该文总结并分析了人工智能技术在自动化测试数据生成领域的研究应用，指出这一问题可转化为带有不连续性和非线性的组合优化问题，适合采用神经网络和遗传算法等AI方法解决。并探讨了未来的研究方向及现存挑战。
摘要：
The automatic software test data generation is one of the elementary problems in software testing. The problem of test data generation is reduced to a search or combinatorial optimization problem with discontinuity and nonlinearity. Therefore, it can be suitably resolved by using AI techniques such as neural networks and genetic algorithms. This paper summarizes and analyzes the application research of AI techniques on automatic test data generation. Future research directions and some of the researching problems are also addressed.
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