一句话：提出值具体化变换约束逻辑公式，缓解 COBOL 测试输入生成中字节级建模带来的求解器性能下降。
自动化生成测试输入数据是软件工程研究中的关键技术挑战。本文面向企业应用中广泛使用的 COBOL 语言，开发自动化测试输入数据生成工具。方法沿用符号执行与约束求解相结合的混合方案，并针对 COBOL 的多样数据表示，在工具的内存模型中引入字节级数据表示。然而，这会增加约束的复杂度与规模，导致求解器性能下降。为此，作者提出通过值具体化（value concretization）来变换约束逻辑公式，以简化求解过程。评估结果表明，该技术能够有效缓解上述性能问题。
Automated generation of test input data is a major technical challenge in software engineering research. We are developing a tool for automated test input data generation for COBOL, a language widely used in enterprise applications. As in prior studies, we employ a hybrid approach that combines symbolic execution and constraint solving. In addition, to accommodate the various data representations in COBOL, we introduce a byte-level data representation into the memory model used by our tool. However, this increases constraint complexity and size, leading to degraded solver performance. To address this issue, we propose transforming constraint logic formulae through value concretization. Our evaluation shows that this technique effectively alleviates the performance problem.
@inproceedings{paperbot11742,
title = {Performance Improvement of Automated Test Input Data Generation by Using Value Concretization},
author = {Toshiaki Yasue and Kouichi Ono and Atul Kumar and Diptikalyan Saha and Fumiko Satoh},
booktitle = {ICSE},
year = {2026},
doi = {10.1145/3774748.3795664}
}