An Evaluation of Code Coverage Adequacy in Automatic Testing using Control Flow Graph Visualization

Rahmani, Ani; Min, Joe Lian; Maspupah, Asri

doi:10.1109/iscaie47305.2020.9108838

Cited by 4 publications

(1 citation statement)

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“…Lawrance et al [26] highlight lines in the code under test to indicate the existing quality of a test suite and investigate whether this leads developers to create more effective tests. With a similar goal, Rahmani et al [50] create a control flow graph showing the current branch coverage. Among our participants, we observed a similar, intuitive strive to write additional test cases for lines that were not marked as covered.…”

Section: Related Work: Test Visualizationsmentioning

confidence: 99%

How Does This New Developer Test Fit In? A Visualization to Understand Amplified Test Cases

Brandt

Zaidman

2022

2022 Working Conference on Software Visualization (VISSOFT)

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Developer testing, the practice of software engineers programmatically checking that their own components behave as they expect, has become the norm in today's software projects. With the constantly growing size and complexity of software projects and with the rise of automated test generation tools, understanding a test case is becoming more and more important compared to writing test cases from scratch.This holds especially in the area of developer-centric test amplification, where a tool automatically generates new test cases to improve a developer-maintained test suite. To investigate how visualization can help developers understand and judge test cases, we present the TESTIMPACTGRAPH, a visualization of the call tree and coverage impact of a JUnit test case proposed for amplification. It empowers the developer to drill down into the behavior of a test case, as well as providing them a clear view on how the proposed test case contributes to the coverage of the overall test suite. In a think-aloud study we investigate which information developers seek from the TESTIMPACTGRAPH, how its features can support them in accessing this information, and observations regarding the coverage impact of test cases. We infer ten actionable recommendations on how developer tests can be visualized to help developers understand their behavior and impact.

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Section: Related Work: Test Visualizationsmentioning

confidence: 99%