A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs

A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs

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Backtracking (i.e., reverse execution) helps the user of a debugger to naturally think backwards along the execution path of a program, and thinking backwards makes it easy to locate the origin of a bug.

So far backtracking has been implemented mostly by state saving or by checkpointing.These implementations, however, inherently do not scale.Meanwhile, a more recent backtracking method based on reverse-code generation seems promising because executing reverse code can restore the previous states of a program without state saving.

In the literature, there can be found two methods that generate reverse code: (a) static michael harris sunglasses reverse-code generation that pre-generates reverse code through static analysis before starting a debugging session, and (b) dynamic reverse-code generation that generates reverse code by applying dynamic analysis on the fly during a debugging session.In particular, we espoused the latter one in our previous work to accommodate non-determinism of a program caused by e.g.

, multi-threading.To demonstrate the usefulness of our dynamic reverse-code generation, this article presents a case study of various backtracking methods including ours.We compare the memory usage of various backtracking methods in a simple but nontrivial example, a bounded-buffer program.

In the case of non-deterministic programs such as this bounded-buffer program, our dynamic reverse-code generation outperforms orange zinger tomato the existing backtracking methods in terms of memory efficiency.