Statistical analysis of popular open source software projects and their communities

Author(s):  
Andi Wahju Rahardjo Emanuel
2020 ◽  
Vol 25 (6) ◽  
pp. 5255-5294
Author(s):  
Mozhan Soltani ◽  
Felienne Hermans ◽  
Thomas Bäck

Abstract Open source software projects often use issue repositories, where project contributors submit bug reports. Using these repositories, more bugs in software projects may be identified and fixed. However, the content and therefore quality of bug reports vary. In this study, we aim to understand the significance of different elements in bug reports. We interviewed 35 developers to gain insights into their perceptions on the importance of various contents in bug reports. To assess our findings, we surveyed 305 developers. The results show developers find it highly important that bug reports include crash description, reproducing steps or test cases, and stack traces. Software version, fix suggestions, code snippets, and attached contents have lower importance for software debugging. Furthermore, to evaluate the quality of currently available bug reports, we mined issue repositories of 250 most popular projects on Github. Statistical analysis on the mined issues shows that crash reproducing steps, stack traces, fix suggestions, and user contents, have statistically significant impact on bug resolution times, for ∼70%, ∼76%, ∼55%, and ∼33% of the projects. However, on avarage, over 70% of bug reports lack these elements.


Author(s):  
Huaiwei Yang ◽  
Shuang Liu ◽  
Lin Gui ◽  
Yongxin Zhao ◽  
Jun Sun ◽  
...  

2021 ◽  
Vol 5 (CSCW1) ◽  
pp. 1-28
Author(s):  
R. Stuart Geiger ◽  
Dorothy Howard ◽  
Lilly Irani

2009 ◽  
Vol 78 (7) ◽  
pp. 457-472 ◽  
Author(s):  
Balaji Janamanchi ◽  
Evangelos Katsamakas ◽  
Wullianallur Raghupathi ◽  
Wei Gao

2016 ◽  
Vol 24 (4) ◽  
pp. 22-44 ◽  
Author(s):  
Jing Wu ◽  
Khim-Yong Goh ◽  
He Li ◽  
Chuan Luo ◽  
Haichao Zheng

Drawing on the theoretical lens of communication patterns in organizational theory, this research analyzed the longitudinal success of open source software (OSS) projects by employing social network analysis method, based on extensive analyses of empirical data. This study is expected to provide an understanding on how communication patterns established in different roles and different levels. The authors not only measured OSS success from both developers and users' perspectives, but also extended the existing research by including the potential relationships among these success measures in the estimation model. Following the panel data econometric analysis methodology, they evaluated their research hypotheses using the Three-Stage Least Squares model, accounting for both time-period and project fixed effects. The authors' results indicated that according to the objectives of projects, a proper and planned control for the communication among team members is crucial for the success of OSS projects.


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