Assessment of software measurement

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