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Towards Hierarchical Code-to-Architecture Mapping Using Information Retrieval
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Software Quality and Digital Modernisation (SQUAD))ORCID iD: 0000-0002-7288-5552
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).ORCID iD: 0000-0002-3180-9182
2021 (English)In: ECSA-C 2021 Companion Proceedings of the 15th European Conference on Software Architecture / [ed] Heinrich R; Mirandola R; Weyns D, CEUR-WS , 2021, Vol. 2978, article id 172547Conference paper, Published paper (Refereed)
Abstract [en]

Automating the mapping of a system’s code to its architecture helps improve the adoption of successful Software Architecture Consistency Checking (SACC) methods like Reflexion Modelling. InMap is an interactive code-to-architecture mapping recommendation technique that has been shown to do this task with good recall and precision using natural language software architecture descriptions of the architectural modules. However, InMap like most other automated recommendations techniques maps low level source code units like source code files or classes to architectural modules. For large complex systems this can still be a barrier to adoption due to the effort required by a software architect when accepting or rejecting the recommendations. In this study we propose an extension to InMap that provides recommendations for higher-level source code units, that is, packages. It utilizes InMap’s information retrieval capabilities, using minimal architecture documentation, applied to a software’s codebase, to recommend mappings between the software’s high-level source code entities and its architectural modules. We show that using our proposed hierarchical mapping technique we are able to reduce the effort required by the architect, as high as 6-fold in some cases, and still achieve good precision and fairly good recall.

Place, publisher, year, edition, pages
CEUR-WS , 2021. Vol. 2978, article id 172547
Keywords [en]
Automated Mapping, Software Architecture Consistency Checking, Information Retrieval
National Category
Software Engineering
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kau:diva-87461Scopus ID: 2-s2.0-85117846729OAI: oai:DiVA.org:kau-87461DiVA, id: diva2:1616495
Conference
15th European Conference on Software Architecture
Available from: 2021-12-03 Created: 2021-12-03 Last updated: 2022-02-28Bibliographically approved

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Scopushttp://ceur-ws.org/Vol-2978/saerocon-paper10.pdf

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Sinkala, Zipani TomHerold, Sebastian

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