Change profile analysis of open-source software systems to understand their evolutionary behavior

Saini, Munish; Chahal, Kuljit Kaur

doi:10.1007/s11704-016-6301-0

Cited by 8 publications

(9 citation statements)

References 18 publications

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“…In our previous work [9, 10], we performed the change classification [29] of commit activity data of 106 OSS projects into different change types (as corrective, adaptive, perfective, preventive, and enhancement) by using the automated change classification method. Further the change activity data of 106 projects are evaluated by cluster analysis to classify the projects on the basis of activity performed.…”

Section: Study Setupmentioning

confidence: 99%

“…Complete project‐related details of the 106 OSS projects such as project name, language, domain, license, total commits (before cleaning), total commits classified by automated classifier, number of lines inserted, number of lines deleted, and total number of file changed are presented in Tables 1 and 2 of Appendix [10].…”

Section: Study Setupmentioning

confidence: 99%

“…Our previous work focuses [9, 10] on only one dimension of a change, i.e. intent of making a change.…”

Section: Introductionmentioning

confidence: 99%

“…performed over a period of time. We identified, with the help of cluster analysis, three categories of OSS projects for each change type – high activity, moderate activity, and low activity [10]. Project activity is defined on the basis of number of changes (a.k.a.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we extended our previous work [10], to investigate the relation between projects change‐type activity and other attributes like change effort and change size to understand the change dynamics of the OSS projects. The aim is to have a combined view of the change activity and other change‐related attributes such as change purpose, change effort, and change size as a software system evolves.…”

Section: Introductionmentioning

confidence: 99%

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Analysing change profiles of open source software projects using burst detection

Saini

Chahal

2017

IET softw.

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Software evolution refers to the phenomenon of continuous software change and growth after its initial development. A version control system records all information about these changes. Several research studies in the past have studied the historical records of changes of open source software (OSS) projects and found them useful for understanding the software evolution process. However, most of them investigate the distributions of changes types, change size, and change effort in an isolated manner. There is no work, to the best of our knowledge, which takes a combined view of various dimensions of a change. This study examines the change activity in 106 OSS projects from three points of view: change purpose (type), change size, and change effort. The common patterns in change type, change size, and change effort are highlighted using the burst detection technique. The burst detection technique helps in identifying the peaks in the time series and compares them with the peaks of other time series. The results indicate that the change-type activity of OSS projects is significantly related with change effort, and change size for high and moderate-activity clusters. Though for low-activity cluster, this commonality of patterns is not there for all types of changes.

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Section: Study Setupmentioning

confidence: 99%

Section: Study Setupmentioning

confidence: 99%

“…Our previous work focuses [9, 10] on only one dimension of a change, i.e. intent of making a change.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysing change profiles of open source software projects using burst detection

Saini

Chahal

2017

IET softw.

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Predicting Issue Resolution Time of OSS Using Multiple Features

Qiao,

Lu,

Wang

et al. 2024

J Software Evolu Process

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Developers utilize issue tracking systems to track ideas, feedback, tasks, and bugs for projects in the open‐source software ecosystem of GitHub. In this context, extensive bug reports and feature requests are raised as issues that need to be resolved. This makes issue resolution prediction become more and more important in project management. To address this problem, this paper constructed a multiple feature set from the perspectives of project, issue, and developer, by combining static and dynamic features of issues. Then, we refine a feature set based on the feature's importance. Furthermore, we proposed a method to explore what features and how these features affect the prediction of issue resolution time. Experiments are conducted on a dataset of 46,735 resolved issues from 18 popular GitHub projects to validate the effectiveness of the refined feature set. The results show that our prediction method outperforms the baseline methods.

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Developer Dynamics and Syntactic Quality of Commit Messages in OSS Projects

Chahal

Saini

2018

IFIP Advances in Information and Communication Technology

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Change profile analysis of open-source software systems to understand their evolutionary behavior

Cited by 8 publications

References 18 publications

Analysing change profiles of open source software projects using burst detection

Analysing change profiles of open source software projects using burst detection

Predicting Issue Resolution Time of OSS Using Multiple Features

Developer Dynamics and Syntactic Quality of Commit Messages in OSS Projects

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