Data underlying the publication: Mining Software Testing Knowledge from Stack Overflow
DOI:10.4121/1e28497e-00d5-4be2-8533-0a143922421c.v1
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DOI: 10.4121/1e28497e-00d5-4be2-8533-0a143922421c
DOI: 10.4121/1e28497e-00d5-4be2-8533-0a143922421c
Datacite citation style
Gupta, Dibyendu (2023): Data underlying the publication: Mining Software Testing Knowledge from Stack Overflow. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/1e28497e-00d5-4be2-8533-0a143922421c.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
This paper aims to uncover and gather testing-related information from Stack Overflow, highlighting it as a valuable resource for practitioners seeking answers and guidance. The objective of the study is to accumulate knowledge from real-life experiences shared on Stack Overflow and bridge the knowledge gap between industry practices and teaching practices. The paper explores different types of software testing, popular frameworks, temporal trends of those frameworks, controversial opinions, and recommended practices/tips/advice/suggestions from Stack Overflow posts. The methodology involves determining search terms through literature, querying the Stack Exchange API, conducting frequency analysis of words from posts, and manually inspecting threads. Our results show that Selenium, Spring, JMeter, and React are the most popular frameworks discussed. Automated testing and JavaScript frameworks have shown an upward trajectory over the years. The recommendations made by practitioners were categorized based on the broad scope of topics covered. We draw comparisons and parallels with related previous research and discuss the technical limitations faced during the study. Overall, this paper uncovers valuable insights from Stack Overflow and provides practitioners with current knowledge of industry practices.
History
- 2023-06-23 first online, published, posted
Publisher
4TU.ResearchDataOrganizations
TU Delft, Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS)DATA
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