Introduction to the theory of neural computation
Introduction to the theory of neural computation
Communications of the ACM
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Hybrid Feedforward Neural Networks for Solving Classification Problems
Neural Processing Letters
New Algorithms for Control-Flow Graph Structuring
CSMR '01 Proceedings of the Fifth European Conference on Software Maintenance and Reengineering
Source versus Object Code Extraction for Recovering Software Architecture
WCRE '05 Proceedings of the 12th Working Conference on Reverse Engineering
Predicting software reliability with neural network ensembles
Expert Systems with Applications: An International Journal
A Digital Image Encryption Algorithm Based on Hyper-chaotic Cellular Neural Network
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I)
Source code and binary analysis of software defects
Proceedings of the 5th Annual Workshop on Cyber Security and Information Intelligence Research: Cyber Security and Information Intelligence Challenges and Strategies
Fault-prone module prediction of a web application using artificial neural networks
SEA '07 Proceedings of the 11th IASTED International Conference on Software Engineering and Applications
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Traceability of codes refers to the mapping between equivalent codes written in different languages - including high-level and low-level programming languages. In the field of Legal Metrology, it is critical to guarantee that the software embedded in a meter corresponds to a version that was previously approved by the Legal Metrology Authority. In this paper, we propose a novel approach for correlating source and object codes using artificial neural networks. Our approach correlates the source code with the object code by feeding the neural network with logical flow characteristics of such codes. Any incidence of false positives is obviously a critical issue for software evaluation purposes. Our evaluation using real code examples shows a correspondence around 90% for the traceability of the executable codes with very low rate of false positives.