Bugs are a well known Achilles' heel of software development. In the last few years, machine learning techniques to combat software bugs have become popular. However, results of these techniques are not good enough for practical adoption. In addition, most techniques do not provide reasons for why a code change is a bug.

Furthermore, suggestions to fix the bug would be greatly beneficial. An added bonus would be engaging humans to improve the bug and fix prediction process.

In this dissertation, a step-by-step procedure which effectively predicts buggy code changes (Bug Prognosticator), produces bug fix suggestions (Fix Suggester), and utilizes human feedback is presented. Each of these steps can be used independently, but combining them allows more effective management of bugs. These techniques are tested on many open source and a large commercial project. Human feedback was used to understand and improve the performance of the techniques. Feedback was primarily gathered from industry participants in order to assess practical suitability.

The Bug Prognosticator explores feature selection techniques and classifiers to improve results of code change bug prediction. The optimized Bug Prognosticator is able to achieve an average 97% precision and 70% recall when evaluated on eleven projects, ten open source and one commercial.

The Fix Suggester uses the Bug Prognosticator and statistical analysis of keyword term frequencies to suggest unordered fix keywords to a code change predicted to be buggy. The suggestions are validated against actual bug fixes to confirm their utility. The Fix Suggester is able to achieve 46.9% precision and 38.9% recall on its predicted fix tokens. This is a reasonable start to the difficult problem of predicting the contents of a bug fix.

To improve the efficiency of the Bug Prognosticator and the Fix Suggester, active learning is employed on willing human participants. Developers aid the Bug Prognosticator and the Fix Suggester on code changes that machines find hard to evaluate. The developer's feedback is used to enhance the performance of the Bug Prognosticator and the Fix Suggester. In addition, a user study is performed to gauge the utility of the Fix Suggester.

The dissertation concludes with a discussion of future work and challenges faced by the techniques. Given the success of statistical defect prediction techniques, more industrial exposure would benefit researchers and software practitioners.

Emerging software development environments are characterized by heterogeneity: they are composed of diverse object stores, user interfaces, and tools. This paper presents an approach for providing hypertext services in this heterogenous setting. Central notions of the approach include the following. Anchors are established with respect to interactive views of objects, rather than as attributes of objects. Composable, n-ary links can be established between anchors maintained by different viewers for objects stored in distinct object bases. Viewers (and objects) may be implemented in different programming languages, as a client-server architecture can be used to support the approach. Multiple, concurrently active viewers can be utilized. The paper describes the approach and considers how interfaces to these hypertext services can be supported. Experience with a prototype implementation is described.

While the World-Wide-Web is demonstrably useful for a wide variety of tasks, in its current form it is not capable of supporting wide-area software development activities. This report describes the following areas for improvement and indicates key directions and approaches for their achievement:

• Support for first-class links, thereby enabling end-user annotation and evolutionary development of relationships within the environment;

• Support for a mechanism by which clients can receive asynchronous notifications of resource changes, which is necessary to support the complex interactions found in software engineering;

• Support for equal access to hypermedia services for client-side viewer applications, thereby facilitating the integration of non-HTML data formats found in software engineering;

• Support for distributed authoring and version control, which is necessary for developers to work within a shared information space;

• Support for flexible control and coordination mechanisms, enabling cooperative software development processes and workflow over the Web.