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How disabled tests manifest in test maintainability challenges?

Dong Jae Kim, Bo Yang, Jinqiu Yang, Tse-Hsun (Peter) Chen

2021Year
9Citations
2Top-tier citations

Abstract

Software testing is an essential software quality assurance practice. Testing helps expose faults earlier, allowing developers to repair the code and reduce future maintenance costs. However, repairing (i.e., making failing tests pass) may not always be done immediately. Bugs may require multiple rounds of repairs and even remain unfixed due to the difficulty of bug-fixing tasks. To help test maintenance, along with code comments, the majority of testing frameworks (e.g., JUnit and TestNG) have also introduced annotations such as @Ignore to disable failing tests temporarily. Although disabling tests may help alleviate maintenance difficulties, they may also introduce technical debt. With the faster release of applications in modern software development, disabling tests may become the salvation for many developers to meet project deliverables. In the end, disabled tests may become outdated and a source of technical debt, harming long-term maintenance. Despite its harmful implications, there is little empirical research evidence on the prevalence, evolution, and maintenance of disabling tests in practice. To fill this gap, we perform the first empirical study on test disabling practice. We develop a tool to mine 122K commits and detect 3,111 changes that disable tests from 15 open-source Java systems. Our main findings are: (1) Test disabling changes are 19% more common than regular test refactorings, such as renames and type changes.

(2) Our life-cycle analysis shows that 41% of disabled tests are never brought back to evaluate software quality, and most disabled tests stay disabled for several years. (3) We unveil the motivations behind test disabling practice and the associated technical debt by manually studying evolutions of 349 unique disabled tests, achieving a 95% confidence level and a 5% confidence interval. Finally, we present some actionable implications for researchers and developers.

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