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Genetic algorithms and heuristics hybridized for software architecture recovery

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Abstract

Large scale software systems must be decomposed into modular units to reduce maintenance efforts. Software Architecture Recovery (SAR) approaches have been introduced to analyze dependencies among software modules and automatically cluster them to achieve high modularity. These approaches employ various types of algorithms for clustering software modules. In this paper, we discuss design decisions and variations in existing genetic algorithms devised for SAR. We present a novel hybrid genetic algorithm that introduces three major differences with respect to these algorithms. First, it employs a greedy heuristic algorithm to automatically determine the number of clusters and enrich the initial population that is generated randomly. Second, it uses a different solution representation that facilitates an arithmetic crossover operator. Third, it is hybridized with a heuristic that improves solutions in each iteration. We present an empirical evaluation with seven real systems as experimental objects. We compare the effectiveness of our algorithm with respect to a baseline and state-of-the-art hybrid genetic algorithms. Our algorithm outperforms others in maximizing the modularity of the obtained clusters.

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Notes

  1. https://www.minitab.com/

  2. https://github.com/hasansozer/MOSARCH

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Funding

The work is supported by the Scientific and Research Council of Turkey under Grant No. 120E488

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Authors and Affiliations

  1. Computer Science Department, Özyeğin University, 34794, Istanbul, Turkey

    M. Esad Simitcioğlu, Abdullah Saydemir & Hasan Sözer

  2. Industrial Engineering Department, Özyeğin University, 34794, Istanbul, Turkey

    Milad Elyasi, Ali Ekici & O. Örsan Özener

  3. IMT Atlantique, LS2N-CNRS, La Chantrerie, 4 rue Alfred Kastler, 44300, Nantes, France

    Milad Elyasi

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  1. Milad Elyasi
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  2. M. Esad Simitcioğlu
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  3. Abdullah Saydemir
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  4. Ali Ekici
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  5. O. Örsan Özener
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  6. Hasan Sözer
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Contributions

ME, AE, OOO and HS contributed to the conceptualization of the approach and development of the methodology. ME, AS and MES implemented the algorithms, conducted the experiments, and collected the results. All authors contributed to the writing of the original draft, and they all reviewed the final manuscript.

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Correspondence to Hasan Sözer.

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Elyasi, M., Simitcioğlu, M.E., Saydemir, A. et al. Genetic algorithms and heuristics hybridized for software architecture recovery. Autom Softw Eng 30, 19 (2023). https://doi.org/10.1007/s10515-023-00384-y

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