Type

Journal Article

Authors

Claus Pahl
Pooyan Jamshidi
Aakash Ahmad

Subjects

Computer Science

Topics
evidence based study in software evolution research synthesis systematic knowledge architecture centric software evolution systematic literature review change patterns architecture evolution reuse knowledge software engineering software architecture

Classification and comparison of architecture evolution-reuse knowledge – a systematic review (2014)

Abstract Context: Architecture-centric software evolution (ACSE) enables changes in system’s structure and behaviour while maintaining a global view of the software to address evolution-centric trade-offs. The existing research and practices for ACSE primarily focus on design-time evolution and runtime adaptations to accommodate changing requirements in existing architectures. Objectives: We aim to identify, taxonomically classify and systematically compare the existing research focused on enabling or enhancing change reuse to support ACSE. Method: We conducted a systematic literature review (SLR) of 32 qualitatively selected studies, and taxonomically classified these studies based on solutions that enable i) empirical acquisition and ii) systematic application of architecture evolution-reuse knowledge to guide ACSE. Results: We identified six distinct research themes that support acquisition and application of architecture evolution-reuse knowledge. We investigated: a) how evolution-reuse knowledge is defined, classified and represented in the existing research to support ACSE, b) what are the existing methods, techniques, and solutions to support: b) empirical acquisition and c) systematic application of architecture evolution-reuse knowledge. Conclusions: Change patterns (34% of selected studies) represent a predominant solution, followed by evolution styles (25%) and adaptation strategies and policies (22%) to enable application of reuse knowledge. Empirical methods for acquisition of reuse knowledge represent 19% including pattern discovery, configuration analysis, evolution and maintenance prediction techniques (approximately 6% each). A lack of focus on empirical acquisition of reuse knowledge suggests the need of solutions with architecture change mining as a complementary and integrated phase for architecture change execution.
Collections Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Lero: The Irish Software Engineering Research Centre
Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Status = Published
Ireland -> University of Limerick -> Faculty of Science and Engineering
Ireland -> University of Limerick -> LERO
Ireland -> Dublin City University -> Subject = Computer Science: Software engineering
Ireland -> University of Limerick -> LERO - Project partner authors
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing

Full list of authors on original publication

Claus Pahl, Pooyan Jamshidi, Aakash Ahmad

Experts in our system

1
Claus Pahl
Dublin City University
Total Publications: 191
 
2
Pooyan Jamshidi
Dublin City University
Total Publications: 26