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通过分析代码覆盖提高功能覆盖率的验证输入自动生成方法

An Automatic Test Generation Method for Functional Coverage Improvement by Code Coverage Analysis

  • 摘要: 覆盖率驱动的验证是功能验证的重要方法,但功能覆盖定义的主观性和手工调整验证输入的冗长过程都极大地影响了覆盖率驱动验证的效率.文中分析了代码行覆盖次数与功能覆盖率的内在联系,建立了基于代码行覆盖次数的概率模型,提出一种新的通过分析代码覆盖提高功能覆盖率的验证输入自动生成方法--FOCDGAG.通过代码行覆盖次数计算验证输入序列的适应度,选取对提高功能覆盖率贡献较高的输入序列,使用遗传算法自动生成新的输入序列组.实验结果表明,采用FOCDGAG时不需要功能覆盖信息,可以将全随机输入生成的功能覆盖率收敛速度提高10倍以上,将约束随机输入生成的功能覆盖率收敛速度提高20倍以上.

     

    Abstract: Coverage driven is an important technology for functional verification.However,the efficiency of coverage driven verification is greatly affected by the subjectivity of the functional coverage definitions and lengthy manual test adjustment.This paper analyzes the relationship between the line covered times and functional coverage.Besides,it also establishes a statistical probability model based on the line covered times.By using this model,a novel method,i.e.,functional coverage oriented,code coverage driven and genetic algorithm based automatic test generation (FOCDGAG) is presented.This method selects genetic algorithm to analyze the line covered times and generate new verification inputs automatically.FOCDGAG enhances functional coverage rapidly without using the information of functional coverage.Experimental results show that FOCDGAG can speed up the convergence of random test generation more than 10times and constrained random test generation more than 20 times.

     

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