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This paper presents a novel approach to bug-finding analysis and an implementation of that approach. Our goal is to find as many serious bugs as possible. To do so, we designed a flexible, easy-to-use extension language for specifying analyses and an efflcent algorithm for executing these extensions. The language, metal, allows the users of our system to specify a broad class of analyses in terms that resemble the intuitive description of the rules that they check. The system, xgcc, executes these analyses efficiently using a context-sensitive, interprocedural analysis.Our prior work has shown that the approach described in this paper is effective: it has successfully found thousands of bugs in real systems code. This paper describes the underlying system used to achieve these results. We believe that our system is an effective framework for deploying new bug-finding analyses quickly and easily.

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This paper presents a novel approach to bug-finding analysis and an implementation of that approach. Our goal is to find as many serious bugs as possible. To do so, we designed a flexible, easy-to-use extension language for specifying analyses and an efflcent algorithm for executing these extensions. The language, metal, allows the users of our system to specify a broad class of analyses in terms that resemble the intuitive description of the rules that they check. The system, xgcc, executes these analyses efficiently using a context-sensitive, interprocedural analysis.Our prior work has shown that the approach described in this paper is effective: it has successfully found thousands of bugs in real systems code. This paper describes the underlying system used to achieve these results. We believe that our system is an effective framework for deploying new bug-finding analyses quickly and easily.