Understanding the Surviving Bugsin Open Source Software through the Community Perspective : Using Bayesian Analysis
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Detail(s)
Original language | English |
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Title of host publication | Proceedings - 2019 Amity International Conference on Artificial Intelligence - (AICAI‘19) |
Editors | Sunil Kumar Khatr, Ajay Rana, P.K. Kapur |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 494-498 |
ISBN (electronic) | 978-1-5386-9346-9 |
ISBN (print) | 978-1-5386-9347-6 |
Publication status | Published - Feb 2019 |
Publication series
Name | Proceedings - Amity International Conference on Artificial Intelligence, AICAI |
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Conference
Title | 2019 Amity International Conference on Artificial Intelligence (AICAI 2019) |
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Location | Amity University Dubai |
Place | United Arab Emirates |
City | Dubai |
Period | 4 - 6 February 2019 |
Link(s)
Abstract
Mining the software repositories expose a lot of factors for software quality improvement. Researchers have worked extensively from various aspects of bug reports to predict, prevent and categorize the bugs in the software. Unfortunately, the survival aspect of software bugs is hardly reflected upon for bug removal efficiency. The surviving bugs are far more
crucial for software reliability as compared to timely detected bugs. In this study, we ahead to highlight the existence of surviving bugs in open source software projects from the community perspective. A causal assessment model is developed using the Bayesian network for drawing the probabilistic inference to answer the proposed research questions. The study used
data set from Apache 2.0.44 official release to reflect upon the findings.
crucial for software reliability as compared to timely detected bugs. In this study, we ahead to highlight the existence of surviving bugs in open source software projects from the community perspective. A causal assessment model is developed using the Bayesian network for drawing the probabilistic inference to answer the proposed research questions. The study used
data set from Apache 2.0.44 official release to reflect upon the findings.
Research Area(s)
- open source software, bug correction, bug detection, commenters, comments, Bayesian network, DYNAMICS, MODEL
Citation Format(s)
Understanding the Surviving Bugsin Open Source Software through the Community Perspective: Using Bayesian Analysis. / Razzaq, Seher; Xie, Min.
Proceedings - 2019 Amity International Conference on Artificial Intelligence - (AICAI‘19). ed. / Sunil Kumar Khatr; Ajay Rana; P.K. Kapur. Institute of Electrical and Electronics Engineers, 2019. p. 494-498 8701295 (Proceedings - Amity International Conference on Artificial Intelligence, AICAI ).
Proceedings - 2019 Amity International Conference on Artificial Intelligence - (AICAI‘19). ed. / Sunil Kumar Khatr; Ajay Rana; P.K. Kapur. Institute of Electrical and Electronics Engineers, 2019. p. 494-498 8701295 (Proceedings - Amity International Conference on Artificial Intelligence, AICAI ).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review