Reddit Programming
211 subscribers
1.22K photos
124K links
I will send you newest post from subreddit /r/programming
Download Telegram
Did Flo pessin and Lois Haibt invent the fortran compiler?
https://www.reddit.com/r/programming/comments/1ofuwmm/did_flo_pessin_and_lois_haibt_invent_the_fortran/

<!-- SC_OFF -->John Backus is typically credited with developing fortran, but he was merely the leader of a group, and the people under him did the real work. flo pessin was the first person ever to figure to ever figure out how to translate algebraic formulas into machine code, along with other groundbreaking new compiling techniques which shape literally all of computing today, according to this official source: https://eprints.cs.vt.edu/archive/ 00000875/01/CS82010-R.pdf (It's on page 23 and 24, Beemer and pessin) and following people people merely rediscovered it at a later time. (They also named fortran, again link for source same pages) Lois Haibt, on top of inventing syntactic analysis for algebraic expressions: https://en.wikipedia.org/wiki/ Lois_Haibt, also wrote all of section 4 of the project themselves, and also wrote all the critical parts of the compiler's loop control and branching logic. Her work helped the compiler optimize execution paths, which was revolutionary for the time. All in all, I'd say this all deserves at least 50% of the credit for the creation of the modern day fortran compiler, which is interesting because they were on a team with like 11 other people who all didn’t basically nothing except work they were like workers <!-- SC_ON --> submitted by /u/Psychological_Bug_79 (https://www.reddit.com/user/Psychological_Bug_79)
[link] (https://eprints.cs.vt.edu/archive/00000875/01/CS82010-R.pdf) [comments] (https://www.reddit.com/r/programming/comments/1ofuwmm/did_flo_pessin_and_lois_haibt_invent_the_fortran/)
[R] Bauform: Production-Grade Code Generation with Cryptographic Verification (100% success rate)
https://www.reddit.com/r/programming/comments/1ofwhd5/r_bauform_productiongrade_code_generation_with/

<!-- SC_OFF -->We present Bauform, a production-grade codegen system generating, deploying, and validating working tools with cryptographic signatures. Four for four tools public, instant deploy, no debugging needed. Key: - Multi-model orchestration - Automated validation (functional, security, performance, stability) - Ed25519 signature on all results - API: https://bauform-beta.fly.dev (https://bauform-beta.fly.dev/) Full details: https://bauformsoftware.com (https://bauformsoftware.com/) Verification scripts: https://github.com/tekodu/bauform-evals <!-- SC_ON --> submitted by /u/deviolenza (https://www.reddit.com/user/deviolenza)
[link] (https://doi.org/10.5281/zenodo.17438526) [comments] (https://www.reddit.com/r/programming/comments/1ofwhd5/r_bauform_productiongrade_code_generation_with/)
[Tool] I created a simple technique to give AI coding assistants persistent memory across sessions
https://www.reddit.com/r/programming/comments/1ogd5jh/tool_i_created_a_simple_technique_to_give_ai/

<!-- SC_OFF -->``` TL;DR: Use a PROJECT_JOURNAL.md file to maintain context with AI assistants. Free template available. The Problem Working with AI assistants (Claude, ChatGPT, Copilot) is great, but they forget everything between sessions. You constantly re-explain your project, decisions, and context. The Solution A Project Journal - a markdown file that acts as your AI's memory bank. Structure: - Team & project overview - Tech stack decisions & rationale - Completed features - Session logs - Current status & next steps Usage: Start session: "Read PROJECT_JOURNAL.md" End session: "Update PROJECT_JOURNAL.md with progress" Real-world results: Used this building Vibe CMS (social platform, PHP/flat-file). AI now remembers: - All tech decisions & why - Past session work - Project philosophy - What's next Saves ~15 min/session. Better decisions. Natural documentation. Template: https://github.com/CursorWP/ai-project-journal CC0 license (public domain). Works with any AI. Thoughts? Improvements? I'd love feedback! ``` <!-- SC_ON --> submitted by /u/Funny-Exit5250 (https://www.reddit.com/user/Funny-Exit5250)
[link] (https://github.com/CursorWP/ai-project-journal) [comments] (https://www.reddit.com/r/programming/comments/1ogd5jh/tool_i_created_a_simple_technique_to_give_ai/)
How I cleared AWS Solution Architect Associate on first attempt (800+ score) — strategy and efficient prep plan
https://www.reddit.com/r/programming/comments/1ogegby/how_i_cleared_aws_solution_architect_associate_on/

<!-- SC_OFF -->Hey everyone, I cleared the AWS Solution Architect Associate (SAA-C03) exam on my first attempt with 800+ marks, and I made a short video sharing exactly how I prepared — the strategy, mindset, and resources that helped me do it in limited time. Instead of just listing courses, I focused on: • The optimal learning order (services to study first that give maximum exam coverage) • How to connect theory with hands-on practice efficiently • The mock tests & whitepapers that actually matter • Common traps people fall into and how to avoid them I made the video to help developers who want to transition into cloud architecture roles or strengthen backend + infrastructure knowledge for interviews. https://youtu.be/iFAur7vQvZw If you’ve taken the exam or are preparing, I’d love to hear your experience or resources that worked for you too! <!-- SC_ON --> submitted by /u/abhishekkumar333 (https://www.reddit.com/user/abhishekkumar333)
[link] (https://youtu.be/iFAur7vQvZw) [comments] (https://www.reddit.com/r/programming/comments/1ogegby/how_i_cleared_aws_solution_architect_associate_on/)
Creating a series, Backend from ground up for all backend enthusiasts
https://www.reddit.com/r/programming/comments/1ogen6j/creating_a_series_backend_from_ground_up_for_all/

<!-- SC_OFF -->Anyone planning to switch from frontend to backend, or newbies looking to understand backend from first principles. Do follow me on medium. You will get ample amount of insights as there is always something more to learn. And here is the link to Part 1 - https://medium.com/@pchippigiri/understanding-http-for-backend-engineers-part-1-54d16de6bad1 <!-- SC_ON --> submitted by /u/Comfortable-Fan-580 (https://www.reddit.com/user/Comfortable-Fan-580)
[link] (https://medium.com/@pchippigiri/all-about-http-part-2-4777ea02e722) [comments] (https://www.reddit.com/r/programming/comments/1ogen6j/creating_a_series_backend_from_ground_up_for_all/)
Java project
https://www.reddit.com/r/programming/comments/1ogevb7/java_project/

<!-- SC_OFF -->Hey everyone I recently created a simple open-source project called “Simple Java Web Engine” I’m looking for support whether that’s / stars, forks, feedback , ideas for improvement, or contributors who want to help enhance it 🙏 <!-- SC_ON --> submitted by /u/0xh7 (https://www.reddit.com/user/0xh7)
[link] (https://github.com/0xh7/Simple-Java-Web-Engine) [comments] (https://www.reddit.com/r/programming/comments/1ogevb7/java_project/)
anyone learning MLSys?
https://www.reddit.com/r/programming/comments/1ogfwi5/anyone_learning_mlsys/

<!-- SC_OFF -->I do such things on my free time. cuda, compilers or whatever GPU go brrrs…. I’m making a discord channel for casual chatting room for mlsys engineers. do you want join? if you’re interested! dm me <!-- SC_ON --> submitted by /u/ita9naiwa (https://www.reddit.com/user/ita9naiwa)
[link] (https://ita9naiwa.github.io/) [comments] (https://www.reddit.com/r/programming/comments/1ogfwi5/anyone_learning_mlsys/)
5 Hard-Won Lessons from a Year of Rebuilding a Search System
https://www.reddit.com/r/programming/comments/1ogklk9/5_hardwon_lessons_from_a_year_of_rebuilding_a/

<!-- SC_OFF -->Hey everyone, I wanted to start a discussion on an experience I had after a year of rebuilding a core search system. As an experienced architect, I was struck by how this specific domain (user-facing search) forces a different application of our fundamental principles. It's not that "velocity," "data-first," or "business-value" are new, but their prioritization and implementation in this context are highly non-obvious. These are the 5 key "refinements" we focused on that ultimately led to our success: It's a Data & Product Problem First. We had to shift focus from pure algorithm/infrastructure elegance to the speed and quality of our user data feedback loops. This was the #1 unlock. Velocity Unlocks Correctness. We prioritized a scrappy, end-to-end working pipeline to get A/B data fast. This validation loop allowed us to find correctness, rather than just guessing at it in isolation. Business Impact is the North Star. We moved away from treating offline metrics (like nDCG) as the goal. They became debugging tools, while the real north star became a core business KPI (engagement, retention, etc.). Blurring Lines Unlocks Synergy. We had to break down the rigid silos between Data Science, Backend, and Platform. Progress ignited when data scientists could run A/B tests and backend engineers could explore user data directly. A Product Mindset is the Compass. We re-focused from "building the most elegant system" to "building the most effective system for the user." This clarity made all the difficult technical trade-offs obvious. Has anyone else found that applying core principles in domains like ML/search forces a similar re-prioritization? Would love to hear your experiences. <!-- SC_ON --> submitted by /u/Journerist (https://www.reddit.com/user/Journerist)
[link] (https://www.sebastiansigl.com/blog/rebuilding-search-lessons-learned) [comments] (https://www.reddit.com/r/programming/comments/1ogklk9/5_hardwon_lessons_from_a_year_of_rebuilding_a/)