In the past years, software reverse engineering dealt with source code understanding. Nowadays, it is levered to software requirements abstract level, supported by feature model notations, language independent, and simpler than the source code reading. The recent relevant approaches face the following insufficiencies: lack of a complete integrated methodology, adapted feature model, feature patterns recognition, and Graph based slicing. This work aims to provide some solutions to the above challenges through an integrated methodology. The following results are unique. Elementary and configuration features are specified in a uniform way by introducing semantics specific attributes. The reverse engineering supports feature pattern recognition and requirements feature model graph-based slicing. The slicing criteria are rich enough to allow answering questions of software requirements maintainers. A comparison of this proposed methodology, based on effective criteria, with the similar works, seems to be valuable and competitive: the enrichment of the feature model and feature pattern recognition were never approached and the proposed slicing technique is more general, effective, and practical.
| Published in | American Journal of Software Engineering and Applications (Volume 8, Issue 1) |
| DOI | 10.11648/j.ajsea.20190801.11 |
| Page(s) | 1-7 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2019. Published by Science Publishing Group |
Requirements Engineering, Reverse Engineering, Requirements Variability, Feature Model, Pattern Recognition, Graph-Based Slicing
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APA Style
Anas Alhamwieh, Said Ghoul. (2019). A Feature Based Methodology for Variable Requirements Reverse Engineering. American Journal of Software Engineering and Applications, 8(1), 1-7. https://doi.org/10.11648/j.ajsea.20190801.11
ACS Style
Anas Alhamwieh; Said Ghoul. A Feature Based Methodology for Variable Requirements Reverse Engineering. Am. J. Softw. Eng. Appl. 2019, 8(1), 1-7. doi: 10.11648/j.ajsea.20190801.11
AMA Style
Anas Alhamwieh, Said Ghoul. A Feature Based Methodology for Variable Requirements Reverse Engineering. Am J Softw Eng Appl. 2019;8(1):1-7. doi: 10.11648/j.ajsea.20190801.11
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Download@article{10.11648/j.ajsea.20190801.11,
author = {Anas Alhamwieh and Said Ghoul},
title = {A Feature Based Methodology for Variable Requirements Reverse Engineering},
journal = {American Journal of Software Engineering and Applications},
volume = {8},
number = {1},
pages = {1-7},
doi = {10.11648/j.ajsea.20190801.11},
url = {https://doi.org/10.11648/j.ajsea.20190801.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20190801.11},
abstract = {In the past years, software reverse engineering dealt with source code understanding. Nowadays, it is levered to software requirements abstract level, supported by feature model notations, language independent, and simpler than the source code reading. The recent relevant approaches face the following insufficiencies: lack of a complete integrated methodology, adapted feature model, feature patterns recognition, and Graph based slicing. This work aims to provide some solutions to the above challenges through an integrated methodology. The following results are unique. Elementary and configuration features are specified in a uniform way by introducing semantics specific attributes. The reverse engineering supports feature pattern recognition and requirements feature model graph-based slicing. The slicing criteria are rich enough to allow answering questions of software requirements maintainers. A comparison of this proposed methodology, based on effective criteria, with the similar works, seems to be valuable and competitive: the enrichment of the feature model and feature pattern recognition were never approached and the proposed slicing technique is more general, effective, and practical.},
year = {2019}
}
TY - JOUR T1 - A Feature Based Methodology for Variable Requirements Reverse Engineering AU - Anas Alhamwieh AU - Said Ghoul Y1 - 2019/04/03 PY - 2019 N1 - https://doi.org/10.11648/j.ajsea.20190801.11 DO - 10.11648/j.ajsea.20190801.11 T2 - American Journal of Software Engineering and Applications JF - American Journal of Software Engineering and Applications JO - American Journal of Software Engineering and Applications SP - 1 EP - 7 PB - Science Publishing Group SN - 2327-249X UR - https://doi.org/10.11648/j.ajsea.20190801.11 AB - In the past years, software reverse engineering dealt with source code understanding. Nowadays, it is levered to software requirements abstract level, supported by feature model notations, language independent, and simpler than the source code reading. The recent relevant approaches face the following insufficiencies: lack of a complete integrated methodology, adapted feature model, feature patterns recognition, and Graph based slicing. This work aims to provide some solutions to the above challenges through an integrated methodology. The following results are unique. Elementary and configuration features are specified in a uniform way by introducing semantics specific attributes. The reverse engineering supports feature pattern recognition and requirements feature model graph-based slicing. The slicing criteria are rich enough to allow answering questions of software requirements maintainers. A comparison of this proposed methodology, based on effective criteria, with the similar works, seems to be valuable and competitive: the enrichment of the feature model and feature pattern recognition were never approached and the proposed slicing technique is more general, effective, and practical. VL - 8 IS - 1 ER -
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