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.
Graphical Abstract
We propose IABC‐TCG (Improved Artificial Bee Colony‐Test Case Generation) to generate test cases for the data flow testing of smart contracts. The improved ABC (Artificial Bee Colony) algorithm is applied to generate test cases, in which a dominance relations based fitness function is used to guide the searching for test cases that cover the to‐be‐tested definition‐use pairs and the bee colony search coefficient is adaptively adjusted to improve the effectiveness and efficiency of the search. In addition, the test case selection and updation strategy is improved to avoid unnecessary test cases. Experimental results show that IABC‐TCG achieves 100% coverage and outperforms the comparative approaches in the number of test cases and the average execution time.
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Published: 10 December 2024
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