Variability testing in the wild: the Drupal case study

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• 作者：Ana B. Sánchez ; Sergio Segura ; José A. Parejo…
• 关键词：Test case prioritization ; Test case selection ; Variability ; intensive systems ; Automated testing ; Non ; functional properties ; Variability testing
• 刊名：Software & Systems Modeling
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：16
• 期：1
• 页码：173-194
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Software Engineering/Programming and Operating Systems; Programming Techniques; Software Engineering; Programming Languages, Compilers, Interpreters; Information Systems Applications (incl.Internet);
• 出版者：Springer Berlin Heidelberg
• ISSN：1619-1374
• 卷排序：16

文摘

Variability testing techniques search for effective and manageable test suites that lead to the rapid detection of faults in systems with high variability. Evaluating the effectiveness of these techniques in realistic settings is a must, but challenging due to the lack of variability-intensive systems with available code, automated tests and fault reports. In this article, we propose using the Drupal framework as a case study to evaluate variability testing techniques. First, we represent the framework variability using a feature model. Then, we report on extensive non-functional data extracted from the Drupal Git repository and the Drupal issue tracking system. Among other results, we identified 3392 faults in single features and 160 faults triggered by the interaction of up to four features in Drupal v7.23. We also found positive correlations relating the number of bugs in Drupal features to their size, cyclomatic complexity, number of changes and fault history. To show the feasibility of our work, we evaluated the effectiveness of non-functional data for test case prioritization in Drupal. Results show that non-functional attributes are effective at accelerating the detection of faults, outperforming related prioritization criteria as test case similarity.