Companies that engage in multi-site, multi-project software development continually face the problem of how to understand and improve their software development capabilities. We have defined and applied a goal-oriented process that enables such a company to assess the strengths and weaknesses of those capabilities. Our goals are to help a) to decrease the time and cost to develop software, b)to decrease the time needed to make changes to existing software, c) to improve software quality, d) to attract and retain a talented engineering staff, and e) to facilitate more predictable management of software projects. In response to the variety of product requirements, market needs, and development environments, we selected a goal-oriented process, rather than a criteria-oriented process, to advance our strategy and ensure relevance of the results. We describe the design of the process, discuss results achieved, and present vulnerabilities of the methodology. The process includes both interviews with projects' personnel and analysis of change data. Several common issues have emerged from the assessments across multiple projects, enabling strategic investments in software technology. Teams report satisfaction with the outcome in that they act on the recommendations, ask for additional future assessments, and recommend the process to sibling organizations.

The random data perturbation (RDP) method of preserving the privacy of individual records in a statistical database is discussed. In particular, it is shown that if confidential attributes are allowed as query-defining variables, severe biases may result in responses to queries. It is also shown that even if query definition through confidential variables is not allowed, biases can still occur in responses to queries such as those involving proportions or counts. In either case, serious distortions may occur in user statistical analyses. A modified version of RDP is presented, in the form of a query adjustment procedure and specialized perturbation structure which will produce unbiased results.