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TLA+ AutoRepair (with GPT-4) to fix formal specs and understand them

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TLA+ AutoRepair (with GPT-4) to fix formal specs and understand them

TLA+ is a language for formal specification. It can be used to formally verify algorithms and mathematical theorems. Companies like AWS use it for verifying mission-critical parts of systems like S3. The challenge is that TLA+ and formal specifications have a steep learning curve. This tool can aid in overcoming this obstacle at the outset. TLA+ AutoRepair is used to repair/self-heal formal specifications with GPT-4 in a loop, with or without human intervention. Given a TLA+ specification (.tla file) and a model to check (.cfg), the application will go through each error, send it to GPT-4 (or specified model), and fix all errors. Finally, it will document the code to make it more readable. Example Command: python3 autorepair.py Test_Specs/Counter.tla --model=gpt-4

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, code · Missing: mac, agents, macos
77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
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Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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