Your Java Hot by Solving the JVM Warmup Problem" ⸱ +1k views ⸱ 01h 02m 30s
97. "How sand and Java are used to create the world’s most powerful chips By Johan Janssen" ⸱ +1k views ⸱ 00h 48m 54s
98. "Introduction and pitfalls of Java's new concurrency model - David Vlijmincx" ⸱ +1k views ⸱ 00h 37m 41s
99. "Securing the Supply Chain for Your Java Applications By Thomas Vitale" ⸱ +1k views ⸱ 00h 51m 29s
100. "Welcome to the Jungle - A safari through the JVM landscape by Gerrit Grunwald" ⸱ +1k views ⸱ 00h 38m 47s
101. "Testing with Spring, AOT, GraalVM, and JUnit 5 by Sam Brannen @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 43m 41s
102. "Progressive Delivery in the Kubernetes era by Alex Soto @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 41m 26s
103. "Generative AI in practice: Concrete LLM use cases in Java, with the PaLM API By Guillaume Laforge" ⸱ +1k views ⸱ 00h 51m 57s
104. "Speed up writing tests with Wiremock Spring Boot By Pieter Jan Drouillon" ⸱ +1k views ⸱ 00h 28m 17s
105. "Managing Spring Boot Application Secrets by Badr NASS LAHSEN @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 52m 28s
106. "Bootiful workload orchestration with Hashicorp Nomad by Martin Ahrer @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 52m 53s
107. "Everything new in Spring Security 6 baked with a Spring Boot 3 recipe By Laur Spilca" ⸱ +1k views ⸱ 00h 50m 26s
108. "Securing the Service to Service Call Chain Patterns and Protocols by Adib Saikali @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 43m 29s
109. "Why Spring Belongs In Your Data Stream (From Edge to Multi Cloud) by Fabrizio Marini @ Spring I/O 23" ⸱ +1k views ⸱ 00h 44m 45s
110. "The JVM vs WebAssembly: An In Depth Comparative Analysis By Shivansh Vij" ⸱ +1k views ⸱ 01h 33m 05s
111. "Introducing Spring AI" ⸱ +1k views ⸱ 01h 06m 39s
112. "Kotlin for Fun for Spring Fans by Shinya Yanagihara @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 42m 40s
113. "Algebraic Data Types + Pattern Matching = Elegant and readable Java code By Balkrishna Rawool" ⸱ +1k views ⸱ 00h 43m 57s
114. "Voxxed Days Thessaloniki 2023 - Async Showdown: Java Virtual Threads vs. Kotlin Coroutines" ⸱ +1k views ⸱ 00h 43m 56s
115. "Java 21 Unveiled: A Quick Tour of What's New by Alberto Cortina Eduarte" ⸱ +1k views ⸱ 00h 14m 43s
116. "AWS Lambda SnapStart: Dramatically reduce cold starts for your Java functions by Melina & Kevin" ⸱ +1k views ⸱ 00h 40m 21s
117. "Moving Java Forward Together By Sharat Chander" ⸱ +1k views ⸱ 00h 35m 20s
118. "The Aggregate is dead. Long live the Aggregate! by Sara Pellegrini & Milan Savic @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 47m 13s
119. "Java, Code Coverage & Their Best Friend: Bytecode • Evgeny Mandrikov • YOW! 2023" ⸱ +1k views ⸱ 00h 45m 58s
120. "Bootiful Spring Boot 3.x by Josh Long" ⸱ +1k views ⸱ 00h 50m 39s
121. "Do you really need Hibernate? By Simon Martinelli" ⸱ +1k views ⸱ 00h 54m 22s
122. "A Java lambda is all you need for distributed background jobs! By Ronald Dehuysser" ⸱ +1k views ⸱ 00h 31m 17s
123. "[VDIASI23] - Rustam Mehmandarov & Mads Opheim - Modern Java App Development in the Cloud" ⸱ +1k views ⸱ 00h 41m 46s
124. "ML in Java, YES it's possible! By Mohammed Aboullaite" ⸱ +1k views ⸱ 00h 31m 12s
125. "[VDBUH2023] - Johan Janssen - Why and How to Upgrade to Java 17 (and Prepare for 21)" ⸱ +1k views ⸱ 00h 44m 52s
126. "[VDBUH2023] Ana-Maria Mihălceanu & Nicolai Parlog - Keynote: The SolutionFactory To Java's Problems" ⸱ +1k views ⸱ 00h 50m 28s
127. "Scale your @Controller to zero with AWS Lambda or Azure Function by Oleg Zhurakousky @ Spring I/O" ⸱ +1k views ⸱ 00h 46m 57s
128. "Automating away bugs with Error Prone in practice by Rick Ossendrijver @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 44m 49s
129. "Test-Driven Security with Spring 6 by Eleftheria Stein-Kousathana" ⸱ +1k views ⸱ 00h 39m 32s
130. "A Glance At The Java Performance Toolbox by Ana Maria Mihalceanu" ⸱ +1k views ⸱ 00h 40m 17s
131. "[VDCLUJ2023] Rustam Mehmandarov & Mads Opheim - Modern Java App Development in the Cloud" ⸱ +1k views ⸱ 00h 45m 52s
132. "Beam Me Up, Java! Unraveling the Warp-Speed Evolution: A Journey through Java Jonathan Vila (EN)" ⸱ +1k views ⸱ 00h 46m 47s
133. "The Art of Java Language Pattern Matching Simon Ritter Devoxx Ukraine 2023" ⸱ +1k views ⸱ 00h 56m 07s
134. "The Easy Way to Run and Scale Spring Apps on Cloud by Sean Li & Adib Saikali @ Spring I/O 2023" ⸱ +1k views ⸱ 00h 54m 39s
135. "A Glance At The Java Performance Toolbox By Ana Maria Mihalceanu" ⸱ +1k views ⸱ 00h 43m 04s
136. "Say the Words: Modern Java with JavaFX and GraalVM for Rich Client UIs By Paul & Gail Anderson" ⸱ +900 views ⸱ 00h 51m 41s
137. "From Spring Native to Spring Boot 3 by Moritz Halbritter & Sébastien Deleuze @ Spring I/O 2023" ⸱ +900 views ⸱ 01h 00m 31s
138. "Java Observability with OpenTelemetry By Andrzej Kubik" ⸱ +900 views ⸱ 00h 50m 49s
139. "Java Meets AI: How to build LLM-Powered Applications with LangChain4j by Lize Raes" ⸱ +800 views ⸱ 00h 46m 41s
140. "Devnexus 2023 - Spring Modulith: What the What? - Felipe Gutierrez, Glenn Renfro" ⸱ +800 views ⸱ 00h 48m 14s
141. "A hitchhikers guide to observe Java applications in Kubernetes By Tiffany Jernigan, Matthias Haeussl" ⸱ +800 views ⸱ 02h 44m 35s
142. "Keeping Your Java Hot by Solving the JVM Warmup Problem By Simon Ritter" ⸱ +800 views ⸱ 00h 45m 45s
143. "Java is Agile by Venkat Subramaniam" ⸱ +800 views ⸱ 00h 45m 14s
144. "A Glance At The Java Performance Toolbox Ana-Maria Mihalceanu Devoxx Ukraine 2023" ⸱ +800 views ⸱ 00h 42m 57s
145. "Mastering GC: tame the beast and make it your best ally by Jean-Philippe Bempel @ Spring I/O 2023" ⸱ +800 views ⸱ 00h 44m 16s
146. "Master the Fundamentals of Java 21 by Cracking Code Challenges" ⸱ +800 views ⸱ 01h 05m 28s
147. "Devnexus 2023 - Asynchronous Programming in Java using Virtual Threads - Venkat Subramaniam" ⸱ +800 views ⸱ 00h 50m 02s
148. "Securing Your Java Containers by Breaking In By Brian Vermeer" ⸱ +800 views ⸱ 00h 46m 18s

... here's the remaining part of the list
Let me know what do you think and if you wish to see more posts like this in /java!
Changelog: - 2023-02-23: added missing conferences from the comments and updated view counts.

I am the creator of the Maven JPackage template. Basically it's a nice starting point for folks that are interested in building JavaFX or Swing apps that will generate nice Windows, macOS, and Linux installers. It uses jlink to produce small JVMs while also maintaining compatibility with standard Maven dependency management.
Over the years, I have had several people ping me about using this template with Spring Boot.
I've got two ideas for how to do this properly.

1. create a template using the JavaFX web view. Pro: fairly easy to do. Con: Relies on the JavaFX embedded web view, which I believe is based on WebKit. Minimum app size for a Hello World I believe would be around 60mb.
   
2. create a template that uses GraalVM and Tauri. Pro: the experiments I've done have shown this to be quite fast to load. I can add an interface back to the JVM code to make calls into the Tauri subsystems just like the JavaScript code via Tauri commands, which includes much more modern APIs. Uses the modern browser webviews. No reliance on Swing or JavaFX. As Tauri mobile comes out, I think it could even support mobile. Could use the Tauri built-in auto-updater system. Cons: GraalVM is slower for builds.
   

My question is... would anyone use either of these? If you would use it, would it be for personal projects / solo developer stuff, or would this be something interesting for enterprise[s] or commercial stuff?

I am currently hosting an ATM9 server for myself.
​
If i run 1 chunk destroyer the TPS drops from 20 to 10, with 2 running it drops to 7.
​
The server has 4vcores 20GB dedicated, Ubuntu ARM.
Im using GraalVM 21 with the following args: -XX:+UnlockExperimentalVMOptions -XX:+UnlockDiagnosticVMOptions -XX:+AlwaysActAsServerClassMachine -XX:+AlwaysPreTouch -XX:+DisableExplicitGC -XX:+UseNUMA -XX:AllocatePrefetchStyle=3 -XX:NmethodSweepActivity=1 -XX:ReservedCodeCacheSize=400M -XX:NonNMethodCodeHeapSize=12M -XX:ProfiledCodeHeapSize=194M -XX:NonProfiledCodeHeapSize=194M -XX:-DontCompileHugeMethods -XX:+PerfDisableSharedMem -XX:+UseFastUnorderedTimeStamps -XX:+UseCriticalJavaThreadPriority -XX:+EagerJVMCI -Dgraal.TuneInlinerExploration=1 -Dgraal.CompilerConfiguration=enterprise
​
Is there any way to improve TPS with a chunk destroyer running?

Pierre Misse-Chanabier will talk to us about Polyphemus for the Pharo Virtual Machine.
The presentation will focus on how to create Tooling on the Pharo Virtual Machine. (This does not require Virtual machine level knowledge).
We will start by taking a look at a few existing tools. We will create one or two small tools, and see how they differ from tooling on the image side.
​
Pierre Misse Chanabier is a recently graduated PhD with a focused interest on Virtual Machines, Code Generation, and Meta Programming. He worked on and contributed to many different levels and parts of the Pharo ecosystem.
He is now working on how to leverage images for more than what they do now. He's currently working at Microdoc on the Graal VM.
Born in south of France, he currently lives in Lille.
​
This will be an online meeting from home. This is a repeat of last November's presentation that could not go ahead due to issues with our Zoom account.
​
If you'd like to join us, please sign up in advance on the meeting's Meetup page to receive the meeting details. Don’t forget to bring your laptop and drinks!

MS-ISAC CYBERSECURITY ADVISORY
MS-ISAC ADVISORY NUMBER: 2024-007
DATE(S) ISSUED: 01/18/2024
SUBJECT: Oracle Quarterly Critical Patches Issued January 16, 2024
OVERVIEW: Multiple vulnerabilities have been discovered in Oracle products, the most severe of which could allow for remote code execution.
SYSTEMS AFFECTED:

• Fujitsu M10-1, M10-4, M10-4S, M12-1, M12-2, M12-2S Servers, versions prior to XCP2430, prior to XCP3130, prior to XCP4040
• GoldenGate Big Data and Application Adapters, versions 19.1.0.0.0-19.1.0.0.16, 21.3-21.12
• Integrated Lights Out Manager (ILOM), versions 3, 4, 5
• JD Edwards EnterpriseOne Orchestrator, versions prior to 9.2.8.0
• JD Edwards EnterpriseOne Tools, versions prior to 9.2.8.1
• MySQL Cluster, versions 7.5.32 and prior, 7.6.28 and prior, 8.0.35 and prior, 8.1.0, 8.2.0 and prior
• MySQL Connectors, versions 8.0.35 and prior, 8.2.0 and prior
• MySQL Enterprise Monitor, versions 8.0.36 and prior
• MySQL Server, versions 8.0.35 and prior, 8.1.0, 8.2.0 and prior
• MySQL Workbench, versions 8.0.34 and prior
• Oracle Access Manager, version 12.2.1.4.0
• Oracle Agile PLM, version 9.3.6
• Oracle Agile Product Lifecycle Management for Process, versions prior to 6.2.4.2
• Oracle Analytics Desktop, versions 6.4.0.0.0, prior to 7.2
• Oracle Application Testing Suite, version 13.3.0.1
• Oracle Audit Vault and Database Firewall, versions 20.1-20.9
• Oracle Banking APIs, versions 19.1.0, 21.1.0, 22.1.0, 22.2.0
• Oracle Banking Branch, versions 14.5.0-14.7.0
• Oracle Banking Cash Management, versions 14.5.0-14.7.0
• Oracle Banking Collections and Recovery, versions 14.5.0-14.7.0
• Oracle Banking Corporate Lending Process Management, versions 14.5.0-14.7.0
• Oracle Banking Credit Facilities Process Management, versions 14.5.0-14.7.0
• Oracle Banking Digital Experience, versions 19.1.0, 21.1.0, 22.1.0, 22.2.0
• Oracle Banking Electronic Data Exchange for Corporates, versions 14.5.0-14.7.0
• Oracle Banking Enterprise Default Management, versions 14.5.0-14.7.0
• Oracle Banking Extensibility Workbench, versions 14.5.0-14.7.0
• Oracle Banking Liquidity Management, versions 14.5.0-14.7.0, 14.7.0.3.0
• Oracle Banking Origination, versions 14.5.0-14.7.0
• Oracle Banking Party Management, versions 14.5.0-14.7.0
• Oracle Banking Supply Chain Finance, versions 14.5.0-14.7.0
• Oracle Banking Trade Finance Process Management, versions 14.5.0-14.7.0
• Oracle Banking Virtual Account Management, versions 14.5.0-14.7.0
• Oracle BI Publisher, versions 6.4.0.0.0, 7.0.0.0.0, 12.2.1.4.0
• Oracle Big Data Spatial and Graph, version 3.0.4
• Oracle Business Intelligence Enterprise Edition, versions 6.4.0.0.0, 7.0.0.0.0, 12.2.1.4.0
• Oracle Business Process Management Suite, version 12.2.1.4.0
• Oracle Coherence, versions 12.2.1.4.0, 14.1.1.0.0
• Oracle Commerce Guided Search, version 11.3.2
• Oracle Commerce Platform, version 11.3.2
• Oracle Communications ASAP, version 7.4
• Oracle Communications Billing and Revenue Management, versions 12.0.0.4.0-12.0.0.8.0, 15.0.0.0.0
• Oracle Communications BRM - Elastic Charging Engine, versions 12.0.0.4-12.0.0.8
• Oracle Communications Cloud Native Core Automated Test Suite, versions 23.1.3, 23.2.1, 23.3.0
• Oracle Communications Cloud Native Core Console, versions 23.3.0, 23.3.1
• Oracle Communications Cloud Native Core Network Data Analytics Function, versions 23.3.0, 23.4.0
• Oracle Communications Cloud Native Core Network Exposure Function, version 23.3.1
• Oracle Communications Cloud Native Core Network Function Cloud Native Environment, versions 23.1.0, 23.2.0, 23.3.1
• Oracle Communications Cloud Native Core Network Repository Function, versions 23.1.4, 23.3.1
• Oracle Communications Cloud Native Core Network Slice Selection Function, versions 23.2.0, 23.3.1
• Oracle Communications Cloud Native Core Security Edge Protection Proxy, versions 23.1.0, 23.2.0, 23.3.0
• Oracle Communications Cloud Native Core Unified Data Repository, version 23.3.1
• Oracle Communications Convergence, versions 3.0.3.2, 3.0.3.3
• Oracle Communications Convergent Charging Controller, versions 6.0.1.0.0, 12.0.1.0.0-12.0.6.0.0, 15.0.0.0.0
• Oracle Communications Diameter Signaling Router, versions 8.6.0.0, 9.0.0.0
• Oracle Communications Element Manager, versions 9.0.0.0.0-9.0.2.0.1, 9.4.53
• Oracle Communications Fraud Monitor, versions 5.0, 5.1
• Oracle Communications Instant Messaging Server, version 10.0.1.7.0
• Oracle Communications IP Service Activator, versions 7.4.0, 7.5.0
• Oracle Communications Messaging Server, version 8.1.0.24.0
• Oracle Communications MetaSolv Solution, version 6.3.1.0.0
• Oracle Communications Network Analytics Data Director, versions 23.2.0.0.2, 23.3.0.0.0
• Oracle Communications Network Charging and Control, versions 6.0.1.0.0, 12.0.1.0.0-12.0.6.0.0, 15.0.0.0.0
• Oracle Communications Order and Service Management, versions 7.4.0, 7.4.1
• Oracle Communications Policy Management, versions 12.6.1.0.0, 15.0.0.0.0
• Oracle Communications Pricing Design Center, versions 12.0.0.4.0-12.0.0.8.0, 15.0.0.0.0
• Oracle Communications Service Catalog and Design, versions 7.4.0.7.0, 7.4.1.5.0, 7.4.2.8.0
• Oracle Communications Session Report Manager, versions 9.0.0.0.0-9.0.2.0.1, 9.4.53
• Oracle Communications Unified Assurance, versions 5.0.0-5.5.19, 6.0.0-6.0.3
• Oracle Communications Unified Inventory Management, versions 7.4.0, 7.4.1, 7.4.2
• Oracle Complex Maintenance, Repair, and Overhaul, versions 11.5, 12.1, 12.2
• Oracle Database Server, versions 19.3-19.21, 21.3-21.12, 22.3-23.8, 23.9.0-23.9.4, 23.10
• Oracle E-Business Suite, versions 12.2.3-12.2.13
• Oracle Enterprise Data Quality, version 12.2.1.4.0
• Oracle Enterprise Manager Base Platform, version 13.5.0.0
• Oracle Enterprise Manager for Fusion Middleware, version 13.5.0.0
• Oracle Enterprise Manager for Oracle Database, version 13.5.0.0
• Oracle Enterprise Manager for Oracle Virtual Infrastructure, version 13.5.0.0
• Oracle Enterprise Manager for Virtualization, version 13.5.0.0
• Oracle Enterprise Manager Ops Center, version 12.4.0.0
• Oracle Essbase, version 21.5.3.0.0
• Oracle Financial Services Analytical Applications Infrastructure, versions 8.0.7, 8.0.8, 8.0.9, 8.1.0, 8.1.1, 8.1.2
• Oracle Financial Services Behavior Detection Platform, versions 8.0.8.1, 8.1.1.1, 8.1.2.5, 8.1.2.6
• Oracle Financial Services Compliance Studio, version 8.1.2.5
• Oracle Financial Services Enterprise Case Management, versions 8.0.8.2, 8.1.1.1, 8.1.2.5, 8.1.2.6
• Oracle Financial Services Lending and Leasing, versions 14.5.0-14.7.0
• Oracle Financial Services Revenue Management and Billing, versions 2.7.1, 2.8.0, 2.9.0, 2.9.1, 3.0.0-3.2.0, 4.0.0, 5.0.0, 5.1.0, 6.0.0
• Oracle Financial Services Trade-Based Anti Money Laundering Enterprise Edition, version 8.0.8
• Oracle FLEXCUBE Enterprise Limits and Collateral Management, versions 14.5.0-14.7.0
• Oracle FLEXCUBE Investor Servicing, versions 14.5.0-14.7.0
• Oracle FLEXCUBE Private Banking, versions 14.5.0-14.7.0
• Oracle Fusion Middleware, version 12.2.1.4.0
• Oracle Global Lifecycle Management OPatch, versions prior to 12.2.0.1.40
• Oracle GoldenGate, versions 19.1.0.0.0-19.1.0.0.231017, 21.3-21.12
• Oracle GoldenGate Studio, version 12.2.0.4.0
• Oracle GraalVM Enterprise Edition, versions 20.3.12, 21.3.8, 22.3.4
• Oracle GraalVM for JDK, versions 17.0.9, 21.0.1
• Oracle Graph Server and Client, versions prior to 22.4.6, prior to 23.4.0
• Oracle HTTP Server, version 12.2.1.4.0
• Oracle Hyperion Calculation Manager, version 11.2.14.0.0
• Oracle Hyperion Financial Data Quality Management, Enterprise Edition, version 11.2.14.0.0
• Oracle Hyperion Financial Management, version 11.2.14.0.0
• Oracle Hyperion Financial Reporting, version 11.2.14.0.0
• Oracle Hyperion Infrastructure Technology, version 11.2.14.0.0
• Oracle Hyperion Planning, version 11.2.14.0.0
• Oracle Identity Manager, version 12.2.1.4.0
• Oracle Java SE, versions 8u391, 8u391-perf, 11.0.21, 17.0.9, 21.0.1
• Oracle JDeveloper, version 12.2.1.4.0
• Oracle Managed File Transfer, version 12.2.1.4.0
• Oracle Middleware Common Libraries and Tools, version 12.2.1.4.0
• Oracle NoSQL Database, versions prior to 1.6, prior to 19.5.40, prior to 20.3.38, prior to 21.2.30, prior to 22.3.94, prior to 23.1.29
• Oracle Outside In Technology, version 8.5.6
• Oracle REST Data Services, versions prior to 23.3.0
• Oracle Retail Advanced Inventory Planning, versions 15.0.3, 16.0.3
• Oracle Retail Customer Management and Segmentation Foundation, versions 18.0.0.14, 19.0.0.8
• Oracle Retail EFTLink, versions 20.0.1, 21.0.0-23.0.0
• Oracle Secure Backup, versions prior to 18.1.0.2.0
• Oracle Service Bus, version 12.2.1.4.0
• Oracle SOA Suite, version 12.2.1.4.0
• Oracle Solaris, version 11
• Oracle SQL Developer, versions 21.4.2, 22.2.0, 23.1.0
• Oracle Utilities Network Management System, versions 2.3.0.2, 2.4.0.1, 2.5.0.1, 2.5.0.2, 2.6.0.0, 2.6.0.1
• Oracle Utilties Application Framework, versions 4.3.0.3.0-4.3.0.6.0, 4.4.0.0.0, 4.4.0.2.0, 4.4.0.3.0, 4.5.0.0.0, 4.5.0.1.1, 4.5.0.1.3
• Oracle WebCenter Content, version 12.2.1.4.0
• Oracle WebCenter Portal, version 12.2.1.4.0
• Oracle WebCenter Sites, version 12.2.1.4.0
• Oracle WebLogic Server, versions 12.2.1.4.0, 14.1.1.0.0
• Oracle ZFS Storage Appliance Kit, version 8.8
• PeopleSoft Enterprise PeopleTools, versions 8.59, 8.60, 8.61
• Primavera P6 Enterprise Project Portfolio Management, versions 19.12.0-19.12.22, 20.12.0-20.12.20, 21.12.0-21.12.17, 22.12.0-22.12.10
• Primavera Unifier, versions 19.12.0-19.12.16, 20.12.0-20.12.16, 21.12.0-21.12.17, 22.12.0-22.12.11
• Siebel Applications, versions prior to 23.12
• TimesTen In-Memory Database, versions prior to 21.1.1.19.0, prior to 22.1.1.19.0

RISK: Government:

• Large and medium government entities: High
• Small government entities: High

Businesses:

• Large and medium business entities: High
• Small business entities: High

Home users: Low
RECOMMENDATIONS: We recommend the following actions be taken:

• Apply appropriate patches or appropriate mitigations provided by Oracle to vulnerable systems immediately after appropriate testing. (M1051: Update Software)
  • Safeguard 7.1: Establish and Maintain a Vulnerability Management Process: Establish and maintain a documented vulnerability management process for enterprise assets. Review and update documentation annually, or when significant enterprise changes occur that could impact this Safeguard.
  • Safeguard 7.2: Establish and Maintain a Remediation Process: Establish and maintain a risk-based remediation strategy documented in a remediation process, with monthly, or more frequent, reviews.
  • Safeguard 7.4: Perform Automated Application Patch Management: Perform application updates on enterprise assets through automated patch management on a monthly, or more frequent, basis.
  • Safeguard 7.5 : Perform Automated Vulnerability Scans of Internal Enterprise Assets: Perform automated vulnerability scans of internal enterprise assets on a quarterly, or more frequent, basis. Conduct both authenticated and unauthenticated scans, using a SCAP-compliant vulnerability scanning tool.
  • Safeguard 7.7: Remediate Detected Vulnerabilities: Remediate detected vulnerabilities in software through processes and tooling on a monthly, or more frequent, basis, based on the remediation process.
  • Safeguard 12.1: Ensure Network Infrastructure is Up-to-Date: Ensure network infrastructure is kept up-to-date. Example implementations include running the latest stable release of software and/or using currently supported network-as-a-service (NaaS) offerings. Review software versions monthly, or more frequently, to verify software support.
  • Safeguard 18.1: Establish and Maintain a Penetration Testing Program: Establish and maintain a penetration testing program appropriate to the size, complexity, and maturity of the enterprise. Penetration testing program characteristics include scope, such as network, web application, Application Programming Interface (API), hosted services, and physical premise controls; frequency; limitations, such as acceptable hours, and excluded attack types; point of contact information; remediation, such as how findings will be routed internally; and retrospective requirements.
  • Safeguard 18.2: Perform Periodic External Penetration Tests: Perform periodic external penetration tests based on program requirements, no less than annually. External penetration testing must include enterprise and environmental reconnaissance to detect exploitable information. Penetration testing requires specialized skills and experience and must be conducted through a qualified party. The testing may be clear box or opaque box.
  • Safeguard 18.3: Remediate Penetration Test Findings: Remediate penetration test findings based on the enterprise’s policy for remediation scope and prioritization.
• Vulnerability scanning is used to find potentially exploitable software vulnerabilities to remediate them. (M1016: Vulnerability Scanning)
  • Safeguard 16.13: Conduct Application Penetration Testing: Conduct application penetration testing. For critical applications, authenticated penetration testing is better suited to finding business logic vulnerabilities than code scanning and automated security testing. Penetration testing relies on the skill of the tester to manually manipulate an application as an authenticated and unauthenticated user.
• Apply the Principle of Least Privilege to all systems and services, and run all software as a non-privileged user (one without administrative rights) to diminish the effects of a successful attack. (M1026: Privileged Account Management)
  • Safeguard 4.7: Manage Default Accounts on Enterprise Assets and Software: Manage default accounts on enterprise assets and software, such as root, administrator, and other pre-configured vendor accounts. Example implementations can include: disabling default accounts or making them unusable.
  • Safeguard 5.4: Restrict Administrator Privileges to Dedicated Administrator Accounts: Restrict administrator privileges to dedicated administrator accounts on enterprise assets. Conduct general computing activities, such as internet browsing, email, and productivity suite use, from the user’s primary, non-privileged account.
  • Safeguard 5.5: Establish and Maintain an Inventory of Service Accounts: Establish and maintain an inventory of service accounts. The inventory, at a minimum, must contain department owner, review date, and purpose. Perform service account reviews to validate that all active accounts are authorized, on a recurring schedule at a minimum quarterly, or more frequently
• Remind all users not to visit untrusted websites or follow links/open files provided by unknown or untrusted sources. (M1017: User Training)
  • Safeguard 14.1: Establish and Maintain a Security Awareness Program: Establish and maintain a security awareness program. The purpose of a security awareness program is to educate the enterprise’s workforce on how to interact with enterprise assets and data in a secure manner. Conduct training at hire and, at a minimum, annually. Review and update content annually, or when significant enterprise changes occur that could impact this Safeguard.
  • Safeguard 14.2: Train Workforce Members to Recognize Social Engineering Attacks: Train workforce members to recognize social engineering attacks, such as phishing, pre-texting, and tailgating.
• Use capabilities to prevent suspicious behavior patterns from occurring on endpoint systems. This could include suspicious process, file, API call, etc. behavior. (M1040 : Behavior Prevention on Endpoint)
  • Safeguard 13.2 : Deploy a Host-Based Intrusion Detection Solution: Deploy a host-based intrusion detection solution on enterprise assets, where appropriate and/or supported.
  • Safeguard 13.7 : Deploy a Host-Based Intrusion Prevention Solution: Deploy a host-based intrusion prevention solution on enterprise assets, where appropriate and/or supported. Example implementations include use of an Endpoint Detection and Response (EDR) client or host-based IPS agent.
• Use capabilities to detect and block conditions that may lead to or be indicative of a software exploit occurring. (M1050: Exploit Protection)
  • Safeguard 10.5: Enable Anti-Exploitation Features: Enable anti-exploitation features on enterprise assets and software, where possible, such as Microsoft® Data Execution Prevention (DEP), Windows® Defender Exploit Guard (WDEG), or Apple® System Integrity Protection (SIP) and Gatekeeper™.

REFERENCES:

Oracle: https://www.oracle.com/security-alerts/cpujan2024.html

This is a follow up to my recent post where I gave a brief performance guide with some tips that had recently given me some really significant gains that I wanted to share. I didn't want to spam feedthebeast, and I figured you guys are more worthy of this information. There were some major issues with my methodology that lead me to share some false conclusions. Some comments (thanks u/starlevel01, u/scratchisthebest, u/IThundxr, u/G0D3P5) made me decide to spend hours creating and performing more sound benchmarks. Results can be found in this google sheet. The most significant claim I made was that GraalVM enterprise edition could significantly reduce your memory usage and thus significantly improve your performance on low end machines.

Testing methodology

I ran testing on my computer (Ryzen 3600, GTX 1660, 32GB system RAM) with All The Mods 8 version 1.1.0 (a 1.19.2 based pack). In order to test Java 21 (which is not officially supported on 1.19, but can work), I upgraded forge to 43.3.5 from 43.2.14. I disabled Oculus and Simple Backups to improve consistency in my testing. I created a consistent world save to use. I collected TPS/GC info from Spark, and I collected FPS info from PresentMon. I ran tests with three amounts of allocated memory: 6GB, 8GB and 10GB. I decided these would represent low, normal and excessive amounts of memory allocated.
JVMs tested:

• Adoptium 17
• Adoptium 21
• Oracle GraalVM 17
• Oracle GraalVM 21
• Oracle GraalVM 17 Enterprise Edition (soon to be deprecated)

Java args tested:

• None
• G1GC from BruceTheMoose
• G1GC for Graal from BruceTheMoose
• Shenandoah from BruceTheMoose
• ZGC from BruceTheMoose
• ZGC from 1ByteBit

Testing results

TLDR: Adoptium 17 with no arguments or G1GC args gave me superior performance in all RAM scenarios.

Garbage collectors/arguments

I was unable to get ZGC to perform better for me in any scenario. This could be because ZGC would benefit from additional/more powerful CPU cores. This is an important reminder: specific JVM performance is machine dependent. I was also unable to get Shenandoah to outperform G1GC/no args, which could also be due to my hardware. The idea that it is actually pretty difficult to beat the default JVM parameters was shown in these results.

Java 17 vs. 21

In my testing on a 1.19 modpack, Java 21 JVMs underperformed their Java 17 counterparts. One major improvement in Java 21 is supposed to be in ZGC, but I was not able to see that very well, probably since my ZGC never worked very well. I expect is that Java 17 is still getting a lot of the performance improvements that 21 is. I'm not sure if there are some performance benefits 21 has that require some difference in code to be active, but you wouldn't get that on 1.19 since Java 17 is the supported version. In summary, for 1.16-1.19 I would just use Java 17. For 1.20+ use Java 21.

Adoptium vs. GraalVM

I did not see a scenario where GraalVM outperformed Adoptium. The idea with GraalVM is that it is supposed to do better with fewer resources, and I think you could argue my results show GraalVM dropping less performance than Adoptium with less RAM, but GraalVM was never better. There was no difference between the standard and enterprise editions, confirming that when GraalVM was rereleased and the community and enterprise editions where merged, the exclusive performance enhancements in the enterprise edition were preserved. If you are going to use GraalVM, it would be best to use the new version and not the enterprise edition.
GraalVM did tend to have good minimum frame rates and tick rates, meaning less stuttering. This can lead to a better perceived experience. If you are having stutters, I’d try GraalVM.

My previous errors

• When I switched some low end machines to GraalVM 17 EE, I saw some huge improvements. This was probably because I was changing some 1.16 instances that were using Adoptium 8. A comparison between Adoptium 17 and GraalVM 17 would probably be pretty close.
• When I performed rudimentary testing on my own machine, I initially measured a marginal improvement with GraalVM and certain Java arguments. To reduce the number of tests I needed to do, I only tested future iterations on those settings. If I had also tested with Adoptium and no args, I probably would have seen similar performance between them.

Obligatory greg

Running meaningless benchmarks for hours was almost as fun as gregging, but seeing that my setup did not explode due to rain, it was not as fun.

Edit after the fact (justice for ZGC)

Using u/azureaquatic 's ZGC instructions in the comments I was able to replicate the results of absolutely no visual studders whatsoever for GC. I am not going to take the time to formally benchmark it, but I can say that I assume the numbers would show it is at least as good overall and I think probably significantly better in 0.1% framerates. I did have to enable ModernFix dynamic resources to see these results, so part of this improvement might just be from that.

This is a follow-up to my previous threads where I tested the effectiveness of various weapons on your squad. The specifics of testing are detailed in the post regarding Assault Rifles.
Analyzing and ranking the best Assault Rifles for squadmates (Mass Effect 3) : masseffect (reddit.com)
To summarize, I went through the Noveria Fighter Base mission on Insanity using my squadmates to deal the majority of the damage and measuring how long it took them to complete the mission and kill the Atlas. There are quite a few exceptions to the specifics of testing so I'll mention them here.
Since most Shotguns rely on close range to get the most out of their pellet spread, I was very proactive with micromanaging the squad.
Squadmates were Tali and James. Tali can get a 45% damage boost through a passive skill and an outfit. James can get a 75% boost through passive skills and an outfit.
James had Incendiary Ammo (32% extra damage against armor and health + small damage over time) that was shared with Tali at half of its strength. While the last evolution of Incendiary Ammo that causes 50% of shots to explode is the more effective option, I did not spec into it as it would have given a disproportionally large advantage to the high fire rate Shotguns. Incendiary Ammo also had the benefit of panicking unshielded enemies, preventing them from moving and making them vulnerable to follow-up shots, which synergized well with the multi-pellet nature of most Shotguns.
Every test was done with a level V variant of the weapon and used the Shotgun Smart Choke V (+50% accuracy) and High-Velocity Barrel V (+25% damage, 65% armor mitigation)
Rankings:

1. Geth Plasma Shotgun (mission 23:13, Atlas 2:48) - Only fires uncharged shots that take three hits to kill and the delay between shots is a whopping three full seconds. The plasma bolts can't pierce cover and since the projectiles are quite large, they have a high chance of impacting nearby objects and harmlessly dissipating before they can deal any damage.
   
2. Venom (mission 19:30, Atlas 1:32) - Only fires uncharged shots that take three hits to kill, though fired a little faster than the GPS. Since the explosive radius isn't big and the projectiles are quite small, they often require a direct hit to do damage, which isn't common as the shots are slow.
   
3. Graal Spike Thrower (mission 18:25, Atlas 1:53) - What a surprise, another chargeable Shotgun at the bottom of the list. I have often seen the Graal suggested for your team on account of its low spread but that is precisely the reason it didn't score higher. Near-misses that would deal at least some damage on other shotties instead do nothing. Low mag size and fire rate don't help things either.
   
4. Reegar Carbine (mission 18:23, Atlas 0:55) - Required even more micromanagement than the other Shotguns. Despite its absolutely gargantuan damage potential, it will often go to waste, and not just because it does literally nothing outside of spitting distance. Your idiot teammates will somehow miss most of their shots with an electric current at point-blank range, causing them to spend more time reloading than shooting. Atlas kill time was the fastest in the class but other weapon types can have similar times without forcing your team to stand within French-kissing distance to an enemy that can insta-kill them.
   
5. Disciple (mission 16:49, Atlas 1:56) - Very precise spread that works against the weapon at close range. Damage isn't spectacular but has an increased chance to stagger, which gives it a niche use (though I didn't notice it proc on the shielded Centurions).
   
6. Eviscerator (mission 15:38, Atlas 1:45) - Another tight spread Shotgun that has a tendency to miss. Fires the first two shots at max fire rate, then there's an odd delay for the third.
   
7. Katana (mission 14:11, Atlas 2:15) - Statistically pretty bad, but it's fired more rapidly than most other Shotguns, and the high spread ensures that it hits with at least some pellets. Could be imagining it, but it also seems that your team was much more reactive with the Katana, often opening fire on enemies as soon as they were seen.
   
8. Piranha (mission 13:48, Atlas 1:14) - Has the opposite problem to the high-accuracy Shotguns, spread is too large to do much at longer ranges, like the landing pad. Conversely, it is the best option at close range, even beating out the Reegar. The fights at the control room were the fastest in the test.
   
9. Wraith (mission 13:29, Atlas 1:26) - One of the two Shotguns that your squad can perform one-shots with, though it doesn't happen too often on account of needing most of the tight spread to hit. The two-shot clipazine and the low rate of fire prevent it from being higher.
   
10. Claymore (mission 12:37, Atlas 1:04) - The other Shotgun capable of one-shots but these will occur much more frequently and at surprisingly long distances too. Complete overkill against already injured enemies that cause another unnecessary reload.
    
11. Scimitar (mission 12:24, Atlas 1:51) - Damage is pretty low but the spread is just large enough to still deal solid damage at range without being inconsistent too close. Fired at its max fire rate until the enemy is dead, reaches cover or has to be reloaded. Can be obtained for free near the beginning of the game.
    
12. Crusader (mission 11:05, Atlas 1:22) - Not reliant on range to be effective. Four-to-five shot kill (unless a headshot is scored) but fired and reloaded quite rapidly. Shots can pierce cover, even without mods. What the bottom three entries wish they were. The best option if you don't like micromanaging your squad.
    
13. Raider (mission 10:38, Atlas 1:08) - Most certainly was not expecting this to beat the Crusader. Roughly the same damage as the Claymore, but spread over two shots. Couldn't kill in a single hit but your squad will immediately follow up with another shot when necessary, usually ensuring a kill. Not severely crippled by already injured enemies like the Claymore. Spread is very wide but pellet damage is high enough to remove about three or four bars of health at longer ranges.
    

Conclusion
Because your squadmates seem to be hard-coded to miss with their first shots, it would seem that Shotguns with a higher spread generally have an advantage when it comes to quickly engaging the target. Therefore, the higher accuracy Shotguns, like the Disciple and Eviscerator, might actually be more effective without the Smart Choke. Despite that, an overly large spread will still cause the weapon to be ineffective at longer ranges, so the Choke is still a good choice for something like the Piranha or Scimitar.
Video examples:
Raider: AT-12 Raider Squadmate usage showcase (Mass Effect 3) (youtube.com)
Crusader: N7 Crusader Squadmate usage showcase (Mass Effect 3) (youtube.com)
Scimitar: M-27 Scimitar Squadmate usage showcase (Mass Effect 3) (youtube.com)
Claymore: M-300 Claymore Squadmate usage showcase (Mass Effect 3) (youtube.com)

EDIT: I have created a follow up post that addresses some inaccuracies I posted here through thorough testing. It focuses on Java settings and arguments. I have heavily edited this post to reflect what I have found.
I think that a lot of people here are pretty aware of how to get decent performance out of Minecraft, but there were recently some comments here (that I can't find now) that lead me to some stuff I haven't seen before that gave me some really significant gains. I'm going to explain this stuff at a basic level for anyone that isn't familiar. This information is largely derived from this guide on JVMs and this guide on performance mods, but both of them are slightly out of date so I will summarize. Most of this information will be relevant to Minecraft 1.16.5+ (sorry GT:NH players) (not sorry GT:NH players who can apparently use Java 17?).

Choosing a JRE

When you run a Java program (like Minecraft), you need to choose a Java Runtime Environment (JRE) aka Java Virtual Machine (JVM). A Java Development Kit (JDK) will include this.
For Minecraft 1.16-1.19 you want to use a JVM at version 17. For 1.20+ you want to use version 21. There are annual releases of new Java versions, but 17 and 21 are long term support (LTS). Having a higher version of Java is not necessarily better.
There are several JVMs out there. Adoptium is a great option. It's also possible to get good performance from GraalVM. GraalVM theoretically adds optimizations that might lead to better performance, but actual results vary and depend on your machine. In my experience GraalVM can have better minimum FPS and tick rates (less stuttering), which can lead to significantly better perceived performance. If you are having stuttering issues, I’d try GraalVM.
To "install" Java for Minecraft purposes, you just need to put the files somewhere you want them. Some JVMs will come with an installer that will put the files in a standard place for you.
When you are using a launcher in the Prism, PolyMC, MultiMC family, you will be able to specify the Java version you want to use globally or per instance. You need to make sure you are actually using the JRE that you want.

Java Arguments

Read my linked post for a more in depth explanation of the effects of Java arguments. They can sometimes gain you a bit of performance. If you have Java 21 and/or a higher end PC, you will want to try ZGC. It is possible adding these arguments won't give you a performance gain, so compare against using no arguments if you try them.
G1GC:

-XX:+UnlockExperimentalVMOptions -XX:+UnlockDiagnosticVMOptions -XX:+AlwaysActAsServerClassMachine -XX:+AlwaysPreTouch -XX:+DisableExplicitGC -XX:+UseNUMA -XX:NmethodSweepActivity=1 -XX:ReservedCodeCacheSize=400M -XX:NonNMethodCodeHeapSize=12M -XX:ProfiledCodeHeapSize=194M -XX:NonProfiledCodeHeapSize=194M -XX:-DontCompileHugeMethods -XX:MaxNodeLimit=240000 -XX:NodeLimitFudgeFactor=8000 -XX:+UseVectorCmov -XX:+PerfDisableSharedMem -XX:+UseFastUnorderedTimeStamps -XX:+UseCriticalJavaThreadPriority -XX:ThreadPriorityPolicy=1 -XX:AllocatePrefetchStyle=3 -XX:+UseG1GC -XX:MaxGCPauseMillis=37 -XX:+PerfDisableSharedMem -XX:G1HeapRegionSize=16M -XX:G1NewSizePercent=23 -XX:G1ReservePercent=20 -XX:SurvivorRatio=32 -XX:G1MixedGCCountTarget=3 -XX:G1HeapWastePercent=20 -XX:InitiatingHeapOccupancyPercent=10 -XX:G1RSetUpdatingPauseTimePercent=0 -XX:MaxTenuringThreshold=1 -XX:G1SATBBufferEnqueueingThresholdPercent=30 -XX:G1ConcMarkStepDurationMillis=5.0 -XX:G1ConcRSHotCardLimit=16 -XX:G1ConcRefinementServiceIntervalMillis=150 -XX:GCTimeRatio=99 

ZGC:

-XX:+UnlockExperimentalVMOptions -XX:+UseZGC -XX:+DisableExplicitGC -XX:+AlwaysPreTouch -XX:+PerfDisableSharedMem -XX:-ZUncommit -XX:+ParallelRefProcEnabled 

Shenandoah:

-XX:+UnlockExperimentalVMOptions -XX:+UnlockDiagnosticVMOptions -XX:+AlwaysActAsServerClassMachine -XX:+AlwaysPreTouch -XX:+DisableExplicitGC -XX:+UseNUMA -XX:NmethodSweepActivity=1 -XX:ReservedCodeCacheSize=400M -XX:NonNMethodCodeHeapSize=12M -XX:ProfiledCodeHeapSize=194M -XX:NonProfiledCodeHeapSize=194M -XX:-DontCompileHugeMethods -XX:MaxNodeLimit=240000 -XX:NodeLimitFudgeFactor=8000 -XX:+UseVectorCmov -XX:+PerfDisableSharedMem -XX:+UseFastUnorderedTimeStamps -XX:+UseCriticalJavaThreadPriority -XX:ThreadPriorityPolicy=1 -XX:AllocatePrefetchStyle=3 -XX:+UseShenandoahGC -XX:ShenandoahGCMode=iu -XX:ShenandoahGuaranteedGCInterval=1000000 -XX:AllocatePrefetchStyle=1 

Your launcher should have a Java arguments box in the same place where you can choose your JRE.

Memory Allocation

It is best to set you minimum and maximum RAM setting to the same amount. The idea is that if you give your instance too much RAM, it might have infrequent, long and noticeable pauses for garbage collection (memory management). If you don't allocate enough RAM, you will have frequent pauses/stutters. You can argue that you don't need to set your minimum and maximum allocation to the same amount, which probably won't hurt your performance and might leave more RAM available to your system if you need it for something else, but to me it makes sense to just dictate how much RAM your instance uses.
When you look at the F3 menu, you can see how much of the allocated RAM is being used, and you can get a feel for if it needs more or less. There are mods like Spark that can give you a more detailed look at your RAM use/garbage collection stats. The RAM allocation settings are in the same place in your launcher as the other Java settings.
GraalVM can potentially perform better with lower amounts of RAM.

Performance Mods

Performance mods are going to get you large gains. To see more performance mods for different versions, use the link at the top of this post.
Many performance mods are eternal ports/forks of the same thing. An example is Canary is a forge port of Lithium, but so is Radium which claims to be better. Embeddium is a fork of Rubidium which is a port of Sodium. You only want to have one version of a mod, and you can try to check that you have the best one for your version.
Some performance mods have big tradeoffs, like incompatibilities or changed behavior, or even big performance tradeoffs.
You do not want to use every performance mod you can find. Try to only add ones that you know give a significant performance improvement. Here is a list of performance mods I would use for forge 1.19.2:

• Alternate Current
• Chunky (chunk pre-generator)
• Clumps
• Dynamic View Distance*
• Embeddium
• Entity Collision FPS Fix
• Entity Culling
• Farsight*
• Fast Suite
• Fast Workbench
• Fast Furnace
• Fastload-Reforged
• Ferrite Core
• ImmediatelyFast
• LazyDFU
• Let Me Despawn
• Memory Leak Fix
• ModernFix
• Pluto
• Radium
• Reforgium
• Saturn
• Smooth Boot
• Starlight

*Technically don't improve performance but make it look like performance is better
If you are playing a modpack and you want more performance, you can try adding some of your own performance mods, but be prepared for incompatibilities.

Conclusion

I hope this is helpful to someone. I feel like it could be since a lot of the sources I've seen are slightly outdated. If you have a big performance tip please leave it in a comment. I have seen these optimizations make a big difference for several people.
EDIT: I have removed the rudimentary benchmarks from this post since the way I didn't separate my variables lead to misleading results.

Graal Native Image is a technology to compile Java code ahead-of-time to a lightweight native binary executable, which has the advantages of smaller resources, starts in milliseconds, no warmup needed, and reduce attack surface. The serialization in graalvm is tricky and slow since it doesn't support reflection, jit, and bytecode manipulation. Many performance optimization can't be applied in graalvm.
In Fury 0.4.0 version, Fury can run on GraalVM native image efficiently and is super easy-to-use. Neither reflection nor meta config are needed. Fury generates all code for Fury JIT framework and MethodHandle/LambdaMetafactory at graalvm native image build time. Then use those generated code for serialization at runtime without any extra cost, the performance is great.
Compared to native JDK serialization, Fury can be 46x faster than JDK, and less than half of the serialized size.
See https://github.com/alipay/fury/blob/main/docs/guide/graalvm_guide.md for example and benchmarks.
This is a big step for jvm serialization, please give it a try and share us with your feedbacks.

For the November UKSTUG meeting, Pierre Misse-Chanabier will talk to us about Polyphemus for the Pharo Virtual Machine ( https://github.com/hogoww/Polyphemus ).The presentation will focus on how to create Tooling on the Pharo Virtual Machine. (This does not require Virtual machine level knowledge)
We will start by taking a look at a few existing tools. We will create one or two small tools, and see how they differ from tooling on the image side.Pierre Misse Chanabier is a recently graduated PhD with a focused interest on Virtual Machines, Code Generation, and Meta Programming. He worked on and contributed to many different levels and parts of the Pharo
ecosystem.
He is now working on how to leverage images for more than what they do now. He's currently working at Microdoc on the Graal VM ( https://www.microdoc.com/ ).
Born in south of France, he currently lives in Lille.
This will be an online meeting from home.
If you'd like to join us, please sign up in advance on the meeting's Meetup page ( https://www.meetup.com/ukstug/events/297644731 ) to receive the meeting details. Don’t forget to bring your laptop and drinks!

So I had a situation where I got hacked last week, my account was hacked by someone telling me to email a certain email and type "Happy holidays graal" and I would get a reward (20 k gralats and 5 EC), unfortunately, I fell for it and at that moment that I sent that email my account got disconnected (I never shared my ID or passwords), the person started talking to other people using my account and eventually got banned, the next day I got it back but with a ban of 70 years, I've tried contacting everyone for weeks and got no reply I feel that they are not even reading into the situation and just replying with the first thing that they read. I have sent proof, I have sent emails, talked to admins, toonslab and no one has been able to help me. Please lmk if anyone can help, it's getting annoying how little they care about their players

I have the following code (reduced to a minimum working example):
``` clojure (ns timer.core (:gen-class))
(defn handle2 [x] (if (string? x) (IntegeparseInt x) x))
(defn -main ([max-time] (println (format "Going to sleep %d seconds" (handle2 max-time))) (let [sleep-time (* (handle2 max-time) 1000)] (Thread/sleep sleep-time) (println (format "Waken up")))) ([] (-main 10))) ```
that works in the cider REPl on emacs and also works with > lein run on a windows terminal (x64 Native Command Prompt for VS 2022) and also can be compiled into an uberjar with leiningen and calling the java -jar command works. All the previous work with or without the max-time argument, as it is expected.
But when I build a executable from the uberjar with the GraalVM using the command ```

native-image --report-unsupported-elements-at-runtime --initialize-at-build-time -jar .\target\timer-0.1.0-SNAPSHOT-standalone.jar -H:Name=timer-cli `` although it compiles atimer-cli.exe` executable binary, this fails when is run with this error:

exp-timer-cli.exe Going to sleep 10 seconds Exception in thread "main" java.lang.IllegalArgumentException: No matching method sleep found taking 1 args at clojure.lang.Reflector.invokeMatchingMethod(Reflector.java:127) at clojure.lang.Reflector.invokeStaticMethod(Reflector.java:332) at timer.core$_main.invokeStatic(core.clj:72) at timer.core$_main.invoke(core.clj:68) at timer.core$_main.invokeStatic(core.clj:76) at timer.core$_main.invoke(core.clj:68) at clojure.lang.AFn.applyToHelper(AFn.java:152) at clojure.lang.AFn.applyTo(AFn.java:144) at timer.core.main(Unknown Source)
with or without parameter. But if I substitute (handle2 max-time) by an actual number (let's say 2), the program works, but of course with the hardcoded variable as sleep time, and prints the parameter value on the message string.
Does any one have experience with the GraalVM and knows why this happens? And how to solve this would be greatly appreciated.
Using: - Leiningen 2.10.0 on Java 19.0.2 OpenJDK 64-Bit Server VM - GraalVM 22.3.1