Empirical Studies in Question-Answering Systems: A Discussion

Krüger, Jacob; Schröter, Ivonne; Kenner, Andy; Leich, Thomas

doi:10.1109/cesi.2017.6

Cited by 6 publications

(3 citation statements)

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“…Community-question-answering systems aim to identify the best answer for any question, facilitating the search of users with similar problems [30]. The advantages of such systems are the broad background of the users that may be practitioners, researchers, and students, as well as their global background, as these systems are not limited to a specific region [20]. Thus, they can provide a good basis for an empirical analysis to address some of the known biases of locality and sampling in empirical studies.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, they can provide a good basis for an empirical analysis to address some of the known biases of locality and sampling in empirical studies. Still, communityquestion-answering systems also face several problems, for instance, managing the large number of data, integrating the right users, as well as ensuring the quality of questions and answers [20,30,31].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, they are concerned with other topics than software product lines. Based on such works, we described methods to perform empirical analyses of the contents and discussed their flaws and limitations[20]. The closest to this paper is our own previous work, in which we presented some initial findings on aspect-oriented programming[17].…”

mentioning

confidence: 99%

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Are You Talking about Software Product Lines? An Analysis of Developer Communities

Krüger¹

2019

Preprint

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Community-question-answering systems, such as Stack Overflow, provide a platform for various communities to ask questions, dis- cuss topics, and find knowledge. Especially software developers are heavily relying on such systems to identify solutions for their problems. While the content of community-question-answering systems may be less scientific, it usually represents practical knowledge from various perspectives and backgrounds. Thus, analyzing this content can be valuable for the scientific community to understand previous and current (i.e., open questions) needs of practitioners. In this paper, we report a systematic analysis of two websites that comprise communities with a focus on software development: Stack Exchange and Quora. We extract questions, answers, comments, and discussions on software product lines in general and feature modeling in particular. The results provide a historical perspective, an overview on commonly addressed scopes, and a classification of discussed topics and problems. Moreover, our findings are interesting to understand the practical impact of software-product-line techniques outside of well-analyzed case studies, to support lectures by identifying regularly asked questions, and to scope tool development based on reported technical problems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%