Understanding the triaging and fixing processes of long lived bugs

Saha, Ripon K.; Khurshid, Sarfraz; Perry, Dewayne E.

doi:10.1016/j.infsof.2015.03.002

Cited by 36 publications

(21 citation statements)

References 26 publications

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“…For example, the bug triager checks whether it is a valid bug or a duplicate bug (similar to any previously fixed bug) and, if required, consults with other developers of the project, etc. . Usually these activities are performed manually without using any automated tools.…”

Section: Introductionmentioning

confidence: 99%

An empirical investigation of single‐objective and multiobjective evolutionary algorithms for developer's assignment to bugs

Karim

Ruhe

Rahman³

et al. 2016

J Software Evolu Process

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In this paper, the modeling of developers' assignment to bugs (DAB) is studied. The problem is modeled both as a single objective (minimize bug fix time) and as a bi-objective (minimize bug fix time and cost) combinatorial optimization problem. Two models of developer assignment are considered where in the first model a single developer is assigned per bug (single developer model), while in the second model a single developer is assigned for each competency area of a bug (individual competency model). The latter model is proposed in this paper. For the single developer model, GA@DAB, an existing genetic algorithm-based approach, is extended to support precedence among bugs. For the individual competency model of DAB, one genetic algorithm-based approach (Competence@DAB) and one nondominated sorting genetic algorithm II-based approach (CompetenceMulti 2 @DAB ) are proposed to generate solutions minimizing time and minimizing both time and cost, respectively. The performance of the proposed approaches was evaluated for 2040 bugs of 19 open-source milestone projects from the ECLIPSE platform. Our results and analysis show that the proposed individual competency model is far better than the single developer model, with average bug fix time reduction of 39.7% across all projects.

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Section: Introductionmentioning

confidence: 99%

An empirical investigation of single‐objective and multiobjective evolutionary algorithms for developer's assignment to bugs

Karim

Ruhe

Rahman³

et al. 2016

J Software Evolu Process

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“…Saha et al [1] extracted code change metrics, such as the number of changed files, to identify the reasons for delays in bug fixes and to improve the overall bug fixing process in four Eclipse projects: JDT, CDT, Plug-in Development Environment (PDE), and Platform. Their results showed that a significant number of long-lived bugs could be reduced through careful triaging and prioritization if developers would be able to predict their severity, change effort and change impact in advance.…”

Section: B Bug Triagingmentioning

confidence: 99%

“…In order to address the most important bugs for each release, a bug handling process is followed, relying on dedicated collaborative bug tracking tools such as Bugzilla. Researchers have investigated different factors in the bug handling process that may affect bug triaging and fixing time, and provided models for predicting and estimating this time [1]- [10]. They also studied techniques to improve the process of bug fixing [11], [12], bug triaging [13]- [15], or assigning developers to bug reports [16]- [21].…”

Section: Introductionmentioning

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)

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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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“…Anbalagan and Vouk [1] studied the bug reports of Ubuntu project and found that there is a strong linear relationship between the number of users participating in a bug report and the median time taken to fix it. Besides the attribute of bug reports, Saha et al [12] extracted code change metrics, e.g., number of changed files, for analyzing the reason of long live bugs in four Eclipse projects. Hooimeijer and Weimer [5] measured bug-report-triage time using regression analysis based on bug report metrics.…”

Section: Related Workmentioning

confidence: 99%

“…Most of them studied the time of the bug fixing process as a whole (i.e., from a bug was reported until it was resolved), while neglecting the particularity at its different stages. However, some studies pointed out that factors with the same value can usually result in different fixing time [12]. This may derive from the inherent nature of the bug fixing process, i.e., the whole process consists of several individual stages, and different stages focus on different sub-activities of the whole process with different stakeholders involved.…”

Section: Introductionmentioning

confidence: 99%

Stage-oriented Analysis on Factors Impacting Bug Fixing Time

Wang

et al. 2016

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-The timely fixing of bugs is important to ensure software quality. In Open Source Software (OSS) development, behaviors of stakeholders impact the bug fixing process, especially the different stages respectively. However, most of the existing studies on impact factors of bug fixing time usually treat bug fixing process as a whole, while neglecting the particularity at its different stages. Ignoring the detail of different stages cannot let us understand why the fixing time is longer or shorter. In this paper, we aimed at investigating whether the factors have different impacts on the time of different stages and the whole process. Three stages of the whole fixing process were formalized, and twenty-four factors were defined and extracted from three aspects: bug reports, their associated source code and code changes. An empirical study based on two OSS projects, Eclipse JDT Core and Linux Kernel, was conducted for the investigation. The results of our study provide a very positive validation that the influence of factors on bug fixing time is stage related, rather than for the whole process. Our results can help developers better understand influences of factors on the bug fixing process, and thus provide opportunities to improve their process effectively.

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Understanding the triaging and fixing processes of long lived bugs

Cited by 36 publications

References 26 publications

An empirical investigation of single‐objective and multiobjective evolutionary algorithms for developer's assignment to bugs

An empirical investigation of single‐objective and multiobjective evolutionary algorithms for developer's assignment to bugs

A Longitudinal Analysis of Bug Handling Across Eclipse Releases

Stage-oriented Analysis on Factors Impacting Bug Fixing Time

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