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Towards Improved Initial Mapping in Semi Automatic Clustering
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0000-0003-1154-5308
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (DISA ; DSIQ)ORCID iD: 0000-0003-1173-5187
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).ORCID iD: 0000-0002-0835-823X
2018 (English)In: ECSA 2018: PROCEEDINGS OF THE 12TH EUROPEAN CONFERENCE ON SOFTWARE ARCHITECTURE: COMPANION PROCEEDINGS, Association for Computing Machinery (ACM), 2018Conference paper, Published paper (Refereed)
Abstract [en]

An important step in Static Architecture Conformance Checking (SACC) is the mapping of source code entities to entities in the intended architecture. This step is currently relying on manual work, which is one hindrance for more widespread adoption of SACC in industry. Semi-automatic clustering is a promising approach to improve this, and the HuGMe clustering algorithm is an example of such a technique for use in SACC. But HuGMe relies on an initial set of clustered source code elements and algorithm parameters. We investigate the automatic mapping performance of HuGMe in two experiments to gain insight into what influence the starting set has in a medium-sized open source system, JabRef, which contain a relatively large number of architectural violations. Our results show that the highest automatic mapping performance can be achieved with a low number of elements within the initial set. However, the variability of the performance is high. We find a benefit in favoring source code elements with a high fan-out in the initial set.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018.
Keywords [en]
Clustering, Software Architecture Conformance, HuGMe
National Category
Computer and Information Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-80159DOI: 10.1145/3241403.3241456ISI: 000455670400051Scopus ID: 2-s2.0-85055708745ISBN: 978-1-4503-6483-6 (print)OAI: oai:DiVA.org:lnu-80159DiVA, id: diva2:1284853
Conference
12th European Conference on Software Architecture (ECSA), Madrid, Spain, Sep 24-28, 2018
Available from: 2019-02-01 Created: 2019-02-01 Last updated: 2019-08-29Bibliographically approved

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Olsson, TobiasEricsson, MorganWingkvist, Anna

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  • apa
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