Open AccessA Case for Dynamic Reverse-code Generation
Author(s) -
Jooyong Lee
Publication year - 2007
Publication title -
brics report series
Language(s) - English
Resource type - Journals
eISSN - 1601-5355
pISSN - 0909-0878
DOI - 10.7146/brics.v14i15.22179
Subject(s) - backtracking , computer science , debugger , code (set theory) , reverse engineering , parallel computing , programming language , implementation , code generation , bounded function , operating system , key (lock) , debugging , mathematics , mathematical analysis , set (abstract data type)
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. As has often been said, the ultimate solution for backtracking is to use reverse code: executing the reverse code restores the previous states of a program. In our earlier work, we presented a method to generate reverse code on the fly while running a debugger. This article presents a case study of dynamic reverse-code generation. 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 can outperform the existing backtracking methods in terms of memory efficiency.