Software measurement process is a significant part of process improvement in software organizations. The organizations usually follow a measurement process that includes measures selection, data collection, and analysis to improve their processes. Most of the software organizations face difficulties in deciding the measures to collect since there is no universal set of measures for all types of organizations and projects. Experience shows that measurement can be more successful if the measures are collected based on the goals of the organization or the project which it will serve. A few methodologies exist to aid the software organizations. Goal Question Metric (GQM) is one of the most widely known and used one. However, one of the major constraints for the organizations is the associated cost when collecting the measures. Therefore, software organizations also require selecting the optimum set of measures which are good enough for the organization. This thesis study aims to provide solution for this problem. We propose a model, named ‗Optimum Measure Set Decision Model (OMSD)‘, which is an extension of GQM paradigm. The model is based on a heuristics approach, which aims to provide the optimum set of measures from a large number of possible measures. To develop the model, we identified the factors which are significant in selecting the optimum set of measures based on the literature survey results. Then, we evaluated those factors by conducting an empirical study. As the empirical research strategy, we used traditional fixed non-experimental design strategy. We performed a survey by distributing a structured questionnaire in order to evaluate the important factors we identified when selecting the optimum number of measures to be collected in an organization. We evaluated the heuristics rules by means of some sample cases we created. Moreover, we provided an idea for an alternative solution to optimize the number of measures to be collected for the future research. / Software measurement process is a significant part of process improvement in software organizations. The organizations usually follow a measurement process that includes measures selection, data collection, and analysis to improve their processes. Most of the software organizations face difficulties in deciding the measures to collect since there is no universal set of measures for all types of organizations and projects. Experience shows that measurement can be more successful if the measures are collected based on the goals of the organization or the project which it will serve. A few methodologies exist to aid the software organizations. Goal Question Metric (GQM) is one of the most widely known and used one. However, one of the major constraints for the organizations is the associated cost when collecting the measures. Therefore, software organizations also require selecting the optimum set of measures which are good enough for the organization. This thesis study aims to provide solution for this problem. We propose a model, named ‗Optimum Measure Set Decision Model (OMSD)‘, which is an extension of GQM paradigm. The model is based on a heuristics approach, which aims to provide the optimum set of measures from a large number of possible measures. To develop the model, we identified the factors which are significant in selecting the optimum set of measures based on the literature survey results. Then, we evaluated those factors by conducting an empirical study. As the empirical research strategy, we used traditional fixed non-experimental design strategy. We performed a survey by distributing a structured questionnaire in order to evaluate the important factors we identified when selecting the optimum number of measures to be collected in an organization. We evaluated the heuristics rules by means of some sample cases we created. Moreover, we provided an idea for an alternative solution to optimize the number of measures to be collected for the future research. / Cell# 0046-762640583, 0046-762509253

Software organizations have been initiating measurement programs as part of their software process improvement practices which in turn increase the quality of the software products. However, high numbers of organizations reported their measurement programs as failures. One of the major difficulties they faced was stated to be the difficulty in deciding which set of measures to collect for different software entities; products, processes, and resources. In addition to what should be collected, organizations would like to collect as minimum number of measures as possible in order to be cost effective. Different goal based measures selection models have been introduced to aid in these, namely Goal Question Metric (GQM) is one of the most well known and adopted ones by software organizations. It facilitates measurement programs to define goals and then collect measures according to goals. However, the current approaches require being more structured and integrated to enable an effective software measurement process. ‘Structured’ means the goals, questions and measures as well as their vertical and horizontal relations are well-defined. A structured measurement process can be ‘integrated’ to the organization via establishing links between business and organizational goals and the measurement process. The whole process becomes more ‘effective’ as these goals and measures become traceable, and hence the mechanisms to prioritize and select the optimum set of measures could be established. In this research work our main focus is to evaluate goal based models and to develop a framework for a more effective measurement process, called Structured Optimized Measurement Selection (SOMS). As part of SOMS, alternative ways for goals prioritization and measures optimization are proposed. In order to make the whole process more efficient, a tool is developed as well. Both SOMS with different alternative prioritization and optimization techniques as well as the tool were evaluated by conducting case studies in a CMMI level 3 software development organization and the results are compared to a previous case study conducted on the same case by using other techniques which are extensions of GQM, i.e. namely Structured Prioritized Goals Questions Metrics (SPGQM) and Optimum Measures Set Decision (OMSD).