Efficient Dynamic Checking of Heap Invariants using the Garbage Collector

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Modern software is increasingly developed using managed programming languages, such as Java and C#, because they eliminate a large class of low-level memory-related errors that have plagued languages such as C and C++ and caused countless failures and security vulnerabilities. Unfortunately, software still suffers from a troubling array of higher-level semantic errors, which can cause programs to misbehave without necessarily triggering an overt failure. Prior techniques for detecting these errors suffer from some combination of imprecision (false positives), poor scalability on large programs, or extremely high run-time overheads.This project will explore a new approach for detecting programming errors that is precise, informative, scalable, and efficient enough to use in deployed software. The approach leverages techniques from static analysis that allow programmers to express expected program properties, but overcomes prior limitations by checking the properties at run-time. The key idea is to piggyback error checking on the garbage collector, which can check and elucidate complex program properties with very low overhead because it periodically visits all objects in the heap. The result of this research will be a much-needed technique for detecting and diagnosing bugs in deployed software -- especially large, complex, and highly dynamic programs, such as server applications.