The study of the software development process is a relatively new research area but it is growing rapidly. This development process, also called 'the software life cycle' or 'the software process', is the methodology used throughout the industry for the planning, design, implementation, testing and maintenance that takes place during the creation of a software product. Over the years a variety of different process models have been developed. From the numerous process models now available, project managers need validation of the choice he/she has made for a software development model that he/she believes will provide the best results. Yet the quality software so sought after by software project managers can be enhanced by improving the development process through which it is delivered. Well tested, reliable evidence is needed to assist these project managers in choosing and planning a superior software process as well as for improving the adopted software process. While some guidelines for software process validation and improvement have been provided, such as CMMI, quantitative evidence is, in fact, scarce. The quantitative evidence sometimes may not be able to be obtained from high level processes that refer to a planned process model, such as a waterfall model. Furthermore, there has been little analysis of low level processes. These low level processes refer to the actions of how a development team follow a high level software process model to develop a software product. We describe these low level processes as project enactment. Normally there is a gap between the high level software process and the project enactment. In order to improve this software development process, this gap needs to be identified, measured and analyzed. In this dissertation, we propose an approach that examines the deviation between a planned process model and the project enactment of that plan. We measure the discrepancy from two aspects: consistency and inconsistency. The analytical results of the proposed approach, which include both qualitative and quantitative data, provide powerful and precise evidence for tailoring, planning and selecting any software process model. The entire approach is composed of four major phases: 1) re-presentation of the planned process model, 2) pre-processing the low level process data, 3) process mining, and 4) analysis and comparison of the recovered process model and planned process model. We evaluate the proposed approach in three case studies: a small, a medium, and a large-sized project obtained from an industrial software development organization. The appropriate data on low level processes is collected and our approach is then applied to these projects individually. From each case study we then performed a detailed analysis of the inconsistencies that had surfaced as well as the consistencies between the plan and the enactment models. An analysis of the inconsistencies revealed that several 'agile' practices were introduced during the project's development even though the planned process model was initially based on 'ISO-12207' instead of the 'agile' method. In addition, our analysis identifies the patterns in the process that are frequently repeated. The outcome of the case studies shows that our approach is applicable to a range of software projects. The conclusions derived from these case studies confirmed that our approach could be used to enhance the entire software development process, including tailoring and assessment.