Refactoring fat interfaces using a genetic algorithm

Daniele Romano, Steven Raemaekers, Martin Pinzger

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

11 Citations (Scopus)


Recent studies have shown that the violation of the Interface Segregation Principle (ISP) is critical for maintaining and evolving software systems. Fat interfaces (i.e., interfaces violating the ISP) change more frequently and degrade the quality of the components coupled to them. According to the ISP the interfaces' design should force no client to depend on methods it does not invoke. Fat interfaces should be split into smaller interfaces exposing only the methods invoked by groups of clients. However, applying the ISP is a challenging task when fat interfaces are invoked differently by many clients. In this paper, we formulate the problem of applying the ISP as a multi-objective clustering problem and we propose a genetic algorithm to solve it. We evaluate the capability of the proposed genetic algorithm with 42,318 public Java APIs whose clients' usage has been mined from the Maven repository. The results of this study show that the genetic algorithm outperforms other search based approaches (i.e., random and simulated annealing approaches) in splitting the APIs according to the ISP.

Original languageEnglish
Title of host publicationProceedings - 30th International Conference on Software Maintenance and Evolution, ICSME 2014
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages10
ISBN (Electronic)9780769553030
Publication statusPublished - 4 Dec 2014
Event30th International Conference on Software Maintenance and Evolution, ICSME 2014 - Victoria, Canada
Duration: 28 Sep 20143 Oct 2014


Conference30th International Conference on Software Maintenance and Evolution, ICSME 2014


  • APIs
  • genetic algorithms
  • Interface Segregation Principle
  • refactoring
  • search-based software engineering

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