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Fex: Assisted Identification of Domain Features from C Programs

Müller, Patrick ; Narasimhan, Krishna ; Mezini, Mira (2021)
Fex: Assisted Identification of Domain Features from C Programs.
21st International Working Conference on Source Code Analysis and Manipulation. virtual Conference (27.-28.09.2021)
doi: 10.1109/SCAM52516.2021.00029
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Modern software typically performs more than one functionality. These functionalities or features are not always organized in a way for modules representing these features to be used individually. Many software engineering approaches like programming language constructs, or product line visualization techniques have been proposed to organize projects as modules. Unfortunately, much legacy software suffer from years or decades of improper coding practices that leave the modules in the code almost undetectable. In such scenarios, a desirable requirement is to identify modules representing different features to be extracted. In this paper, we propose a novel approach that combines information retrieval and program analysis approaches to allow domain experts to identify slices of the program that represent modules using natural language search terms. We evaluate our approach by building a proof of concept tool in C, and extract modules from open source projects.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2021
Autor(en): Müller, Patrick ; Narasimhan, Krishna ; Mezini, Mira
Art des Eintrags: Bibliographie
Titel: Fex: Assisted Identification of Domain Features from C Programs
Sprache: Englisch
Publikationsjahr: 24 November 2021
Verlag: IEEE
Buchtitel: Proceedings: IEEE 21st International Working Conference on Source Code Analysis and Manipulation - SCAM 2021
Veranstaltungstitel: 21st International Working Conference on Source Code Analysis and Manipulation
Veranstaltungsort: virtual Conference
Veranstaltungsdatum: 27.-28.09.2021
DOI: 10.1109/SCAM52516.2021.00029
Kurzbeschreibung (Abstract):

Modern software typically performs more than one functionality. These functionalities or features are not always organized in a way for modules representing these features to be used individually. Many software engineering approaches like programming language constructs, or product line visualization techniques have been proposed to organize projects as modules. Unfortunately, much legacy software suffer from years or decades of improper coding practices that leave the modules in the code almost undetectable. In such scenarios, a desirable requirement is to identify modules representing different features to be extracted. In this paper, we propose a novel approach that combines information retrieval and program analysis approaches to allow domain experts to identify slices of the program that represent modules using natural language search terms. We evaluate our approach by building a proof of concept tool in C, and extract modules from open source projects.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Softwaretechnik
DFG-Sonderforschungsbereiche (inkl. Transregio)
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Hinterlegungsdatum: 05 Mär 2024 15:38
Letzte Änderung: 11 Jun 2024 16:07
PPN: 519039084
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