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Ahmad, Muhammad Ovais
Publications (1 of 1) Show all publications
Tegegne, E. W., Seppänen, P. & Ahmad, M. O. (2019). Software development methodologies and practices in start-ups. IET Software, 13(6), 497-509
Open this publication in new window or tab >>Software development methodologies and practices in start-ups
2019 (English)In: IET Software, ISSN 1751-8806, E-ISSN 1751-8814, Vol. 13, no 6, p. 497-509Article in journal (Refereed) Published
Abstract [en]

Software start-ups are aiming to develop cutting-edge software products under highly uncertain conditions, overcoming fast-growing markets under multiple influences. This study aims to identify and analyse the existing scientific literature regarding software development methodologies and practices in software start-ups published between January 2006 and December 2017 using the systematic mapping study. The results identified 37 relevant primary studies out of 1982 papers. To validate the results from the mapping study, an empirical study was based on the research data collected from 14 real-life software start-ups located in Finland, Italy and Norway. The result shows that Agile and Lean start-up methodologies are the most commonly used in software start-ups due to the flexible nature and easy tailoring. A total of 144 software development work practices are extracted from the primary studies. This study contributes to the research in several ways: (i) provides state of the art regarding software development methods and practices in software start-up contexts, (ii) reports commonly used methods along with its benefits identified in primary studies and (iii) identifies opportunities for future software start-up research.

Place, publisher, year, edition, pages
Institution of Engineering and Technology, 2019
Keywords
Mapping, Empirical studies, Scientific literature, Software development methodologies, Software development methods, Software products, State of the art, Systematic mapping studies, Uncertain condition, Software design
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-75974 (URN)10.1049/iet-sen.2018.5270 (DOI)000499993300002 ()2-s2.0-85075825906 (Scopus ID)
Available from: 2019-12-13 Created: 2019-12-13 Last updated: 2020-01-09Bibliographically approved
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