Software quality and the Capability Maturity Model
Communications of the ACM
An analysis of SEI software process assessment results: 1987–1991
ICSE '93 Proceedings of the 15th international conference on Software Engineering
A conceptual map of software process improvement
Scandinavian Journal of Information Systems
Capability Maturity Model, Version 1.1
IEEE Software
How ISO 9001 Compares With The CMM
IEEE Software
Selecting a Project's Methodology
IEEE Software
Extreme Programming from a CMM Perspective
IEEE Software
IEEE Software
New directions on agile methods: a comparative analysis
Proceedings of the 25th International Conference on Software Engineering
Communications of the ACM
Software Effort, Quality, and Cycle Time: A Study of CMM Level 5 Projects
IEEE Transactions on Software Engineering
Failure is a four-letter word: a parody in empirical research
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Software process evaluation: A machine learning approach
ASE '11 Proceedings of the 2011 26th IEEE/ACM International Conference on Automated Software Engineering
Overcoming the challenges in cost estimation for distributed software projects
Proceedings of the 34th International Conference on Software Engineering
The impact of process maturity on defect density
Proceedings of the ACM-IEEE international symposium on Empirical software engineering and measurement
Empirical Software Engineering
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We present the results of a three year field study of the software development process choices made by project teams at two leading offshore vendors. In particular, we focus on the performance implications of project teams that chose to augment structured, plan-driven processes to implement the CMM level-5 Key Process Areas (KPAs) with agile methods. Our analysis of 112 software projects reveals that the decision to augment the firm-recommended, plan-driven approach with improvised, agile methods was significantly affected by the extent of client knowledge and involvement, the newness of technology, and the project size. Furthermore this decision had a significant and mostly positive impact on project performance indicators such as reuse, rework, defect density, and productivity