eprintid: 1576532 rev_number: 26 eprint_status: archive userid: 608 dir: disk0/01/57/65/32 datestamp: 2017-10-02 13:00:20 lastmod: 2021-09-26 22:33:02 status_changed: 2017-10-02 13:00:20 type: article metadata_visibility: show creators_name: Paixao, M creators_name: Harman, M creators_name: Zhang, Y creators_name: Yu, Y title: An Empirical Study of Cohesion and Coupling: Balancing Optimisation and Disruption ispublished: pub divisions: UCL divisions: B04 divisions: C05 divisions: F48 keywords: software modularisation, software evolution, multiobjective search, Couplings, Measurement, Software engineering, Software systems, Evolutionary computation, Optimization note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: Search based software engineering has been extensively applied to the problem of finding improved modular structures that maximise cohesion and minimise coupling. However, there has, hitherto, been no longitudinal study of developers’ implementations, over a series of sequential releases. Moreover, results validating whether developers respect the fitness functions are scarce, and the potentially disruptive effect of search-based re-modularisation is usually overlooked. We present an empirical study of 233 sequential releases of 10 different systems; the largest empirical study reported in the literature so far, and the first longitudinal study. Our results provide evidence that developers do, indeed, respect the fitness functions used to optimise cohesion/coupling (they are statistically significantly better than arbitrary choices with p << 0:01), yet they also leave considerable room for further improvement (cohesion/coupling can be improved by 25% on average). However, we also report that optimising the structure is highly disruptive (on average more than 57% of the structure must change), while our results reveal that developers tend to avoid such disruption. Therefore, we introduce and evaluate a multiobjective evolutionary approach that minimises disruption while maximising cohesion/coupling improvement. This allows developers to balance reticence to disrupt existing modular structure, against their competing need to improve cohesion and coupling. The multiobjective approach is able to find modular structures that improve the cohesion of developers’ implementations by 22.52%, while causing an acceptably low level of disruption (within that already tolerated by developers). date: 2018-06 date_type: published official_url: https://doi.org/10.1109/TEVC.2017.2691281 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green article_type_text: Article verified: verified_manual elements_id: 1425888 doi: 10.1109/TEVC.2017.2691281 lyricists_name: Esteves Paixao, Matheus lyricists_name: Harman, Mark lyricists_id: MPAIX74 lyricists_id: MHARM36 actors_name: Harman, Mark actors_name: Flynn, Bernadette actors_id: MHARM36 actors_id: BFFLY94 actors_role: owner actors_role: impersonator full_text_status: public publication: IEEE Transactions on Evolutionary Computation volume: 22 number: 3 pagerange: 394-414 issn: 1941-0026 citation: Paixao, M; Harman, M; Zhang, Y; Yu, Y; (2018) An Empirical Study of Cohesion and Coupling: Balancing Optimisation and Disruption. IEEE Transactions on Evolutionary Computation , 22 (3) pp. 394-414. 10.1109/TEVC.2017.2691281 <https://doi.org/10.1109/TEVC.2017.2691281>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1576532/1/Paixao_Empirical_study_cohesion.pdf