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Further Optimizing my Java SwissTable: Profile Pollution and SWAR Probing
https://www.reddit.com/r/programming/comments/1pp0wg2/further_optimizing_my_java_swisstable_profile/

<!-- SC_OFF -->Hey everyone. Follow-up to my last post where I built a SwissTable-ish hash map on the JVM: https://www.reddit.com/r/programming/comments/1plbpzg/building_a_fast_memoryefficient_hash_table_in/ This time I went back with a profiler and optimized the actual hot path (findIndex). A huge chunk of time was going to Objects.equals() because of profile pollution / missed devirtualization. After fixing that, the next bottleneck was ARM/NEON “movemask” pain (VectorMask.toLong()), so I tried SWAR… and it ended up faster (even on x86, which I did not expect). <!-- SC_ON --> submitted by /u/Charming-Top-8583 (https://www.reddit.com/user/Charming-Top-8583)
[link] (https://bluuewhale.github.io/posts/further-optimizing-my-java-swiss-table/) [comments] (https://www.reddit.com/r/programming/comments/1pp0wg2/further_optimizing_my_java_swisstable_profile/)
Greptile publishes their State of AI coding 2025 report
https://www.reddit.com/r/programming/comments/1ppexvk/greptile_publishes_their_state_of_ai_coding_2025/

<!-- SC_OFF -->Greptile, a company that does AI Code reviews for 1 billion lines of code from 2000 companies a month, has published some metrics on the code they've processed.: * Lines of code per developer grew from 4,450 to 7,839 in 2025. * Median PR size increased 33% from March to November 2025, rising from 57 to 76 lines changed per PR. * Medium teams (6-15 devs) increased output from 7,005 to 13,227 lines per developer. ^Median lines changed per file grew from 18 to 22 as PRs become denser. <!-- SC_ON --> submitted by /u/humanquester (https://www.reddit.com/user/humanquester)
[link] (https://www.greptile.com/state-of-ai-coding-2025) [comments] (https://www.reddit.com/r/programming/comments/1ppexvk/greptile_publishes_their_state_of_ai_coding_2025/)
What writing a tiny bytecode VM taught me about debugging long-running programs
https://www.reddit.com/r/programming/comments/1pplwnm/what_writing_a_tiny_bytecode_vm_taught_me_about/

<!-- SC_OFF -->While working on a small bytecode VM for learning purposes, I ran into an issue that surprised me: bugs that were invisible in short programs became obvious only once the runtime stayed “alive” for a while (loops, timers, simple games). One example was a Pong-like loop that ran continuously. It exposed: subtle stack growth due to mismatched push/pop paths error handling paths that didn’t unwind state correctly how logging per instruction was far more useful than stepping through source code What helped most wasn’t adding more language features, but: dumping VM state (stack, frames, instruction pointer) at well-defined boundaries diffing dumps between iterations to spot drift treating the VM like a long-running system rather than a noscript runner The takeaway for me was that continuous programs are a better stress test for runtimes than one-shot noscripts, even when the program itself is trivial. I’m curious: What small programs do you use to shake out runtime or interpreter bugs? Have you found VM-level tooling more useful than source-level debugging for this kind of work? (Implementation details intentionally omitted — this is about the debugging approach rather than a specific project.) <!-- SC_ON --> submitted by /u/Imaginary-Pound-1729 (https://www.reddit.com/user/Imaginary-Pound-1729)
[link] (https://vexonlang.blogspot.com/2025/12/vexon-what-building-small-bytecode.html) [comments] (https://www.reddit.com/r/programming/comments/1pplwnm/what_writing_a_tiny_bytecode_vm_taught_me_about/)
Probability stacking in distributed systems failures
https://www.reddit.com/r/programming/comments/1ppuvve/probability_stacking_in_distributed_systems/

<!-- SC_OFF -->An article about resource jitter that reminds that if 50 nodes had a 1% degradation rate and were all needed for a call to succeed, then each call has a 40% chance of being degraded. <!-- SC_ON --> submitted by /u/that_is_just_wrong (https://www.reddit.com/user/that_is_just_wrong)
[link] (https://medium.com/@vedantcj/beyond-the-average-engineering-for-resource-jitter-in-distributed-systems-ffec6add2e08) [comments] (https://www.reddit.com/r/programming/comments/1ppuvve/probability_stacking_in_distributed_systems/)
The impact of technical blogging
https://www.reddit.com/r/programming/comments/1ppykuk/the_impact_of_technical_blogging/

<!-- SC_OFF -->How Charity Majors, antirez, Thorsten Ball, Eric Lippert, Sam Rose... responded to the question: “What has been the most surprising impact of writing engineering blogs?" <!-- SC_ON --> submitted by /u/swdevtest (https://www.reddit.com/user/swdevtest)
[link] (https://writethatblog.substack.com/p/the-impact-of-technical-blogging) [comments] (https://www.reddit.com/r/programming/comments/1ppykuk/the_impact_of_technical_blogging/)