Article

Using Compressed Bytecode Traces for Slicing Java Programs

Authors:

Abhik RoychoudhuryAuthors Info & Claims

ICSE '04: Proceedings of the 26th International Conference on Software Engineering

Pages 512 - 521

Published: 23 May 2004 Publication History

Abstract

Dynamic slicing is a well-known program debuggingtechnique. Given a program P and input I, it finds all programstatements which directly/indirectly affect the valuesof some variablesý occurrences when P is executed with I.Dynamic slicing algorithms often proceed by traversing theexecution trace of P produced by input I (or a dependencegraph which captures control/data flow in the executiontrace). Consequently, it is important to develop space efficient representations of the execution trace.In this paper, we use results from data compression tocompactly represent bytecode traces of sequential Java programs.The major space savings come from the optimizedrepresentation of data (instruction) addresses used by memoryreference (branch) bytecodes as operands. We give detailedexperimental results on the space efficiency and timeoverheads for our compact trace representation. We thenshow how dynamic slicing algorithms can directly traverseour compact traces without resorting to costly decompression.We also develop an extension of dynamic slicing whichallows us to explain omission errors (i.e. why some eventsdid not happen during program execution).

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Cited By

Reis SAbreu RD'Amorim M(2019)Demystifying the combination of dynamic slicing and spectrum-based fault localizationProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367471.3367705(4760-4766)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367471.3367705
Feyzi FParsa S(2018)A program slicing-based method for effective detection of coincidentally correct test casesComputing10.1007/s00607-018-0591-z100:9(927-969)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s00607-018-0591-z
(2017)Hierarchical regression test case selection using slicingInternational Journal of Computational Science and Engineering10.1504/IJCSE.2017.08288214:2(179-197)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJCSE.2017.082882
Show More Cited By

Index Terms

Using Compressed Bytecode Traces for Slicing Java Programs
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Process validation
        Traceability
      2. Software defect analysis
        Software testing and debugging
  2. Software notations and tools
    1. General programming languages
      1. Language types

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Published In

cover image ACM Conferences

ICSE '04: Proceedings of the 26th International Conference on Software Engineering

May 2004

761 pages

ISBN:0769521630

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

IEEE Computer Society

United States

Publication History

Published: 23 May 2004

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Conference

ICSE04

Sponsor:

SIGSOFT

ICSE04: 26th International Conference on Software Engineering

May 23 - 28, 2004

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ICSE '04 Paper Acceptance Rate 58 of 436 submissions, 13%;

Overall Acceptance Rate 276 of 1,856 submissions, 15%

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2025 IEEE/ACM 46th International Conference on Software Engineering

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Cited By

Reis SAbreu RD'Amorim M(2019)Demystifying the combination of dynamic slicing and spectrum-based fault localizationProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367471.3367705(4760-4766)Online publication date: 10-Aug-2019
https://dl.acm.org/doi/10.5555/3367471.3367705
Feyzi FParsa S(2018)A program slicing-based method for effective detection of coincidentally correct test casesComputing10.1007/s00607-018-0591-z100:9(927-969)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s00607-018-0591-z
(2017)Hierarchical regression test case selection using slicingInternational Journal of Computational Science and Engineering10.1504/IJCSE.2017.08288214:2(179-197)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1504/IJCSE.2017.082882
Palepu VXu GJones J(2017)Dynamic Dependence SummariesACM Transactions on Software Engineering and Methodology10.1145/296844425:4(1-41)Online publication date: 9-Jan-2017
https://dl.acm.org/doi/10.1145/2968444
Böhme MOliveira BRoychoudhury ANotkin DCheng BPohl K(2013)Partition-based regression verificationProceedings of the 2013 International Conference on Software Engineering10.5555/2486788.2486829(302-311)Online publication date: 18-May-2013
https://dl.acm.org/doi/10.5555/2486788.2486829
Androutsopoulos KClark DHarman MKrinke JTratt L(2013)State-based model slicingACM Computing Surveys10.1145/2501654.250166745:4(1-36)Online publication date: 30-Aug-2013
https://dl.acm.org/doi/10.1145/2501654.2501667
Palepu VXu GJones JDenney EBultan TZeller A(2013)Improving efficiency of dynamic analysis with dynamic dependence summariesProceedings of the 28th IEEE/ACM International Conference on Automated Software Engineering10.1109/ASE.2013.6693066(59-69)Online publication date: 11-Nov-2013
https://dl.acm.org/doi/10.1109/ASE.2013.6693066
Qi DRoychoudhury ALiang ZVaswani K(2012)DARWINACM Transactions on Software Engineering and Methodology10.1145/2211616.221162221:3(1-29)Online publication date: 3-Jul-2012
https://dl.acm.org/doi/10.1145/2211616.2211622
Ko AMyers B(2010)Extracting and answering why and why not questions about Java program outputACM Transactions on Software Engineering and Methodology10.1145/1824760.182476120:2(1-36)Online publication date: 8-Sep-2010
https://dl.acm.org/doi/10.1145/1824760.1824761
Zhang CYan DZhao JChen YYang SKramer JBishop JDevanbu PUchitel S(2010)BPGenProceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 210.1145/1810295.1810351(271-274)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.1145/1810295.1810351
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