Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764954
Title: An empirical study on object-oriented software dependencies : logical, structural and semantic
Author: Ajienka, Nemitari Miebaka
ISNI:       0000 0004 7658 505X
Awarding Body: Brunel University London
Current Institution: Brunel University
Date of Award: 2018
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
Three of the most widely studied software dependency types are the structural, logical and semantic dependencies. Logical dependencies capture the degree of co-change between software artifacts. Semantic dependencies capture the degree to which artifacts, comments and names are related. Structural dependencies capture the dependencies in the source code of artifacts. Prior studies show that a combination of dependency analysis (e.g., semantic and logical analysis) improves accuracy when predicting which artifacts are likely to be impacted by ripple effects of software changes (though not to a large extent) compared to individual approaches. In addition, some dependencies could be hidden dependencies when an analysis of one dependency type (e.g., logical) does not reveal artifacts only linked by another dependency type (semantic). While previous studies have focused on combining dependency information with minimal benefits, this Thesis explores the consistency of these measurements, and whether hidden dependencies arise between artifacts, and in any of the axes studied. In this Thesis, 79 Java projects are empirically studied to investigate (i) the direct influence and the degree of overlap between dependency types on three axes (logical - structural (LSt); logical - semantic (LSe); structural - semantic (StSe)) (structural, logical and semantic), and (ii) the presence of hidden coupling on the axes. The results show that a high proportion of hidden dependencies can be detected on the LSt and StSe axes. Notwithstanding, the LSe axis shows a much smaller proportion of hidden dependencies. Practicable refactoring methods to mitigate hidden dependencies are proposed in the Thesis and discussed with examples.
Supervisor: Capiluppi, A. ; Counsell, S. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.764954  DOI: Not available
Keywords: Software coupling ; Change impact analysis ; Text mining ; Software metrics ; Open source software
Share: