Dynamic Heap Type Inference for Program Understanding and Debugging

This research was conducted by Marina Polishchuk, Ben Liblit, and Chloë Schulze. The paper is to be published as a short paper in the 34th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL 2007).

Abstract

C programs can be difficult to debug due to lax type enforcement and low-level access to memory. We present a dynamic analysis for C that checks heap snapshots for consistency with program types. Our approach builds on ideas from physical subtyping and conservative garbage collection. We infer a program-defined type for each allocated storage location or identify “untypable” blocks that reveal heap corruption or type safety violations. The analysis exploits symbolic debug information if present, but requires no annotation or recompilation beyond a list of defined program types and allocated heap blocks. We have integrated our analysis into the GNU Debugger (gdb), and describe our initial experience using this tool with several small to medium-sized programs.

Full paper

The full paper is available as a single PDF document. A suggested BibTeX citation record is also available.