Practical data breakpoints

Abstract

A data breakpoint associates debugging actions with programmer-specified conditions on the memory state of an executing program. Data breakpoints provide a means for discovering program bugs that are tedious or impossible to isolate using control breakpoints alone. In practice, programmers rarely use data breakpoints, because they are either unimplemented or prohibitively slow in available debugging software. In this paper, we present the design and implementation of a practical data breakpoint facility. A data breakpoint facility must monitor all memory updates performed by the program being debugged. We implemented and evaluated two complementary techniques for reducing the overhead of monitoring memory updates. First, we checked write instructions by inserting checking code directly into the program being debugged. The checks use a segmented bitmap data structure that minimizes address lookup complexity. Second, we developed data flow algorithms that eliminate checks on some classes of write instructions but may increase the complexity of the remaining checks. We evaluated these techniques on the SPARC using the SPEC benchmarks. Checking each write instruction using a segmented bitmap achieved an average overhead of 42%. This overhead is independent of the number of breakpoints in use. Data flow analysis eliminated an average of 79% of the dynamic write checks. For scientific programs such the NAS kernels, analysis reduced write checks by a factor of ten or more. On the SPARC these optimizations reduced the average overhead to 25%.