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Allowing Overlapping Boundaries in Source Code using a Search Based Approach to Concept Binding

Mahdavi, K; Gold, N; Li, Z; Harman, M; (2007) Allowing Overlapping Boundaries in Source Code using a Search Based Approach to Concept Binding. In: Koschke, R and Merlo, E and Walenstein, A, (eds.) Duplication, Redundancy, and Similarity in Software: Dagstuhl Seminar Proceedings. Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany: Dagstuhl, Germany. Green open access

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Abstract

One approach to supporting program comprehension involves binding concepts to source code. Previously proposed approaches to concept binding have enforced nonoverlapping boundaries. However, real-world programs may contain overlapping concepts. This paper presents techniques to allow boundary overlap in the binding of concepts to source code. In order to allow boundaries to overlap, the concept binding problem is reformulated as a search problem. It is shown that the search space of overlapping concept bindings is exponentially large, indicating the suitability of sampling-based search algorithms. Hill climbing and genetic algorithms are introduced for sampling the space. The paper reports on experiments that apply these algorithms to 21 COBOL II programs taken from the commercial financial services sector. The results show that the genetic algorithm produces significantly better solutions than both the hill climber and random search.

Type: Proceedings paper
Title: Allowing Overlapping Boundaries in Source Code using a Search Based Approach to Concept Binding
Event: Duplication, Redundancy, and Similarity in Software: Dagstuhl Seminar 06301, 23-26 July 2006
Open access status: An open access version is available from UCL Discovery
Publisher version: http://drops.dagstuhl.de/opus/frontdoor.php?source...
Language: English
Additional information: This is the published version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Concept Assignment, Slicing, Clustering, Heuristic Algorithms
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10024609
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