Impact of Introducing Domain-Specific Modelling in Software Maintenance: An Industrial Case StudyShow others and affiliations
2016 (English)In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 42, no 3, p. 248-263, article id 7270333Article in journal (Refereed) Published
Abstract [en]
Domain-specific modelling (DSM) is a modern software development technology that aims at enhancing productivity. One of the claimed advantages of DSM is increased maintainability of software. However, current empirical evidence supporting this claim is lacking. In this paper, we contribute evidence from a case study conducted at a software development company. We study how the introduction of DSM affected the maintenance of a legacy system. We collected data about the maintenance phase of a system that was initially developed using manual programming, but which was gradually replaced by DSM development. We performed statistical analyses of the relation between the use of DSM and the time needed to resolve defects, the defect density, and the phase in which defects were detected. The results show that after introducing DSM the defect density is lower, that defects are found earlier, but resolving defects takes longer. Other observed benefits are that the number of developers and the number of person-hours needed for maintaining the system decreased, and the portability to new platforms increased. Our findings are useful for organizations that consider introducing DSM and would like to know which benefits can be realized in software maintenance.
Place, publisher, year, edition, pages
2016. Vol. 42, no 3, p. 248-263, article id 7270333
Keywords [en]
Empirical investigation, maintenance measurement, process measurement, productivity, software maintenance, Defect density, Defects, Legacy systems, Maintenance, Software design, Development technology, Domain-specific modelling, Industrial case study, Process measurements, Computer software maintenance
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-32616DOI: 10.1109/TSE.2015.2479221Scopus ID: 2-s2.0-84963795496OAI: oai:DiVA.org:ri-32616DiVA, id: diva2:1158808
2017-11-212017-11-212023-11-22Bibliographically approved