Text Mining Studies of Software Repository Contents

Dobrzyński, Bartosz; Sosnowski, J.

doi:10.5220/0011970100003464

Cited by 2 publications

(14 citation statements)

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“…Syntactic features were related to natural language words used, other objects, and linguistic deficiencies (incorrect words, grammar flaws). Semantic features could be derived using advanced text mining techniques; this problem was discussed in many papers, including our previous one [45]. Here, we restricted our studies to the following problems:…”

Section: Textual Attributesmentioning

confidence: 99%

“…Deriving semantic significance from these texts needed a special adaptation. We proposed an original approach in [45], which considered specific features of these texts, namely non-NL objects. Moreover, they could be enhanced by correlating them with other attributes.…”

Section: Textual Attributesmentioning

confidence: 99%

“…Hence, it was reasonable to consider them in text mining algorithms. We developed such algorithms for issue and comment classification, which was presented in [45]. A clustering of issues based on textual properties could facilitate their investigation.…”

Section: Textual Attributesmentioning

confidence: 99%

“…Hence, it was reasonable to consider them in text mining algorithms. We developed such algorithms for issue and comment classification, which was presented in [45].…”

Section: Textual Attributesmentioning

confidence: 99%

“…The number of comments and time features could be correlated with the issue-handling processing presented in our previous paper [15]. In [45], we presented text mining schemes for classifying comment categories and analyzing their sequences. This also facilitated the process of detecting discussion deficiencies among project actors.…”

Section: Issue Commenting Activitiesmentioning

confidence: 99%

See 4 more Smart Citations

Enhancing Software Project Monitoring with Multidimensional Data Repository Mining

Reszka,

Sosnowski,

Dobrzyński

2023

Electronics

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Software project development and maintenance activities have been reported in various repositories. The data contained in these repositories have been widely used in various studies on specific problems, e.g., predicting bug appearance, allocating issues to developers, and identifying duplicated issues. Developed analysis schemes are usually based on simplified data models while issue report details are neglected. Confronting this problem requires a deep and wide-ranging exploration of software repository contents adapted to their specificities, which differs significantly from classical data mining. This paper is targeted at three aspects: the structural and semantic exploration of repositories, deriving characteristic features in value and time perspectives, and defining the space of project monitoring goals. The considerations presented demonstrate a holistic image of the project development process, which is useful in the assessment of its efficiency and identification of imperfections. The original analysis introduced in this work was verified using open source and some commercial software project repositories.

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Section: Textual Attributesmentioning

confidence: 99%

Section: Textual Attributesmentioning

confidence: 99%

Section: Textual Attributesmentioning

confidence: 99%

“…Hence, it was reasonable to consider them in text mining algorithms. We developed such algorithms for issue and comment classification, which was presented in [45].…”

Section: Textual Attributesmentioning

confidence: 99%

Section: Issue Commenting Activitiesmentioning

confidence: 99%

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Enhancing Software Project Monitoring with Multidimensional Data Repository Mining

Reszka,

Sosnowski,

Dobrzyński

2023

Electronics

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Graph-Driven Exploration of Issue Handling Schemes in Software Projects

Dobrzyński,

Sosnowski

2024

Applied Sciences

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The Issue Tracking System (ITS) repositories are rich sources of software development documentation that are useful in assessing the status and quality of software projects. An original model is proposed for tracing issue handling activities and their impact on project progress. As opposed to classical data mining of software repositories, we consider fine-grained features of issues which provide a better insight into project evolution. A thorough analysis of repository contents allows us to define useful metrics for characterizing issue handling schemes. These metrics are derived from the introduced graph model and developed original data mining algorithms targeting timing, issue flow progress and project actor activity aspects. This study is associated with issue processing states and their sequences (handling paths), leading to problem resolution. The introduced taxonomy of issue processing schemes facilitates the creation of a pertinent knowledge database and the identification of both bad (anomalies) and good practices. The proposed approach is illustrated with experimental results related to a representative set of ITS project repositories. These results enhance experts’ knowledge of the project and can be used for correct decision-making actions. They reveal weak points in project development and possible directions for improvement.

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Text Mining Studies of Software Repository Contents

Cited by 2 publications

References 0 publications

Enhancing Software Project Monitoring with Multidimensional Data Repository Mining

Enhancing Software Project Monitoring with Multidimensional Data Repository Mining

Graph-Driven Exploration of Issue Handling Schemes in Software Projects

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