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Doc2OracLL: Investigating the Impact of Documentation on LLM-based Test Oracle Generation
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Code documentation is a critical aspect of software development, serving as a bridge between human understanding and machine-readable code. Beyond assisting developers in understanding and maintaining code, documentation also plays a critical role in automating various software engineering tasks, such as test oracle generation (TOG). In Java, Javadoc comments provide structured, natural language documentation embedded directly in the source code, typically detailing functionality, usage, parameters, return values, and exceptions. While prior research has utilized Javadoc comments in test oracle generation (TOG), there has not been a thorough investigation into their impact when combined with other contextual information, nor into identifying the most relevant components for generating correct and strong test oracles, or understanding their role in detecting real bugs. In this study, we dive deep into investigating the impact of Javadoc comments on TOG.
Forward citations
Cited by 2 Pith papers
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LogicHunter combines specification-driven test generation with a ReAct-based agentic oracle to discover 40 previously unknown bugs in LangChain, LlamaIndex, and CrewAI, achieving 91.17% oracle precision.
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Beyond Coverage and Kill Scores: Empirically Measuring Test Suite Behavioural Gaps
An empirical study extracts 20,729 expected behaviors from ten Java libraries and finds 17.5% remain untested, independent of line coverage and mutation scores.
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