Using Test Data to Improve Software Quality: Problems and Suggestions
Abstract
a result, testing may appear complete while important defects remain hidden. Based on recent studies on test suite quality, search-based test
generation, software test data management, synthetic test data, and requirement-based testing, this paper discusses how test data affects software quality. It analyzes problems in coverage, realism, traceability, maintenance, privacy protection, and defect feedback. It then proposes
suggestions including requirement- and risk-driven data design, boundary and negative data strengthening, test data repositories, privacyaware synthetic data, and defect-linked updates. The main argument is that test data should be treated as a managed quality asset rather than a
temporary input.
Keywords
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DOI: http://dx.doi.org/10.70711/aitr.v4i3.9928
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