Abstract
Software module clustering is the problem of automatically partitioning the structure of a software system using low-level dependencies in the source code to understand and improve the system’s architecture. Munch, a clustering tool based on search-based software engineering techniques, was used to modularise a unique dataset of sequential source code software versions. This paper employs a seeding technique, based on results from previous modularisations, to improve the effectiveness and efficiency of the procedure. In order to reduce the running time further, a statistic for controlling the number of iterations of the modularisation based on the similarities between time adjacent graphs is introduced. We examine the convergence of the heuristic search technique and estimate and evaluate a number of stopping criterion. The paper reports the results of extensive experiments conducted on our comprehensive time-series dataset and provides evidence to support our proposed techniques.
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Arzoky, M., Swift, S., Counsell, S., Cain, J. (2014). An Approach to Controlling the Runtime for Search Based Modularisation of Sequential Source Code Check-ins. In: Blockeel, H., van Leeuwen, M., Vinciotti, V. (eds) Advances in Intelligent Data Analysis XIII. IDA 2014. Lecture Notes in Computer Science, vol 8819. Springer, Cham. https://doi.org/10.1007/978-3-319-12571-8_3
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DOI: https://doi.org/10.1007/978-3-319-12571-8_3
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