On the impact of obliviousness and quantification on model composition effort

Everton Guimaraes, Alessandro Garcia, Kleinner Farias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Researchers and practitioners advocate that design properties, such as obliviousness and quantification, can improve the modularity of software systems, thereby reducing the effort of composing design models. However, there is no empirical knowledge about how these design properties impact model composition effort. This paper, therefore, performs an empirical study to understand this impact. The main contributions are: (i) quantitative indicators to evaluate to what extent such design properties impact model composition effort; (ii) an objective evaluation of the impact of such modularity properties in 26 versions of two software projects by using statistical tests; and (iii) lessons learned on whether (and how) modularity anomalies related to misuse of quantification and obliviousness in the input models can significantly increase model composition effort.

Original languageEnglish (US)
Title of host publicationProceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PublisherAssociation for Computing Machinery
Pages1043-1048
Number of pages6
ISBN (Print)9781450324694
DOIs
StatePublished - Jan 1 2014
Event29th Annual ACM Symposium on Applied Computing, SAC 2014 - Gyeongju, Korea, Republic of
Duration: Mar 24 2014Mar 28 2014

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Other

Other29th Annual ACM Symposium on Applied Computing, SAC 2014
CountryKorea, Republic of
CityGyeongju
Period3/24/143/28/14

All Science Journal Classification (ASJC) codes

  • Software

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  • Cite this

    Guimaraes, E., Garcia, A., & Farias, K. (2014). On the impact of obliviousness and quantification on model composition effort. In Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014 (pp. 1043-1048). (Proceedings of the ACM Symposium on Applied Computing). Association for Computing Machinery. https://doi.org/10.1145/2554850.2555034