标题： 基于神经进化的游戏测试增强：针对Scratch程序的分支覆盖方法 显示英文标题

标题： Enhancing NeuroEvolution-Based Game Testing: A Branch Coverage Approach for Scratch Programs

摘要： 自动化测试生成对于类似游戏的程序提出了独特的挑战，这是由于它们的非确定性行为和复杂的控制结构。 NEATEST框架已被用于Scratch游戏的自动化测试，采用基于神经进化测试生成的方法，优化以实现语句覆盖。 然而，仅靠语句覆盖通常不足以检测故障，因为它不能保证执行所有逻辑分支。 本文介绍了一种基于分支覆盖的适应度函数，以提高自动化游戏测试的测试效果。 我们通过集成一个优先考虑控制依赖分支的分支适应度函数来扩展NEATEST，引导神经进化过程以最大化分支探索。 为了评估这种方法的有效性，对25个Scratch游戏进行了实证实验，将Neatest与语句覆盖（NSC）与Neatest与分支覆盖（NBC）进行比较。 还进行了突变分析，以评估两种技术的故障检测能力。 结果表明，在25个游戏中的13个中，NBC实现了比NSC更高的分支覆盖，特别是在具有复杂条件结构的程序中。 此外，NBC在突变测试中实现了较低的误报率，使其成为识别游戏程序中故障行为更可靠的方法。 这些发现证实了基于分支覆盖的测试生成提高了Scratch程序的测试覆盖率和故障检测能力。 显示英文摘要

摘要： Automated test generation for game-like programs presents unique challenges due to their non-deterministic behavior and complex control structures. The NEATEST framework has been used for automated testing in Scratch games, employing neuroevolution-based test generation optimized for statement coverage. However, statement coverage alone is often insufficient for fault detection, as it does not guarantee execution of all logical branches. This paper introduces a branch coverage-based fitness function to enhance test effectiveness in automated game testing. We extend NEATEST by integrating a branch fitness function that prioritizes control-dependent branches, guiding the neuroevolution process to maximize branch exploration. To evaluate the effectiveness of this approach, empirical experiments were conducted on 25 Scratch games, comparing Neatest with Statement Coverage (NSC) against Neatest with Branch Coverage (NBC). A mutation analysis was also performed to assess the fault detection capabilities of both techniques. The results demonstrate that NBC achieves higher branch coverage than NSC in 13 out of 25 games, particularly in programs with complex conditional structures. Moreover, NBC achieves a lower false positive rate in mutation testing, making it a more reliable approach for identifying faulty behavior in game programs. These findings confirm that branch coverage-based test generation improves test coverage and fault detection in Scratch programs.