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Issue No. 11 - Nov. (2014 vol. 40)
ISSN: 0098-5589
pp: 1100-1125
Dimitrios Athanasiou , Software Improvement Group, Amstelplein 1, 1096HA Amsterdam, The Netherlands
Ariadi Nugroho , Software Improvement Group, Amstelplein 1, 1096HA Amsterdam, The Netherlands
Joost Visser , Software Improvement Group, Amstelplein 1, 1096HA Amsterdam, The Netherlands
Andy Zaidman , Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD Delft, The Netherlands
Automated testing is a basic principle of agile development. Its benefits include early defect detection, defect causelocalization and removal of fear to apply changes to the code. Therefore, maintaining high quality test code is essential. This study introduces a model that assesses test code quality by combining source code metrics that reflect three main aspects of test codequality: completeness, effectiveness and maintainability. The model is inspired by the Software Quality Model of the SoftwareImprovement Group which aggregates source code metrics into quality ratings based on benchmarking. To validate the model we assess the relation between test code quality, as measured by the model, and issue handling performance. An experiment isconducted in which the test code quality model is applied to $18$ open source systems. The test quality ratings are tested for correlation with issue handling indicators, which are obtained by mining issue repositories. In particular, we study the (1) defect resolution speed, (2) throughput and (3) productivity issue handling metrics. The results reveal a significant positive correlation between test code quality and two out of the three issue handling metrics (throughput and productivity), indicating that good test code quality positively influences issue handling performance.
Measurement, Software, Productivity, Throughput, Benchmark testing, Correlation,measurement, Testing, defects, bugs, metrics
Dimitrios Athanasiou, Ariadi Nugroho, Joost Visser, Andy Zaidman, "Test Code Quality and Its Relation to Issue Handling Performance", IEEE Transactions on Software Engineering, vol. 40, no. , pp. 1100-1125, Nov. 2014, doi:10.1109/TSE.2014.2342227
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