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This master’s dissertation stands as a guideline for defining a measurement program for GEEE that can be piloted at the Gothenburg site EEEG. The measurement program is based on the “CMMI process area Measurements and Analysis, Level 2”. The proposed measurement program is designed in such a way that is applicable for repeatable process measurement with potential minor alters depending on the nature of the process being examined. Major effort has been made on creating a program that not only collects the numerical data but also delivers substantial results in terms of goal setting, data analysis and decision making. Designing a process for measurement facilitate organizational strategy toward process improvements. This measurement program is designed with the help of some well-known methods such as: GQM (Goal-Question-Metric), PDCA (Plan-Do-Check-Act) and ETVX (Entry-Task-Validation- Exit) where five major phases are resulted, namely; Identify, Define, Collect data, Analysis, Evolve, thereafter embedded in a template-shaped tool. The whole template, after a complete fulfillment, would provide the organization with a guideline to achieve the organizational objectives. It is vital to mention that this template itself does not improve the processes. It only shows the status of the chosen project/process after having the filled template executed. What this template generates is to provide the stakeholders with necessary information and basis to make informed decision afterwards in order to improve the chosen processes/projects. Since the processes in “Maturity Level 2 of CMMI” are project based, it is important the status of processes can be measured and communicated. This procedure plays a crucial role in creating a platform for moving to the next maturity level.

This thesis comprises an investigation in order to find possibilities to implement the method used in the automotive industry to automatically generate a collision free measurement program within the aircraft components manufacturer. The purpose with the study was to compare and analyse the different methods used to generate measurement programs at GKN Aerospace Engine Systems in Trollhättan, National Electric Vehicle Sweden (NEVS) and Volvo Cars Corporations (VCC).The study was conducted through meetings, observations and questionnaires with staff from the geometry assurance engineering (GAE) departments and measurement departments in each company. By mapping the virtual GAE process started from concept development in CAD to the measurement phase in which components are measured in coordinated measuring machines (CMM), a chain of activities was analysed.NEVS and VCC are today using RD&T and IPS to generate optimized CMM programs in which a time efficient measurement path can be generated. This method was compared with the current approach at GKN Aerospace where they use one supplier for offline CMM programming (OLP) software solutions and CMMs. They are thereby working in a closed system where the OLP communicates with the CMM by supplier specific methods. The automobile manufacturer NEVS and VCC, in contrast, uses a DMIS protocol which is an ISO and ANSI standard.The study shows that an implementation of the software used by the Swedish automobile manufacture NEVS and VCC at GKN Aerospace in Trollhättan, may not have any significant improvements regarding time savings and thereby no economic benefits. However, the approach for generating an optimized measurement program in RD&T and IPS may have major improvements in other facilities within the aerospace industry which has also resulted in an instruction manual to be used for potential implementation.

Context. Most organizations are aware of the significance of software measurement programs to help organizations assess and improve the ways they develop software. Measurement plays a vital role in improving software process and products. However, the number of failing measurement programs is high and the reasons are vary. A recent approach for planning measurement programs is GQM+Strategies, which makes an important extension to existing approaches, it links measurements and improvement activities to strategic goals and ways to achieve this goals. However, concrete guides of how to collect the information needed to use GQM+strategies is not provided in the literature yet. Objectives. The contribution of this research is to propose and assess an elicitation approach (The Goal Strategy Elicitation (GSE) approach) for the information needed to apply GQM+strategies in an organization, which also leads to a partial evaluation of GQM+strategies as such. In this thesis, the initial focus is placed on eliciting the goals and strategies in the most efficient way. Methods. The primary research approach used is action research, which allows to flexibly assess a new method or technique in an iterative manner, where the feedback of one iteration is taken into the next iteration, thus improving on the method or technique proposed. Complementary to that, we used literature review with the primary focus to position the work, explore GQM+strategies, and to determine which elicitation approach for the support of measurement programs have been proposed. Results. The Goal Strategy Elicitation (GSE) approach as a tool for eliciting goals and strategies within the software organization to contribute in planning a measurement program has been developed. The iterations showed that the approach of elicitation may not be too structured (e.g. template/notation based), but rather shall support the stakeholders to express their thoughts relatively freely. Hence, the end-result was an interview guide, not based on notations (as in the first iteration), and asking questions in a way that the interviewees are able to express themselves easily without having to e.g. distinguish definitions for goals and strategies. Conclusions. We conclude that the GSE approach is a strong tool for the software organization to be able to elicit the goals and strategies to support GQM+Strategies. GSE approach evolved in each iteration and the latest iteration together with the guideline is still used within the studied company for eliciting goals and strategies, and the organization acknowledged that they will continue to do so. Moreover, we conclude that there is a need for further empirical validation of the GSE approach in further full-scale industry trials.

Background and purpose. This thesis documents a program of five studies concerned with the assessment of software measurement. The goal of this program is to assist the software industry to improve the information support for managers, analysts and software engineers by providing evidence of where opportunities for improving measurement and analysis exist. Methods. The first study examined the assessment of software measurement frameworks using models of best practice based on performance/success factors. The software measurement frameworks of thirteen organisations were surveyed. The association between a factor and the outcome experienced with the organisations' frameworks was then evaluated. The subsequent studies were more info-centric and investigated using models of information quality to assess the support provided for software processes. For these studies, information quality models targeting specific software processes were developed using practitioner focus groups. The models were instantiated in survey instruments and the responses were analysed to identify opportunities to improve the information support provided. The final study compared the use of two different information quality models for the assessing and improving information support. Assessments of the same quantum of information were made using a targeted model and a generic model. The assessments were then evaluated by an expert panel in order to identify which information quality model was more effective for improvement purposes. Results. The study of performance factors for software measurement frameworks confirmed the association of some factors with success and quantified that association. In particular, it demonstrated the importance of evaluating contextual factors. The conclusion is that factor-based models may be appropriately used for risk analysis and for identifying constraints on measurement performance. Note, however, that a follow-up study showed that some initially successful frameworks subsequently failed. This implied an instability in the dependent variable, success, that could reduce the value of factor-based models for predicting success. The studies of targeted information quality models demonstrated the effectiveness of targeted assessments for identifying improvement opportunities and suggest that they are likely to be more effective for improvement purposes than using generic information quality models. The studies also showed the effectiveness of importance-performance analysis for prioritizing improvement opportunities.