Publication: Quantitative CMMI assessment for offshoring through the analysis of project management repositories
Issued Date
2009-01-01
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ISSN
18651348
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2-s2.0-68149094342
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Mahidol University
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SCOPUS
Bibliographic Citation
Lecture Notes in Business Information Processing. Vol.35 LNBIP, (2009), 32-44
Suggested Citation
Thanwadee Sunetnanta, Ni On Nobprapai, Olly Gotel Quantitative CMMI assessment for offshoring through the analysis of project management repositories. Lecture Notes in Business Information Processing. Vol.35 LNBIP, (2009), 32-44. doi:10.1007/978-3-642-02987-5_6 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/27365
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Title
Quantitative CMMI assessment for offshoring through the analysis of project management repositories
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Abstract
The nature of distributed teams and the existence of multiple sites in offshore software development projects pose a challenging setting for software process improvement. Often, the improvement and appraisal of software processes is achieved through a turnkey solution where best practices are imposed or transferred from a company's headquarters to its offshore units. In so doing, successful project health checks and monitoring for quality on software processes requires strong project management skills, well-built onshore-offshore coordination, and often needs regular onsite visits by software process improvement consultants from the headquarters' team. This paper focuses on software process improvement as guided by the Capability Maturity Model Integration (CMMI) and proposes a model to evaluate the status of such improvement efforts in the context of distributed multi-site projects without some of this overhead. The paper discusses the application of quantitative CMMI assessment through the collection and analysis of project data gathered directly from project repositories to facilitate CMMI implementation and reduce the cost of such implementation for offshore-outsourced software development projects. We exemplify this approach to quantitative CMMI assessment through the analysis of project management data and discuss the future directions of this work in progress. © 2009 Springer Berlin Heidelberg.