Comprehensive Evaluation of Association Measures for Fault Localization

To cite the data package, please use the following citation: Lucia, Lo, D., Lingxiao, J., & Budi, A. (2010). Data from: Comprehensive evaluation of association measures for fault localization. InK Repository at Singapore Management University. http://ink.library.smu.edu.sg/sis_research/1330</p

Version history, similar report, and structure: Putting them together for improved bug localization

During the evolution of a software system, a large number of bug reports are submitted. Locating the source code files that need to be fixed to resolve the bugs is a challenging problem. Thus, there is a need for a technique that can automatically figure out these buggy files. A number of bug localization solutions that take in a bug report and output a ranked list of files sorted based on their likelihood to be buggy have been proposed in the literature. However, the accuracy of these tools still need to be improved. In this paper, to address this need, we propose AmaLgam, a new method for locating relevant buggy files that puts together version history, similar reports, and structure. To do this, AmaLgam integrates a bug prediction technique used in Google which analyzes version history, with a bug localization technique named BugLocator which analyzes similar reports from bug report system, and the state-of-the-art bug localization technique BLUiR which considers structure. We perform a large-scale experiment on four open source projects, namely AspectJ, Eclipse, SWT and ZXing to localize more than 3,000 bugs. Compared with a history-aware bug localization solution of Sisman and Kak, our approach achieves a 46.1 % improvement in terms of mean average precision (MAP). Compared with BugLocator, our approach achieves a 24.4 % improvement in terms of MAP. Compared with BLUiR, our approach achieves a 16.4% improvement in terms of MAP

Extended Comprehensive Study of Association Measures for Fault Localization

To cite the data package, please use the following citation: Lucia, L., Lo, D., Jiang, L., Thung, F., & Budi, A. (2014). Data from: Extended Comprehensive Study of Association Measures for Fault Localization. InK Repository at Singapore Management University. http://ink.library.smu.edu.sg/sis_research/1818</p

Debugging multi-agent systems with design documents

Debugging multi-agent systems, which are concurrent, distributed, and consist of complex components is difficult, yet crucial. The development of these complex systems is supported by agent-oriented software engineering methodologies which utilise agents as the central design metaphor. The systems that are developed are inherently complex since the components of these systems may interact in flexible and sophisticated ways and traditional debugging techniques are not appropriate. Despite this, very little effort has been applied to developing appropriate debugging tools and techniques. Debugging multi-agent systems without good debugging tools is highly impractical and without suitable debugging support developing and maintaining multi-agent systems will be more difficult than it need be. In this thesis we propose that the debugging process can be supported by following an agent-oriented design methodology, and then using the developed design artifacts in the debugging phase. We propose a domain independent debugging framework which comprises the developed processes and components that are necessary in using design artifacts as debugging artifacts. Our approach is to take a non-formal design artifact, such as an AUML protocol design, and encode it in a machine interpretable manner such that the design can be used as a model of correct system behaviour. These models are used by a run-time debugging system to compare observed behaviour against specified behaviour. We provide details for transforming two design artifact types into equivalent debugging artifacts and show how these can be used to detect bugs. During a debugging episode in which a bug has been identified our debugging approach can provide detailed information about the possible reason for the bug occurring. To determine if this information was useful in helping to debug programs we undertook a thorough empirical study and identified that use of the debugging tool translated to an improvement in debugging performance. We conclude that the debugging techniques developed in this thesis provide effective debugging support for multi-agent systems and by having an extensible framework new design artifacts can be explored and as translations are developed they can be added to the debugging system