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Wyświetlanie 1-2 z 2
Tytuł:
Analysis of Factors Influencing Developers Sentiments in Commit Logs: Insights from Applying Sentiment Analysis
Autorzy:
Kaur, Rajdeep
Chahal, Kuljit Kaur
Saini, Munish
Powiązania:
https://bibliotekanauki.pl/articles/2123250.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
human factor
software development team
software developer
developers' sentiment
sentiment analysis
commit log
developer activity type
team size
Opis:
Background: In the open source software paradigm, software development depends upon efforts of volunteer members that are geographically dispersed and collaborate with each other over the Internet. Communication artifacts like mailing lists, forums, and issue tracking systems are used by developers for communication. The way they express themselves through these communication channels greatly influences their productivity, efficiency of development activities, and survival of the project as well. Therefore, it is essential to understand affective state of developers’ contributions to make software engineering more effective. Aim: This study examined commit logs of seven GitHub projects to analyze developers’ sentiments. This study also investigated the relationship of developers’ sentiments in commit logs with team size of project, type of change activity, and contribution volume. Method: Sentiments of developers are calculated using SentiStrength-SE tool that is specialized in software engineering domain. Results: Our findings revealed that the majority of sentiments conveyed by developers in commit logs were neutral. Furthermore, we found that team size, change activity, and commit contribution volume influenced sentiments conveyed in commit logs. Conclusion: Our findings will help project managers to better understand developer sentiments while performing different software development tasks/activities. It will be beneficial in improving developer productivity and retention.
Źródło:
e-Informatica Software Engineering Journal; 2022, 16, 1; art. no. 220102
1897-7979
Pojawia się w:
e-Informatica Software Engineering Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machine Learning or Information Retrieval Techniques for Bug Triaging: Which is better?
Autorzy:
Goyal, A.
Sardana, N.
Powiązania:
https://bibliotekanauki.pl/articles/384096.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
bug triaging
bug report assignment
developer recommendation
machine learning
information retrieval
Opis:
Bugs are the inevitable part of a software system. Nowadays, large software development projects even release beta versions of their products to gather bug reports from users. The collected bug reports are then worked upon by various developers in order to resolve the defects and make the final software product more reliable. The high frequency of incoming bugs makes the bug handling a difficult and time consuming task. Bug assignment is an integral part of bug triaging that aims at the process of assigning a suitable developer for the reported bug who corrects the source code in order to resolve the bug. There are various semi and fully automated techniques to ease the task of bug assignment. This paper presents the current state of the art of various techniques used for bug report assignment. Through exhaustive research, the authors have observed that machine learning and information retrieval based bug assignment approaches are most popular in literature. A deeper investigation has shown that the trend of techniques is taking a shift from machine learning based approaches towards information retrieval based approaches. Therefore, the focus of this work is to find the reason behind the observed drift and thus a comparative analysis is conducted on the bug reports of the Mozilla, Eclipse, Gnome and Open Office projects in the Bugzilla repository. The results of the study show that the information retrieval based technique yields better efficiency in recommending the developers for bug reports.
Źródło:
e-Informatica Software Engineering Journal; 2017, 11, 1; 117-141
1897-7979
Pojawia się w:
e-Informatica Software Engineering Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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