Universiti Teknologi Malaysia Institutional Repository

Sequential strategy for software process measurement using statistical process control

Alhassan, Muhammad Abubakar (2014) Sequential strategy for software process measurement using statistical process control. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computing.



Software development process (SDP) and Software products are like two sides of a coin. We cannot achieve one without another. Today, in our software industries, monitoring software process is very challenging. Many problems of software process monitoring are hampering the quality of our software products. Several researchers in this area contributed their quota on addressing process monitoring issues using quantitative techniques. In this study, we address the problem of detecting software process deviations as a result of variations, investigating the causes of variations in software process, and the problem of process measurement. In addition, the study focus on code peer review process (CPRP). The first two problems can be addressed using one of the powerful quantitative techniques known as statistical process control (SPC). Also, control charts would be used in this study as it has been proved to be one of the suitable tools of SPC in monitoring process issues. As we know, the more defects we found during SDP, the less quality of the software product. Therefore, this study considers defect density as the metric to be use due to its significance in determining product quality. In order to have good analysis, this study conduct a case study on both Capability Maturity Model (CMM), lower and higher maturity levels software industries. On the other hand, to handle the problem of process measurement, a Sequential Strategy for Process Measure (SSPM) is proposed. This strategy is evaluated by Instrument for Evaluating Software Measurement Repository (IESMR) and Normative Information Model-based System Analysis and Design (NIMSAD) framework. Based on its evaluation, the strategy is similar to IESMR but differ in selecting measures, therefore it can be use for process measurement.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Sains (Sains Komputer)) - Universiti Teknologi Malaysia, 2014 ; Supervisor : Dayang Norhayati Abang Jawawi
Uncontrolled Keywords:quality control, statistical methods, process control
Subjects:T Technology > TS Manufactures
ID Code:41717
Deposited By: Haliza Zainal
Deposited On:08 Oct 2014 02:20
Last Modified:07 Sep 2017 00:34

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