PreDive: preserving diversity in test cases for evolving digital circuits using grammatical evolution
Authors: 
Krishn Kumar Gupt, Meghana Kshirsagar, Lukas Rosenbauer, Joseph P. Sullivan, Douglas Mota Dias, Conor RyanAuthors Info & Claims
Pages 719 - 722
Abstract
The ever-present challenge in the domain of digital devices is how to test their behavior efficiently. We tackle the issue in two ways. We switch to an automated circuit design using Grammatical Evolution (GE). Additionally, we provide two diversity-based methodologies to improve testing efficiency. The first approach extracts a minimal number of test cases from subsets formed through clustering. Moreover, the way we perform clustering can easily be used for other domains as it is problem-agnostic. The other uses complete test set and introduces a novel fitness function hitPlex that incorporates a test case diversity measure to speed up the evolutionary process.
Experimental and statistical evaluations on six benchmark circuits establish that the automatically selected test cases result in good coverage and enable the system to evolve a highly accurate digital circuit. Evolutionary runs using hitPlex indicate promising improvements, with up to 16% improvement in convergence speed and up to 30% in success rate for complex circuits when compared to the system without the diversity extension.
References
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Prabhleen Bindra, Meghana Kshirsagar, Conor Ryan, Gauri Vaidya, Krishn Kumar Gupt, and Vivek Kshirsagar. 2021. Insights into the Advancements of Artificial Intelligence and Machine Learning, the Present State of Art, and Future Prospects: Seven Decades of Digital Revolution.
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Tsong Yueh Chen. 2010. Fundamentals of test case selection: Diversity, diversity, diversity. In The 2nd International Conference on Software Engineering and Data Mining. IEEE, 723--724.
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Mohammed Ferdjallah. 2011. Introduction to digital systems: modeling, synthesis, and simulation using VHDL. John Wiley & Sons.
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Krishn Kumar Gupt, Meghana Kshirsagar, Joseph P Sullivan, and Conor Ryan. 2021. Automatic Test Case Generation for Prime Field Elliptic Curve Cryptographic Circuits. In 2021 IEEE 17th International Colloquium on Signal Processing & Its Applications (CSPA). IEEE, 121--126.
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Krishn Kumar Gupt, Meghana Kshirsagar, Joseph P Sullivan, and Conor Ryan. 2021. Automatic test case generation for vulnerability analysis of galois field arithmetic circuits. In 2021 IEEE 5th International Conference on Cryptography, Security and Privacy (CSP). IEEE, 32--37.
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J R Koza. 1992. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge, MA, USA.
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Meghana Kshirsagar, Rushikesh Jachak, Purva Chaudhari, and Conor Ryan. 2020. GEMO: Grammatical Evolution Memory Optimization System. In IJCCI. 184--191.
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Conor Ryan, Meghana Kshirsagar, Krishn Kumar Gupt, Lukas Rosenbauer, and Joseph P Sullivan. 2021. Hierarchical Clustering Driven Test Case Selection in Digital Circuits.
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- PreDive: preserving diversity in test cases for evolving digital circuits using grammatical evolution
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Published: 19 July 2022
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