Collaborative bug finding for Android apps

Tan, Shin Hwei; Li, Ziqiang

doi:10.1145/3377811.3380349

Cited by 21 publications

(41 citation statements)

References 63 publications

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“…In this section, we discuss prior work that applied clustering techniques [4,6,20,41,48] and natural language processing (NLP) [20,22,23,24,38,42,43] to software testing.…”

Section: Related Workmentioning

confidence: 99%

Identifying Similar Test Cases That Are Specified in Natural Language

Viggiato¹,

Paas²,

Buzon³

et al. 2021

Preprint

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Software testing is still a manual process in many industries, despite the recent improvements in automated testing techniques. As a result, test cases are often specified in natural language by different employees and many redundant test cases might exist in the test suite. This increases the (already high) cost of test execution. Manually identifying similar test cases is a time-consuming and error-prone task. Therefore, in this paper, we propose an unsupervised approach to identify similar test cases. Our approach uses a combination of text embedding, text similarity and clustering techniques to identify similar test cases. We evaluate five different text embedding techniques, two text similarity metrics, and two clustering techniques to cluster similar test steps and four techniques to identify similar test cases from the test step clusters. Through an evaluation in an industrial setting, we showed that our approach achieves a high performance to cluster test steps (an F-score of 87.39%) and identify similar test cases (an F-score of 83.47%). Furthermore, a validation with developers indicates several different practical usages of our approach (such as identifying redundant and legacy test cases), which help to reduce the testing manual effort and time.

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“…In this section, we discuss prior work that applied clustering techniques [4,6,20,41,48] and natural language processing (NLP) [20,22,23,24,38,42,43] to software testing.…”

Section: Related Workmentioning

confidence: 99%

Identifying Similar Test Cases That Are Specified in Natural Language

Viggiato¹,

Paas²,

Buzon³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Studies on GitHub. Several studies have shown the effectiveness of using GitHub Classroom for teaching [30], [31], [32], [33]. Different from all these studies, GitHub-OSS Fixit focuses on teaching students how to contribute to oSS projects by creating good quality pull requests.…”

Section: Project Requirementsmentioning

confidence: 99%

GitHub-OSS Fixit: Fixing Bugs at Scale in a Software Engineering Course

Tan

et al. 2021

2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)

Self Cite

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Many studies have shown the benefits of introducing open-source projects into teaching Software Engineering (SE) courses. However, there are several limitations of existing studies that limit the wide adaptation of open-source projects in a classroom setting, including (1) the selected project is limited to one particular project, (2) most studies only investigated on its effect on teaching a specific SE concept, and (3) students may make mistakes in their contribution which leads to poor quality code. Meanwhile, software companies have successfully launched programs like Google Summer of Code (GSoC) and FindBugs "fixit" to contribute to open-source projects. Inspired by the success of these programs, we propose GitHub-OSS Fixit, a teambased course project where students are taught to contribute to open-source Java projects by fixing bugs reported in GitHub. We described our course outline to teach students SE concepts by encouraging the usages of several automated program analysis tools. We also included the carefully designed instructions that we gave to students for participating in GitHub-OSS Fixit. As all lectures and labs are conducted online, we think that our course design could help in guiding future online SE courses. Overall, our survey results show that students think that GitHub-OSS Fixit could help them to improve many skills and apply the knowledge taught in class. In total, 154 students have submitted 214 pull requests to 24 different Java projects, in which 93 of them have been merged, and 46 have been closed by developers.

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“…Studies on GitHub. Several studies have shown the effectiveness of using GitHub Classroom for teaching [26], [27], [28], [29], [30]. Meanwhile, other studies focus on the characteristics of repositories on GitHub [31], [32], the social factors that affect the contribution in GitHub [33], and its pull-based software development model [34], [35].…”

Section: Related Workmentioning

confidence: 99%

GitHub-OSS Fixit: Fixing bugs at scale in a Software Engineering Course

Tan

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Many studies have shown the benefits of introducing open-source projects into teaching Software Engineering (SE) courses. However, there are several limitations of existing studies that limit the wide adaptation of open-source projects in a classroom setting, including (1) the selected project is limited to one particular project, (2) most studies only investigated on its effect on teaching a specific SE concept, and (3) students may make mistakes in their contribution which leads to poor quality code. Meanwhile, software companies have successfully launched programs like Google Summer of Code (GSoC) and FindBugs "fixit" to contribute to open-source projects. Inspired by the success of these programs, we propose GitHub-OSS Fixit, a course project where students are taught to contribute to opensource Java projects by fixing bugs reported in GitHub. We described our course outline to teach students SE concepts by encouraging the usages of several automated program analysis tools. We also included the carefully designed instructions that we gave to students for participating in GitHub-OSS Fixit. As all lectures and labs are conducted online, we think that our course design could help in guiding future online SE courses. Overall, our survey results show that students think that GitHub-OSS Fixit could help them to improve many skills and apply the knowledge taught in class. In total, 154 students have submitted 214 pull requests to 24 different Java projects, in which 59 of them have been merged, and 82 have been closed by developers.

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Collaborative bug finding for Android apps

Cited by 21 publications

References 63 publications

Identifying Similar Test Cases That Are Specified in Natural Language

Identifying Similar Test Cases That Are Specified in Natural Language

GitHub-OSS Fixit: Fixing Bugs at Scale in a Software Engineering Course

GitHub-OSS Fixit: Fixing bugs at scale in a Software Engineering Course

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