IABC‐TCG: Improved artificial bee colony algorithm‐based test case generation for smart contracts

Abstract With the widespread application of smart contracts, there is a growing concern over the quality assurance of smart contracts. The data flow testing is an important technology to ensure the correctness of smart contracts. We propose an approach named IABC‐TCG (Improved Artificial Bee Colony‐Test Case Generation) to generate test cases for the data flow testing of smart contracts. With a dominance relations‐based fitness function, an improved artificial bee colony algorithm is used to generate test cases, in which the bee colony search coefficient is adaptively adjusted to improve the effectiveness and efficiency of the search. In addition, an improved test case selection and updation strategy is used to avoid unnecessary test cases. The experimental results show that IABC‐TCG achieves 100% coverage for all the test requirements on a dataset of 30 smart contracts and outperforms the baseline approaches in terms of the number of test cases and the execution time. Performing tests with the generated test cases, IABC‐TCG can find more errors with less test cost.

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Publication Details

Journal
Journal of Software Evolution and Process
Published
2024-08-08
DOI
https://doi.org/10.1002/smr.2719
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

IABC‐TCG: Improved artificial bee colony algorithm‐based test case generation for smart contracts

Hai Dong, Shaoqing Zhu, Pengcheng Zhang, Shunhui Ji et al.
Journal of Software Evolution and Process
Advanced Malware Detection Techniques
article

IABC‐TCG: Improved artificial bee colony algorithm‐based test case generation for smart contracts

Hai Dong, Shaoqing Zhu, Pengcheng Zhang, Shunhui Ji, Jiahao Gong
article en

Abstract

Abstract With the widespread application of smart contracts, there is a growing concern over the quality assurance of smart contracts. The data flow testing is an important technology to ensure the correctness of smart contracts. We propose an approach named IABC‐TCG (Improved Artificial Bee Colony‐Test Case Generation) to generate test cases for the data flow testing of smart contracts. With a dominance relations‐based fitness function, an improved artificial bee colony algorithm is used to generate test cases, in which the bee colony search coefficient is adaptively adjusted to improve the effectiveness and efficiency of the search. In addition, an improved test case selection and updation strategy is used to avoid unnecessary test cases. The experimental results show that IABC‐TCG achieves 100% coverage for all the test requirements on a dataset of 30 smart contracts and outperforms the baseline approaches in terms of the number of test cases and the execution time. Performing tests with the generated test cases, IABC‐TCG can find more errors with less test cost.

Journal of Software Evolution and ProcessVol. 36(12)
Hohai University (CN), Ministry of Water Resources of the People's Republic of China (CN), RMIT University (AU)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 86%
Advanced Malware Detection Techniques
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IABC‐TCG: Improved artificial bee colony algorithm‐based test case generation for smart contracts — Hai Dong, Shaoqing Zhu, et al. · Journal of Software Evolution and Process (2024) | TGRS Research Map | TGRS