This paper presents a novel methodology for localizing faults in code as it evolves. Our insight is that the essence of failure-inducing edits made by the developer can be captured using mechanical program transformations (e.g., mutation changes). Based on the insight, we present the FIFL framework, which uses both the spectrum information of edits (obtained using the existing FAULTTRACER approach) as well as the potential impacts of edits (simulated by mutation changes) to achieve more accurate fault localization. We evaluate FIFL on real-world repositories of nine Java projects ranging from 5.7KLoC to 88.8KLoC. The experimental results show that FIFL is able to outperform the stateof-the-art FAULTTRACER technique for localizing failureinducing program edits significantly. For example, all 19 FIFL strategies that use both the spectrum information and simulated impact information for each edit outperform the existing FAULTTRACER approach statistically at the significance level of 0.01. In addition, FIFL with its default settings outperforms FAULTTRACER by 2.33% to 86.26% on 16 of the 26 studied version pairs, and is only inferior than FAULTTRACER on one version pair.

Building a summary for library code is a common approach to speeding up the analysis of client code. In presence of callbacks, some reachability relationships between library nodes cannot be obtained during library-code summarization. Thus, the library code may have to be analyzed again during the analysis of the client code with the library summary. In this paper, we propose to summarize library code with tree-adjoining-language (TAL) reachability. Compared with the summary built with context-free-language (CFL) reachability, the summary built with TAL reachability further contains conditional reachability relationships. The conditional reachability relationships can lead to much lighter analysis of the library code during the client code analysis with the TAL-reachability-based library summary. We also performed an experimental comparison of context-sensitive data-dependence analysis with the TAL-reachability-based library summary and context-sensitive data-dependence analysis with the CFL-reachability-based library summary using 15 benchmark subjects. Our experimental results demonstrate that the former has an 8X speed-up over the latter on average.

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Software reuse is a promising solution to the software crisis. Reuse repositories are the basic infrastructure for software reuse. During the past decade, various academic, commercial, governmental, and industrial organizations have developed many Internet-enabled reuse repositories to provide access to software components and related resources. It has necessitated semantic interoperation to allow distributed maintenance and management of these repositories while enabling users to efficiently and conveniently access resources from multiple reuse repositories via a single representation view. In this paper, we have proposed an approach to enhancing the semantic interoperability of reuse repositories, called the improved relevancy matching and ranking (IRMR) method, based on analyzing the correlation of terms in representation methods of the repositories. A prototype system, the Virtual Repository supporting Semantic Interoperation (VRSI), is presented to illustrate the application of this approach to support the semantic interoperation of reuse repositories. Experimental results on real world reuse repositories demonstrated significant improvement in terms of searching effectiveness.