Publication | Open Access
DeepTC-enhancer
32
Citations
42
References
2020
Year
Unknown Venue
EngineeringTest Data GenerationSoftware EngineeringSoftware AnalysisCorpus LinguisticsNatural Language ProcessingComputational LinguisticsTest AutomationLanguage StudiesNatural Language SummariesTesting TechniqueTest ReadabilitySoftware DesignProgram AnalysisSoftware TestingTest Case DesignTest EvolutionTest CasesLinguistics
Automated test case generation tools have been successfully proposed to reduce the amount of human and infrastructure resources required to write and run test cases. However, recent studies demonstrate that the readability of generated tests is very limited due to (i) uninformative identifiers and (ii) lack of proper documentation. Prior studies proposed techniques to improve test readability by either generating natural language summaries or meaningful methods names. While these approaches are shown to improve test readability, they are also affected by two limitations: (1) generated summaries are often perceived as too verbose and redundant by developers, and (2) readable tests require both proper method names but also meaningful identifiers (within-method readability).
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