University of Limerick Institutional Repository

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

DSpace Repository

Show simple item record

dc.contributor.author Ahmad, Aakash
dc.contributor.author Jamshidi, Pooyan
dc.contributor.author Pahl, Claus
dc.date.accessioned 2015-02-19T14:16:39Z
dc.date.available 2015-02-19T14:16:39Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/10344/4308
dc.description peer-reviewed en_US
dc.description.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. en_US
dc.language.iso eng en_US
dc.publisher Wiley en_US
dc.relation.ispartofseries Journal of Software: Evolution and Process;26 (7) pp. 654-691
dc.relation.uri http://dx.doi.org/10.1002/smr.1643
dc.rights This is the author's version of the following article:The definitive version is available at www.blackwell-synergy.com" http://dx.doi.org/10.1002/smr.1643 en_US
dc.subject software architecture en_US
dc.subject architecture-centric software evolution en_US
dc.subject architecture evolution-reuse knowledge en_US
dc.subject systematic literature review en_US
dc.subject evidence-based study in software evolution en_US
dc.subject research synthesis en_US
dc.title Classification and comparison of architecture evolution-reuse knowledge – a systematic review en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1002/smr.1643
dc.contributor.sponsor SFI en_US
dc.relation.projectid 10/CE/I1855 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ULIR


Browse

My Account

Statistics