Unleashing the power of compiler intermediate representation to enhance neural program embeddings
Zongjie Li, Pingchuan Ma, Huaijin Wang, Shuai Wang, Qiyi Tang, Sen Nie, Shi Wu
Abstract
Neural program embeddings have demonstrated considerable promise in a range of program analysis tasks, including clone identification, program repair, code completion, and program synthesis. However, most existing methods generate neural program embeddings directly from the program source codes, by learning from features such as tokens, abstract syntax trees, and control flow graphs.
Topics & Concepts
Computer scienceCompilerProgramming languageControl flowAbstract syntax treeSyntaxArtificial neural networkProgram analysisProgram synthesisCode (set theory)Representation (politics)Source codeAbstract syntaxRange (aeronautics)ParsingArtificial intelligenceSet (abstract data type)Materials sciencePoliticsComposite materialLawPolitical scienceSoftware Engineering ResearchParallel Computing and Optimization TechniquesSoftware Testing and Debugging Techniques