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

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 imple...

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Main Author: Jooyong Yi
Format: Article
Language:English
Published: Open Publishing Association 2013-09-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1309.5152v1
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spelling doaj-012f3f66842545178aa155945cf835dd2020-11-25T00:57:25ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802013-09-01129Festschrift for Dave Schmidt41942810.4204/EPTCS.129.27A Case for Dynamic Reverse-code Generation to Debug Non-deterministic ProgramsJooyong YiBacktracking (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 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 the existing backtracking methods in terms of memory efficiency. http://arxiv.org/pdf/1309.5152v1
collection DOAJ
language English
format Article
sources DOAJ
author Jooyong Yi
spellingShingle Jooyong Yi
A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
Electronic Proceedings in Theoretical Computer Science
author_facet Jooyong Yi
author_sort Jooyong Yi
title A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
title_short A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
title_full A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
title_fullStr A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
title_full_unstemmed A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
title_sort case for dynamic reverse-code generation to debug non-deterministic programs
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2013-09-01
description 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 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 the existing backtracking methods in terms of memory efficiency.
url http://arxiv.org/pdf/1309.5152v1
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