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Authors: Philippe Dugerdil and Sebastien Jossi

Affiliation: HEG-University of Applied Sciences, Switzerland

ISBN: 978-989-8111-52-4

Keyword(s): Reverse-engineering, dynamic analysis, software architecture, empirical study.

Related Ontology Subjects/Areas/Topics: Health Engineering and Technology Applications ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Reverse Engineering

Abstract: Reverse-engineering methods using dynamic techniques rests on the post-mortem analysis of the execution trace of the programs. However, one key problem is to cope with the amount of data to process. In fact, such a file could contain hundreds of thousands of events. To cope with this data volume, we recently developed a trace segmentation technique. This lets us compute the correlation between classes and identify cluster of closely correlated classes. However, no systematic study of the quality of the clusters has been conducted so far. In this paper we present a quantitative study of the performance of our technique with respect to the chosen parameters of the method. We then highlight the need for a benchmark and present the framework for the study. Then we discuss the matching metrics and present the results we obtained on the analysis of two very large execution traces. Finally we define a clustering quality metrics to identify the parameters providing the best results.

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Paper citation in several formats:
Dugerdil P.; Jossi S. and (2008). EMPIRICAL ASSESSMENT OF EXECUTION TRACE SEGMENTATION IN REVERSE-ENGINEERING.In Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT, ISBN 978-989-8111-52-4, pages 20-27. DOI: 10.5220/0001877200200027

@conference{icsoft08,
author={Philippe Dugerdil and Sebastien Jossi},
title={EMPIRICAL ASSESSMENT OF EXECUTION TRACE SEGMENTATION IN REVERSE-ENGINEERING},
booktitle={Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT,},
year={2008},
pages={20-27},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001877200200027},
isbn={978-989-8111-52-4},
}

TY - CONF

JO - Proceedings of the Third International Conference on Software and Data Technologies - Volume 3: ICSOFT,
TI - EMPIRICAL ASSESSMENT OF EXECUTION TRACE SEGMENTATION IN REVERSE-ENGINEERING
SN - 978-989-8111-52-4
AU - Dugerdil, P.
AU - Jossi, S.
PY - 2008
SP - 20
EP - 27
DO - 10.5220/0001877200200027

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