Automatically Categorizing Software Technologies

Nassif, Mathieu; Robillard, Martin P.

doi:10.1109/tse.2018.2836450

Cited by 14 publications

(6 citation statements)

References 26 publications

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“…The studies of Sharma et al [22], Bhat et al [3], Brennan et al [7], Nassif et al [17] and Viviani et al [31] are similar to what is proposed to answer our RQ2. They identified knowledge in textual data from developer communication, through a classification technique.…”

Section: Related Worksupporting

confidence: 81%

Reusing software engineering knowledge from developer communication

Silva

2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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Section: Related Worksupporting

confidence: 81%

Reusing software engineering knowledge from developer communication

Silva

2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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“…However, the results show that our heuristics were rather strict, where they filtered out many simpleif sentences that ended up being highly rated by participants. We plan to investigate if ignoring parts of speech in the condition helps and if other means for differentiating technology related conditions can be used [36], [37], [38].…”

Section: Discussionmentioning

confidence: 99%

Essential Sentences for Navigating Stack Overflow Answers

Nadi

2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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Stack Overflow (SO) has become an essential resource for software development. Despite its success and prevalence, navigating SO remains a challenge. Ideally, SO users could benefit from highlighted navigational cues that help them decide if an answer is relevant to their task and context. Such navigational cues could be in the form of essential sentences that help the searcher decide whether they want to read the answer or skip over it. In this paper, we compare four potential approaches for identifying essential sentences. We adopt two existing approaches and develop two new approaches based on the idea that contextual information in a sentence (e.g., "if using windows") could help identify essential sentences. We compare the four techniques using a survey of 43 participants. Our participants indicate that it is not always easy to figure out what the best solution for their specific problem is, given the options, and that they would indeed like to easily spot contextual information that may narrow down the search. Our quantitative comparison of the techniques shows that there is no single technique sufficient for identifying essential sentences that can serve as navigational cues, while our qualitative analysis shows that participants valued explanations and specific conditions, and did not value filler sentences or speculations. Our work sheds light on the importance of navigational cues, and our findings can be used to guide future research to find the best combination of techniques to identify such cues.

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“…software technology [32]). The purpose component, however, is so far inadequately discussed in the literature.…”

Section: Methodsmentioning

confidence: 99%

Generating GitHub Repository Descriptions: A Comparison of Manual and Automated Approaches

Jazlyn¹,

Jang²,

Huang³

et al. 2021

Preprint

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Given the vast number of repositories hosted on GitHub, project discovery and retrieval have become increasingly important for GitHub users. Repository descriptions serve as one of the first points of contact for users who are accessing a repository. However, repository owners often fail to provide a high-quality description; instead, they use vague terms, the purpose of the repository is poorly explained, or the description is omitted entirely. In this work, we examine the current practice of writing GitHub repository descriptions. Our investigation leads to the proposal of the LSP (Language, Software technology, and Purpose) template to formulate good descriptions for GitHub repositories that are clear, concise, and informative. To understand the extent to which current automated techniques can support generating repository descriptions, we compare the performance of state-of-the-art text summarization methods on this task. Finally, our user study with GitHub users reveals that automated summarization can adequately be used for default description generation for GitHub repositories, while the descriptions which follow the LSP template offer the most effective instrument for communicating with GitHub users.

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Automatically Categorizing Software Technologies

Cited by 14 publications

References 26 publications

Reusing software engineering knowledge from developer communication

Reusing software engineering knowledge from developer communication

Essential Sentences for Navigating Stack Overflow Answers

Generating GitHub Repository Descriptions: A Comparison of Manual and Automated Approaches

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