Refactoring Recommendations Based on the Optimization of Socio-Technical Congruence

Manuel De Stefano, Fabiano Pecorelli, Damian Andrew Tamburri, Fabio Palomba, Andrea De Lucia

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)

Abstract

Software development is known to be a social activity that involves developers, project managers, and stakeholders. Recent studies have proved a direct relation between social and technical aspects, e.g., poor coordination among developers may lead to an increase of technical debt in source code. The so-called socio-technical congruence measures the level of coordination existing in an organization at their different levels. In this late-breaking idea paper, we propose a novel way to employ the socio-technical congruence in the context of source code quality improvement: we design a community-based refactoring recommendation approach that aims at optimizing socio-technical congruence while keeping into account the source code dependencies among the components of a software project. A search-based algorithm is employed to this purpose and we envision the novel approach to be suitable for providing Extract Class and Extract Package refactoring recommendations.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Software Maintenance and Evolution, ICSME 2020
Pages794-796
Number of pages3
ISBN (Electronic)9781728156194
DOIs
Publication statusPublished - Sept 2020

Bibliographical note

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Keywords

  • Recommendation Systems
  • Refactoring
  • Search-based Software Engineering

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