Finding, understanding, and fixing bugs in software systems is challenging. Dynamic binary translation (DBT) systems provide a powerful facility for building program analysis and debugging tools. However, DBT abstractions are too low-level and provide limited contextual information to instrumentation tools, making it hard to implement such tools.
In this theis, we introduce behavioral watchpoints, a new software-based watchpoint framework that simplifies the implementation of DBT-based program analysis and debugging tools. Behavioral watchpoints have two key features: 1) they provide contextual information at the instruction level which are directly available with watchpoints and 2) they enable specializing instruction-level instrumentation with individual data structures. We describe three applications that were easily developed using our watchpoint framework: detecting buffer overflows, detecting read-before-write and memory freeing bugs and detecting memory leaks. We implemented behavioral watchpoints using Granary, a DBT framework for instrumenting operating system kernels. We evaluated the overheads of watchpoints for analyzing and debugging operating system kernel modules and show that these overheads are reasonable.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/43861 |
| Date | 18 February 2014 |
| Creators | Akshay, Kumar |
| Contributors | Goel, Ashvin, Brown, Angela Demke |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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