Quality and Success in Open Source Software: A Systematic Mapping

Gezici, Bahar; Ozdemir, Nurseda; Yılmaz, Nebi; Coşkun, Evren; Tarhan, Ayça; Chouseinoglou, Oumout

doi:10.1109/seaa.2019.00062

Cited by 9 publications

(7 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, substantial work has focused on modeling the success of OSS projects [34,38,49]. Even though there is no universally agreed definition of OSS success [21], there are two main perspectives. The first one is from the development process viewpoint, which is often measured by technical metrics of software [22], e.g., code defect density [40], response time [35], and error resolution rate [28].…”

Section: Background and Theoriesmentioning

confidence: 99%

Sustainability forecasting for Apache incubator projects

Yin

Chen

Xuan

et al. 2021

Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

View full text Add to dashboard Cite

Although OSS development is very popular, ultimately more than 80% of OSS projects fail. Identifying the factors associated with OSS success can help in devising interventions when a project takes a downturn. OSS success has been studied from a variety of angles, more recently in empirical studies of large numbers of diverse projects, using proxies for sustainability, e.g., internal metrics related to productivity and external ones, related to community popularity. The internal socio-technical structure of projects has also been shown important, especially their dynamics. This points to another angle on evaluating software success, from the perspective of self-sustaining and self-governing communities.To uncover the dynamics of how a project at a nascent development stage gradually evolves into a sustainable one, here we apply a socio-technical network modeling perspective to a dataset of Apache Software Foundation Incubator (ASFI), sustainabilitylabeled projects. To identify and validate the determinants of sustainability, we undertake a mix of quantitative and qualitative studies of ASFI projects' socio-technical network trajectories. We develop interpretable models which can forecast a project becoming sustainable with 93+% accuracy, within 8 months of incubation start. Based on the interpretable models we describe a strategy for real-time monitoring and suggesting actions, which can be used by projects to correct their sustainability trajectories.

show abstract

Section: Background and Theoriesmentioning

confidence: 99%

Sustainability forecasting for Apache incubator projects

Yin

Chen

Xuan

et al. 2021

Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

View full text Add to dashboard Cite

show abstract

“…Their work only enumerated prior studies about OSS success, but they had not analyzed these studies' differences. The study of Gezici et al (2019) is the closest to our work. They surveyed the relation of quality and success of OSS.…”

Section: Assessment Of Oss Successmentioning

confidence: 77%

Evaluation indicators for open-source software: a review

et al. 2021

View full text Add to dashboard Cite

In recent years, the widespread applications of open-source software (OSS) have brought great convenience for software developers. However, it is always facing unavoidable security risks, such as open-source code defects and security vulnerabilities. To find out the OSS risks in time, we carry out an empirical study to identify the indicators for evaluating the OSS. To achieve a comprehensive understanding of the OSS assessment, we collect 56 papers from prestigious academic venues (such as IEEE Xplore, ACM Digital Library, DBLP, and Google Scholar) in the past 21 years. During the process of the investigation, we first identify the main concerns for selecting OSS and distill five types of commonly used indicators to assess OSS. We then conduct a comparative analysis to discuss how these indicators are used in each surveyed study and their differences. Moreover, we further undertake a correlation analysis between these indicators and uncover 13 confirmed conclusions and four cases with controversy occurring in these studies. Finally, we discuss several possible applications of these conclusions, which are insightful for the research on OSS and software supply chain.

show abstract

“…In order to classify the answers to RQ2.3 that examined which aspects of OSS could be evaluated by QEMoF, some OSS specific models in literature 16,18,19,29,38 were taken as reference in addition to ISO/IEC 25010, which served as a standard for OSS only in terms of product quality and quality in use. In order to classify the answers to RQ4.6 examining the frequency distribution of software metrics used for evaluation in QEMoF, some studies 16,44,45 were taken as reference. However, there is still a threat that data extraction for answering RQ4.10 for the required skills to use QEMoF might have included some degree of subjectivity in the classification.…”

Section: Discussionmentioning

confidence: 99%

“…Software metrics are associated with software attributes and enable to convert these attributes to a concrete form by obtaining quantifiable data. Based on the studies 16,44,45 in the literature, the software metrics used for evaluation in the QEMoF are classified as shown in Table 7. The table provides the categories, the metrics that fall into each category, and the number and the frequency of these metrics as addressed in the proposed QEMoF.…”

Section: Rq46mentioning

confidence: 99%

See 1 more Smart Citation

Quality evaluation models or frameworks for open source software: A systematic literature review

Yılmaz

Tarhan

2022

J Software Evolu Process

View full text Add to dashboard Cite

As open project repositories have become widespread, evaluating the quality of open source software (OSS) has gained attention in the software community. Despite the variety in quality evaluation models or frameworks (QEMoF) proposed for OSS, their adoption in practice remains limited. To further investigate this argument, a systematic literature review (SLR) has been conducted to characterize the existing QEMoF for OSS, based on particular properties, and to examine comprehensively their content and structure for identifying the gap between theory and practice. In this context, a total of 36 primary studies in the period of 2003-2020 have been analyzed. It has been identified that the majority of QEMoF takes ISO/IEC 9126 as a reference, evaluates community-based aspects, mostly evaluates maintainability and usability as quality attributes, supports subjective and quantitative evaluations, and faces challenges due to diverse and dynamic nature of OSS products. For a better overview of the state of the art in the field, evaluation criteria for comparing the overall quality of the QEMoF are identified and applied. Finally, overall findings are discussed, and suggestions are provided for practitioners and researchers to formulate more robust studies in the future, which can advance the current situation for the benefit of the software community.

show abstract

Quality and Success in Open Source Software: A Systematic Mapping

Cited by 9 publications

References 12 publications

Sustainability forecasting for Apache incubator projects

Sustainability forecasting for Apache incubator projects

Evaluation indicators for open-source software: a review

Quality evaluation models or frameworks for open source software: A systematic literature review

Contact Info

Product

Resources

About