Bugs in software are costly and difficult to find and fix. In recent years, many tools and techniques have been developed for automatically finding bugs by analyzing source code or intermediate code statically (at compile time). Different tools and techniques have different tradeoffs, but the practical impact of these tradeoffs is not well understood. In this paper, we apply five bug finding tools, specifically Bandera, ESC/Java 2, FindBugs, JLint, and PMD, to a variety of Java programs. By using a variety of tools, we are able to cross-check their bug reports and warnings. Our experimental results show that none of the tools strictly subsumes another, and indeed the tools often find non-overlapping bugs. We discuss the techniques each of the tools is based on, and we suggest how particular techniques affect the output of the tools. Finally, we propose a meta-tool that combines the output of the tools together, looking for particular lines of code, methods, and classes that many tools warn about.

Abstract. Parallel programs are increasingly being written using programming frameworks and other environments that allow parallel constructs to be programmed with greater ease. The data structures used allow the modeling of complex mathematical structures like linear systems and partial differential equations using high-level programming abstractions. While this allows programmers to model complex systems in a more intuitive way, it also makes the debugging and profiling of these systems more difficult due to the complexity of mapping these high level abstractions down to the low level parallel programming constructs. This work discusses mapping mechanisms, called variable blame, for creating these mappings and using them to assist in the profiling and debugging of programs created using advanced parallel programming techniques. We also include an example of a prototype implementation of the system profiling three programs.

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