_________________________________________________________________________________________Those science, mathematics, and engineering faculty who are serious about making the education they offer as available to their daughters as to their sons are, we posit, facing the prospect of dismantling a large part of its traditional pedagogical structure, along with the assumptions and practice which support it. [Seymour and Hewett 1997].Prior research indicates that female students can be concerned about the insularity of working alone for long periods of time, as they perceive to be the case with computer science and information technology careers. We studied an advanced undergraduate software engineering course at North Carolina State University to characterize the potential of collaborative learning environments created via pair-programming and agile software development to ameliorate this concern. A collective case study of three representative women in the course revealed that they held the following four themes in common: working with others; productivity; confidence; and interest in IT careers. Three conjectures concerning collaboration emerged from our study, including the importance of face-to-face meetings, an increased confidence among women based on product quality, and a reduction in the amount of time spent on assignments. While our findings are not generalized to early undergraduate courses, the young women we studied were at a critical junction in deciding whether to pursue a career in IT upon their near-term graduation. Additionally, we propose a model for future testing with both males and females that connects these three factors with an increased interest in IT careers.

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Performance is an important attribute of a software system. To develop a software system of acceptable performance, the team needs to specify precise performance requirements, design appropriate test cases, and use suitable techniques to analyze the performance characteristics. However, the lack of a structured framework for performance engineering may impair the effectiveness of the techniques. We propose the Performance Refinement and Evolution Model (PREM) as a performance management framework. Based on the specification of quantitative measurement and workloads, PREM classifies performance requirements specification, analysis activities, and testing into four levels. In this paper, we provide an overview of this model.

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