Retrieving curated stack overflow posts from project task similarities

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Abstract

Software development depends on diverse technologies and methods and, as a result, software development teams often need to handle issues in which team members are not experts. To address this lack of expertise, developers typically rely on information obtained from web-based Q&A sites such as Stack Overflow, a popular platform to find solutions to specific technology-related problems. However, access to these Q&A websites is currently not explicitly integrated with software development projects. Therefore, software developers often need to search for solutions to similar and recurring issues multiple times. This lack of integration not only hinders the reuse of the knowledge obtained but also compels developers to perform repeated searches for recurring problems. In this paper, we investigate an approach that explicitly associates project tasks with Stack Overflow posts that have already been curated by developers, and use project task similarities to investigate the possibility to suggest curated Stack Overflow posts. Precision and accuracy were 71.60% and 77.78%, respectively. We also found indications that project task elements such as the process activity, influence accuracy and precision if attempting to reuse curated Stack Overflow posts.

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APA

Melo, G., Oliveira, T., Alencar, P., & Cowan, D. (2019). Retrieving curated stack overflow posts from project task similarities. In Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE (Vol. 2019-July, pp. 415–418). Knowledge Systems Institute Graduate School. https://doi.org/10.18293/SEKE2019-083

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