CFP last date
20 March 2026
Call for Paper
April Edition
IJCA solicits high quality original research papers for the upcoming April edition of the journal. The last date of research paper submission is 20 March 2026

Submit your paper
Know more
The week's pick
Responsive image
Explainable Hybrid Deep Learning for Automated Diagnosis of Canine Mammary Tumors

Elham Shawky Salama Heba Askr Ashraf Darwish Aboul Ella Hassanien
Random Articles
Reseach Article

Chinwe Reverse Software Engineering Model: A Case Study of Electronic Bookshop System

by Ndigwe C.F., Okeke O.C.
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 83
Year of Publication: 2026
Authors: Ndigwe C.F., Okeke O.C.
10.5120/ijca2026926454

Ndigwe C.F., Okeke O.C. . Chinwe Reverse Software Engineering Model: A Case Study of Electronic Bookshop System. International Journal of Computer Applications. 187, 83 ( Feb 2026), 16-24. DOI=10.5120/ijca2026926454

@article{ 10.5120/ijca2026926454,
author = { Ndigwe C.F., Okeke O.C. },
title = { Chinwe Reverse Software Engineering Model: A Case Study of Electronic Bookshop System },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2026 },
volume = { 187 },
number = { 83 },
month = { Feb },
year = { 2026 },
issn = { 0975-8887 },
pages = { 16-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number83/chinwe-reverse-software-engineering-model-a-case-study-of-electronic-bookshop-system/ },
doi = { 10.5120/ijca2026926454 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-02-21T01:28:14.219460+05:30
%A Ndigwe C.F.
%A Okeke O.C.
%T Chinwe Reverse Software Engineering Model: A Case Study of Electronic Bookshop System
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 83
%P 16-24
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Chinwe Reverse Software Engineering (CRSE) model for Legacy Software was developed to enable software engineers to build application by reverse engineering legacy application using the best features of the classical system with contemporary advanced technology. This will enable the reverse engineered system to adapt to modern environment while preserving the good features of the legacy application. In this paper a use case is presented for use to testing the CRSE model and presenting the detail design of the system in illustration of how the model can be used in real life software engineering development. This will serve as a guide to academics and developers on the deployment of the model in other use cases and projects. The Use case used is an Electronic Bookshop System with a legacy Java application that work offline but is reverse engineered to work online. The result of the design show a successful decompilation and refactoring of the system illustrating the veracity of the CRSE process model in reverse engineering of legacy software.

References
  1. Ndigwe C. F. and Okeke O. C (2025) Dual-Step Phase Reverse Software Engineering Model for Legacy Software System, International Journal of Computer Applications (0975 – 8887) 187 (61).
  2. EelcoVisser. (2023). Why decompilation. http://www.program-transformation. org/Transform/WhyDecompilation
  3. Wei-Cheng W., Yutian Y., Hallgrimur D. E., David P., Steven C., Christophe H. and Weihang W. (2024) Is This the Same Code? A Comprehensive Study of Decompilation Techniques for WebAssembly Binaries, SecureComm 2024, Dubai, United Arab Emirates
  4. Xu X., Zhuo Z., Shiwei F., Yapeng Y., Zian S., Nan J., Siyuan C., Lin T., and Xiangyu Z..( 2023). Lmpa: Improving decompilation by synergy of large language model and program analysis. CoRR, abs/2306.02546.
  5. Feng, Y.; Li, B.; Shi, X.; Zhu, Q.; Che, W. (2025) Interactive End-to-End Decompilation via Large Language Models. Electronics 2025, 14, 4442. https://doi.org/10.3390/ electronics14224442
  6. Tan, H.; Luo, Q.; Li, J.; Zhang, Y. (2024) LLM4 Decompile: Decompiling Binary Code with Large Language Models. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, Miami, FL, USA, 12–16 November 2024; pp. 3473–3487.
  7. Wong, W.K.; Wang, H.; Li, Z.; Liu, Z.; Wang, S.; Tang, Q.; Nie, S.; Wu, S. (2023) Refining Decompiled C Code with Large Language Models. arXiv 2023, arXiv:2310.06530.
  8. Feng, Y.; Teng, D.; Xu, Y.; Mu, H.; Xu, X.; Qin, L.; Zhu, Q.; Che, W. (2024) Self-Constructed Context Decompilation with Fined-grained Alignment Enhancement. In Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, Miami, FL, USA, 12–16 November 2024; pp. 6603–6614.
  9. Krysa J. and Sedek G (2008) Source Code, doi:10.7551/mitpress/9780262062749.003.0034
  10. Eric V. W. (2023) Context in Parsing: Techniques and Applications, Commemorative Symposium (EVCS 2023). Article No. 30; pp. 30:1–30:10 OpenAccess Series in Informatics, Germany
  11. Radoslav K. and Gennady A. (2010 ) Source Code Analysis – An Overview, Bulgarian Academy of Sciences Journal of Cybernetics And Information Technologies 10(2) 60-77, Bulgaria.
  12. Azanzi J., Gaoussou C. and Maurice T. (2019) Extracting ontological knowledge from Java source code using Hidden Markov Models Open Computer Science 9(1), 181-199, De Gruyte. DOI: 10.1515/comp-2019-0013
  13. Suárez-Figueroa M. C., Gómez-Pérez A. and Fernández- López M. (2015) The NeOn Methodology framework: A scenario-based methodology for ontology development, Applied Ontology, 2015, 10(2),
  14. Kun Q., Anton B., Fei W., Samira K., Azadeh N., Rahul K., Yisi S., Katherine L., Xianqi C., Eric C., Yash G., Chloe S., Yiwen S., Ahmed F., Theo R., Ihab I., Xiaoguang Q. and Yunyao L. (2023) Open Domain Knowledge Extraction for Knowledge Graphs,
  15. Surafel L. A. and Paolo T. (2015) Extraction of domain concepts from the source code, Science of Computer Programming, 98(4) 680-706, Elsevie
  16. Eman A. A., Mohamed W. M. and Ali O. (2023) Automating Source Code Refactoring in the Classroom, In Proceedings of ACM Conference. ACM, New York, NY, USA. https: //doi.org/10.1145/nnnnnnn.nnnnnnn
  17. Fowler M., Kent B., Brant J, William O., and Roberts D. (1999). Refactoring: Improving the Design of Existing Code. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA. http://dl.acm.org/citation.cfm?id=311424
  18. Eman A. A., Mohamed W. M., Christian N. and Ali O. (2021). On preserving the behavior in software refactoring: A systematic mapping study. Information and Software Technology (2021), 106675
  19. Satrio A. R., Lina O. and Michel R.V. C. (2024) Deductive Software Architecture Recovery via Chain-of- thought Prompting, IEEE/ACM 46th International Conference on Software Engineering: New Ideas and Emerging Results (ICSENIER)
  20. Link D., Pooyan B., Ramin M., and Boehm B. (2019). The Value of Software Architecture Recovery for Maintenance. In Proceedings of the 12th Innovations on Software Engineering Conference (Formerly Known as India Software Engineering Conference). Association for Computing Machinery, New York, Article 17, 10 pages. https://doi.org/10.1145/3299771.3299787
  21. Hamed J., Mohammad M. and Roozbeh R. (2025) Large Language Models (LLMs) for Source Code Analysis: applications, models and datasets, arXiv:2503.17502v1 [cs.SE] 21 Mar 2025., Woodstock, NY
  22. Shahla R., Mansour E., Abdolreza H., and Sepideh A. (2024) A Blockchain Approach to Extract Design Patterns From Source Codes, Wiley Modelling and Simulation in Engineering Volume 2024, Article ID 4992169, 15 pages https://doi.org/10.1155/2024/4992169
  23. Franzoni, V.; Tagliente, S.; Milani, A. (2024) Generative Models for Source Code: Fine-Tuning Techniques for Structured Pattern Learning. Technologies 2024, 12, 219.
  24. Youjia L. , Jianjun S., and Zheng Z. (2024) An Approach for Rapid Source Code Development Based on ChatGPT and Prompt Engineering, IEEE Access 12 53074 – 53087.
  25. Ahmad H., Christoph K., and Andreas R. (2025) Generating Software Architecture Description from Source Code using Reverse Engineering and Large Language Model, https://arxiv.org/abs/2511.05165v1
Index Terms

Computer Science
Information Sciences

Keywords

CSRE Model Code Refactoring legacy software Use Case Desig Class UML Design

Powered by PhDFocusTM