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Traceability links can be recovered using data mined from a revision control system, such as CVS, and an issue tracking system, such as Bugzilla. Existing approaches to recover links between a bug and the methods changed to fix the bug rely on the presence of the bug's identifier in a CVS log message. In this paper we present an approach that relies instead on the presence of a patch in the issue report for the bug. That is, rather than analyzing deltas retrieved from CVS to recover links, our approach analyzes patches retrieved from Bugzilla. We use BugTrace, the tool implementing our approach, to conduct a case study in which we compare the links recovered by our approach to links recovered by manual inspection. The results of the case study support the efficacy of our approach. After describing the limitations of our case study, we conclude by reviewing closely related work and suggesting possible future work.

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This paper describes a tutorial program that serves a double role as an educational tool and a research environment. First, it introduces students to fundamental concepts of propositional logic and gives them practice with theorem proving. Secondly, the program provides an environment in which we can track student learning, explore cognitive issues of human problem solving, and investigate the possibilities of interactive human/machine learning. We have tested the tutorial program on two groups of Discrete Mathematics students and report the results of our assessment. We also discuss the contributions and future directions of our research in interactive human/machine learning.