Choreographic programming simplifies reasoning about distributed systems by using a single global program called a choreography.
Large language models show promise in decompiling binary code, leading to the release of the first open-source LLMs for decompilation.
AdaCCD is a novel method for cross-lingual code clone detection that leverages adaptive semantic contrasts discovery.
ContrastRepair significantly improves program repair efficiency by providing informative feedback to Large Language Models through contrastive test cases.
CoPrompt assists programmers in collaborative NL programming by providing mechanisms for sharing, referring, requesting, and linking prompts.
Semi-Instruct bridges the gap between Natural-Instruct and Self-Instruct to improve code Large Language Models by converting diverse but improper codes into proper instruction-code pairs.
Libfork enables fully-portable continuation stealing with stackless coroutines, achieving optimal time/memory scaling.
Classes with “-Er/-Or” and “-Utils” suffixes in Java exhibit higher complexity, impacting maintainability.
Large language models blur the lines between machine- and human-authored code, but DetectCodeGPT offers a novel method to detect machine-generated code by capturing distinct stylized patterns.
ProCQA is a large-scale dataset extracted from StackOverflow, offering mixed-modal QA pairs for programming question answering, leading to significant performance improvements in code retrieval benchmarks.