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inspect4py : a knowledge extraction framework for Python code repositories

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dc.contributor.authorFilgueira, Rosa
dc.contributor.authorGarijo, Daniel
dc.contributor.editorLo, David
dc.contributor.editorMcIntosh, Shane
dc.contributor.editorNovielli, Nicole
dc.date.accessioned2022-03-24T09:26:07Z
dc.date.available2022-03-24T09:26:07Z
dc.date.issued2022-10-17
dc.identifier278376823
dc.identifier27de83b5-f2cb-4db6-aec7-05597b768267
dc.identifier000850208000033
dc.identifier85134039337
dc.identifier.citationFilgueira , R & Garijo , D 2022 , inspect4py : a knowledge extraction framework for Python code repositories . in D Lo , S McIntosh & N Novielli (eds) , Proceedings of the 19th International Conference on Mining Software Repositories (MSR 2022) . ACM , New York, NY , pp. 232-236 , 2022 Mining Software Repositories Conference (MSR 2022) , Pittsburgh , Pennsylvania , United States , 23/05/22 . https://doi.org/10.1145/3524842.3528497en
dc.identifier.citationconferenceen
dc.identifier.isbn9781450393034
dc.identifier.urihttps://hdl.handle.net/10023/25075
dc.description.abstractThis work presents inspect4py, a static code analysis framework designed to automatically extract the main features, metadata and documentation of Python code repositories. Given an input folder with code, inspect4py uses abstract syntax trees and state of the art tools to find all functions, classes, tests, documentation, call graphs, module dependencies and control flows within all code files in that repository. Using these findings, inspect4py infers different ways of invoking a software component. We have evaluated our framework on 95 annotated repositories, obtaining promising results for software type classification (over 95% F1-score). With inspect4py, we aim to ease the understandability and adoption of software repositories by other researchers and developers.
dc.format.extent5
dc.format.extent556410
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofProceedings of the 19th International Conference on Mining Software Repositories (MSR 2022)en
dc.rightsCopyright © 2022 Association of Computing Machinery. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://dl.acm.org/.en
dc.subjectCode miningen
dc.subjectSoftware codeen
dc.subjectSoftware classificationen
dc.subjectSoftware documentationen
dc.subjectCode understandingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQA76 Computer softwareen
dc.subjectZA4050 Electronic information resourcesen
dc.subjectNSen
dc.subjectNISen
dc.subject.lccQA75en
dc.subject.lccQA76en
dc.subject.lccZA4050en
dc.titleinspect4py : a knowledge extraction framework for Python code repositoriesen
dc.typeConference itemen
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.identifier.doi10.1145/3524842.3528497
dc.identifier.urlhttps://doi.org/10.1145/3524842en
dc.identifier.urlhttps://github.com/SoftwareUnderstanding/inspect4pyen
dc.identifier.urlhttps://doi.org/10.5281/zenodo.5907936en
dc.identifier.urlhttps://conf.researchr.org/details/msr-2022/msr-2022-data-showcase/25/Inspect4py-A-Knowledge-Extraction-Framework-for-Python-Code-Repositoriesen


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