Predicting software quality as perceived by a customer may allow an organization to adjust deployment to meet the quality expectations of its customers, to allocate the appropriate amount of maintenance resources, and to direct quality improvement efforts to maximize the return on investment. However, customer perceived quality may be affected not simply by the software content and the development process, but also by a number of other factors including deployment issues, amount of usage, software platform, and hardware configurations. We predict customer perceived quality as measured by various service interactions, including software defect reports, requests for assistance, and field technician dispatches using the afore mentioned and other factors for a large telecommunications software system. We employ the non-intrusive data gathering technique of using existing data captured in automated project monitoring and tracking systems as well as customer support and tracking systems. We find that the effects of deployment schedule, hardware configurations, and software platform can increase the probability of observing a software failure by more than 20 times. Furthermore, we find that the factors affect all quality measures in a similar fashion. Our approach can be applied at other organizations, and we suggest methods to independently validate and replicate our results.

We set out to answer a question we were asked by software project management: how much effort remains to be spent on a specific software project and how will that effort be distributed over time? To answer this question we propose a model based on the concept that each modification to software may cause repairs at some later time and investigate its theoretical properties and application to several projects in Avaya to predict and plan development resource allocation. Our model presents a novel unified framework to investigate and predict effort, schedule, and defects of a software project. The results of applying the model confirm a fundamental relationship between the new feature and defect repair changes and demonstrate its predictive properties.

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.