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Improving Software Processes using Statistical Process Control and Experimental Design

K. Harihara Sudhan, Umesh Kumar Mishra


A well-managed software development process has become strategic core competency in the organization, enabling high-class software development, quality estimation, prediction and control. The process could not be continuously improved if: Sound engineering practices are sacrificed to schedule, there is no feedback on process performance, and each person does something different, wide variation occurs in performing identical tasks, Commitment to improve is not organization-wide. However, improving software development processes is demanding and complex task of organizations for that it needs continuous improvement in defined processes. This paper is proposing a statistical approach (data driven) for process improvement. This approach is based on Software process improvement best practices, Guidelines and different quality standard. The major components of the proposed approach are (i) Process identification for improvement; (ii) Data identification and collection for the process improvement; (iii) Identification of statistical methods / techniques for data analysis; (iv) Create/suggest a model that would be used for process improvement


Software Process, Data, Process Performance Baselines, Process Performance Models, Normality, Statistical Method

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