Evolution of developer social network and its impact on bug fixing process

Kumar, Amit; Gupta, Avdhesh

doi:10.1145/2442754.2442764

Cited by 16 publications

(23 citation statements)

References 23 publications

(25 reference statements)

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“…It is interesting to note that LU involvement in software development is related mainly to defect reporting, analysis and repair [18,31,56]. These activities closely match the three main stages in the innovation problem solving process: problem detection, analysis and removal [47,49].…”

Section: Introductionmentioning

confidence: 84%

Performance implications of stage-wise lead user participation in software development problem solving

Colazo¹

2014

Decision Support Systems

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Section: Introductionmentioning

confidence: 84%

Performance implications of stage-wise lead user participation in software development problem solving

Colazo¹

2014

Decision Support Systems

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“…We selected Eclipse as a case study because it: 1) is a large and mature project that has had a sufficiently long release history with associated bug reporting activity 2) has been widely studied in previous software evolution research [30], [31] and in research about bug fixing in particular [3], [6]; and 3) is a popular open source project that has a stable development community and a regular release process. Eclipse relies on the Bugzilla bug tracking platform [32] to manage and keep track of its bugs, allowing developers to effectively manage all concerns of the bug life cycle.…”

Section: A Selected Case Studymentioning

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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“…For feature "B3", there were 3 PSs, [11,60,8], where the constructed network was a multiplex network. Additionally, only 5 PSs, [46,34,58,25,53], considered the temporality of a network and provided a dynamic network. The rest of the primary studies considered a static network.…”

Section: The Constructed Network Their Validity and Measures Validmentioning

confidence: 99%

On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review

Abufouda¹,

Abukwaik²

2017

IJDKP

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Abstract.Background: Network science is the set of mathematical frameworks, models, and measures that are used to understand a complex system modeled as a network composed of nodes and edges. The nodes of a network represent entities and the edges represent relationships between these entities. Network science has been used in many research works for mining human interaction during different phases of software engineering (SE). Objective: The goal of this study is to identify, review, and analyze the published research works that used network analysis as a tool for understanding the human collaboration on different levels of software development. This study and its findings are expected to be of benefit for software engineering practitioners and researchers who are mining software repositories using tools from network science field. Method: We conducted a systematic literature review, in which we analyzed a number of selected papers from different digital libraries based on inclusion and exclusion criteria. Results: We identified 35 primary studies (PSs) from four digital libraries, then we extracted data from each PS according to a predefined data extraction sheet. The results of our data analysis showed that not all of the constructed networks used in the PSs were valid as the edges of these networks did not reflect a real relationship between the entities of the network. Additionally, the used measures in the PSs were in many cases not suitable for the used networks. Also, the reported analysis results by the PSs were not, in most cases, validated using any statistical model. Finally, many of the PSs did not provide lessons or guidelines for software practitioners that can improve the software engineering practices. Conclusion: Although employing network analysis in mining developers' collaboration showed some satisfactory results in some of the PSs, the application of network analysis needs to be conducted more carefully. That is said, the constructed network should be representative and meaningful, the used measure needs to be suitable for the context, and the validation of the results should be considered. More and above, we state some research gaps, in which network science can be applied, with some pointers to recent advances that can be used to mine collaboration networks.

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Evolution of developer social network and its impact on bug fixing process

Cited by 16 publications

References 23 publications

Performance implications of stage-wise lead user participation in software development problem solving

Performance implications of stage-wise lead user participation in software development problem solving

A Longitudinal Analysis of Bug Handling Across Eclipse Releases

On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review

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