An Empirical Study of Bug Fixing Rate

Zou, Weiqin; Xia, Xin; Zhang, Weiqiang; Chen, Zhenyu; Lo, David

doi:10.1109/compsac.2015.57

Cited by 10 publications

(6 citation statements)

References 50 publications

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“…Similarly, our empirical analysis has confirmed the positive effects of AERI on the bug fixing rate. The bug fixing rate has been studied by Zou et al [28] who analysed the characteristics of bug fixing rates in Eclipse and Mozilla. They measured bug fixing rate, defined as the number of fixed over closed bugs, at a yearly basis from 2001 to 2014, and found that the rate increased from 0.49 to 0.77 for Eclipse and 0.32 to 0.72 for Mozilla.…”

Section: Discussionmentioning

confidence: 99%

“…The most influential factors on bug fixing time were bug location and bug reporting time. Zou et al [28] investigated the characteristics of bug fixing rate and studied the impact of a reporter's different contribution behaviors to the bug fixing rate in Eclipse and Mozilla. Among others, they observed an increase in fixing rate over the years for both projects.…”

Section: Bug Fixing Time Prediction and Estimationmentioning

confidence: 99%

See 1 more Smart Citation

A Longitudinal Analysis of Bug Handling Across Eclipse Releases

Khalil

Constantinou

Mens

et al. 2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Large open source software projects, like Eclipse, follow a continuous software development process, with a regular release cycle. During each release, new bugs are reported, triaged and resolved. Previous studies have focused on various aspects of bug fixing, such as bug triaging, bug prediction, and bug process analysis. Most studies, however, do not distinguish between what happens before and after each scheduled release. We are also unaware of studies that compare bug fixing activities across different project releases. This paper presents an empirical analysis of the bug handling process of Eclipse over a 15-year period, considering 138K bug reports from Bugzilla, including 16 annual Eclipse releases and two quarterly releases in 2018. We compare the bug resolution rate, the fixing rate, the bug triaging time and the fixing time before and after each release date, and we study the possible impact of "release pressure". Among others, our results reveal that Eclipse bug handling activity is improving over time, with an important decrease in the number of reported bugs before releases, an increase in the bug fixing rate and an increasingly balanced bug handling workload before and after releases. The recent transition from an annual to a quarterly release cycle continued to improve the bug handling process.

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Section: Discussionmentioning

confidence: 99%

Section: Bug Fixing Time Prediction and Estimationmentioning

confidence: 99%

A Longitudinal Analysis of Bug Handling Across Eclipse Releases

Khalil

Constantinou

Mens

et al. 2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

View full text Add to dashboard Cite

show abstract

“…13 Optimizing response times on bug fixing is an area of active research. 64,65 Defect resolution thus also provides an ideal backdrop against which different types of developer collaborations and interactions can be effectively studied.…”

Section: Team Assembly and Functioningmentioning

confidence: 99%

“…While every phase of software development demands such collaboration, one of the important phases of such collaboration is bug fixing 13 . Optimizing response times on bug fixing is an area of active research 64,65 . Defect resolution thus also provides an ideal backdrop against which different types of developer collaborations and interactions can be effectively studied.…”

Section: Related Workmentioning

confidence: 99%

Understanding the relation between repeat developer interactions and bug resolution times in large open source ecosystems: A multisystem study

Datta

Roychoudhuri²,

Majumder³

2020

J Software Evolu Process

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Large‐scale software systems are being increasingly built by distributed teams of developers who interact across geographies and time zones. Ensuring smooth knowledge transfer and the percolation of skills within and across such teams remain key challenges for organizations. Towards addressing this challenge, organizations often grapple with questions around whether and how repeat collaborations between members of a team relate to outcomes of important activities. In the context of this paper, the word ‘repeat interaction’ does not imply a greater number of interactions; it refers to repeat interaction between a pair of developers who have collaborated before. In this paper, we empirically examine such a question using real‐world data from three diverse development ecosystems, collectively involving 400,000+ units of work and 600,000+ comments exchanged between numerous developers. Our statistical models consistently establish a counter‐intuitive relation between repeat developer interaction and bug resolution times. Our experimental results show that more instances of repeat developer interactions over bug fixing are associated with more time taken for the bugs to be fixed. Given the expanse and variety of the underlying data, our results offer an unexpected set of insights on a key dynamic of collaboration in software development ecosystems. We discuss how these insights can influence the practice of large‐scale software development at individual, team and organizational levels.

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“…They found bug location and bug reporting time to be the most influential factors on bug fixing time. Zou et al [10] examined the characteristics of the bug fixing rate and studied the impact of a reporter's different contribution behaviors to the bug fixing rate in Eclipse and Mozilla. They observed an increase in the fixing rate over the years for both projects, however, the observed rates were not high, especially for Mozilla.…”

Section: B Bug Handling Characteristicsmentioning

confidence: 99%

Studying the Impact of Policy Changes on Bug Handling Performance

Khalil

2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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The majority of the software development effort is spent on software maintenance. Bug handling constitutes one of the major software maintenance activities. Earlier studies have empirically investigated various aspects of bug handling, such as bug triaging, bug fixing, and bug process analysis. However, results from previous studies may not be applicable to contemporary agile software development practices. Moreover, these studies did not investigate how changes in the development policies and supporting tools impact the bug handling process. Therefore, our main goal is to investigate the impact of such changes on the bug handling process performance. To do so, we are conducting empirical studies on large and long-lived open source software projects. We report on our current research findings and outline the ongoing Ph.D. research project of the first author.

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An Empirical Study of Bug Fixing Rate

Cited by 10 publications

References 50 publications

A Longitudinal Analysis of Bug Handling Across Eclipse Releases

A Longitudinal Analysis of Bug Handling Across Eclipse Releases

Understanding the relation between repeat developer interactions and bug resolution times in large open source ecosystems: A multisystem study

Studying the Impact of Policy Changes on Bug Handling Performance

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