Taxonomies of software ecosystem health metrics and practices: a systematic literature review

dc.contributor.authorYousef Zadeh Shooshtari, Arman
dc.contributor.supervisorStorey, Margaret-Anne
dc.date.accessioned2020-12-22T04:26:32Z
dc.date.available2020-12-22T04:26:32Z
dc.date.copyright2020en_US
dc.date.issued2020-12-21
dc.degree.departmentDepartment of Computer Scienceen_US
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractContext: Since the beginnings of software engineering, metrics (such as SLOCs) and practices have been used in an attempt to measure and improve the features of software development projects, their process, or their contributors. Measuring and enhancing software ecosystem features brings a new complexity level because a software ecosystem comprises several interrelated software projects. Over the past two decades, software ecosystems have gained considerable attention, and researchers have proposed various metrics and practices to measure and improve software ecosystems' health. Objective: This thesis presents a systematic literature review that aims to build comprehensive taxonomies for software ecosystem health metrics and practices. These taxonomies synthesize the results of previous categorizations and update them with newer metrics and practices proposed since then. This study also aims to collect and synthesize all the definitions, metrics, and practices proposed to define, measure, and improve software ecosystem health in the literature. Method: I conducted a systematic literature review and identified 40 primary studies related to defining and measuring software ecosystem health. I extracted the definitions, metrics, and practices for software ecosystem health from the primary studies, and then I categorized the metrics and practices to build the taxonomies. Results: I identified a total of 7 different definitions for software ecosystem health, 142 different metrics, and 174 various practices for software ecosystem health. Our taxonomies for software ecosystem health metrics and practices have three categories (niche creation, productivity, and robustness). Each of these categories has several sub-categories of metrics and practices. Conclusion: Software ecosystems have a wide range of stakeholders that have different perspectives regarding software ecosystem health. To satisfy this spectrum, researchers have proposed various metrics and practices to measure and improve software ecosystems' health. To improve unifying contrasting opinions, I conducted this study. The metrics and practices proposed are diverse in both purpose and the data required to compute them. Some metrics are presented along with a method on how to compute them. In contrast, others are defined abstractly without an operational approach to calculate them, and some are mentioned without a clear rationale. Furthermore, the same metric or practice is often proposed in more than one publication using different names. This thesis addresses these alignment problems.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/12477
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectSoftware ecosystem healthen_US
dc.subjectMetricsen_US
dc.subjectSystematic literature reviewen_US
dc.titleTaxonomies of software ecosystem health metrics and practices: a systematic literature reviewen_US
dc.typeThesisen_US

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