Counting Bugs in Behavioural Models using Counterexample Analysis

Irman Faqrizal, Gwen Salaün
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Abstract

Designing and developing distributed software has always been a tedious and error-prone task, and the ever increasing software complexity is making matters even worse. Model checking automatically verifies that a model, e.g., a Labelled Transition System (LTS), obtained from higher-level specification languages satisfies a given temporal property. When the model violates the property, the model checker returns a counterexample, but this counterexample does not precisely identify the source of the bug. In this work, we propose some techniques for simplifying the debugging of these models. These techniques first extract from the whole behavioural model the part which does not satisfy the given property. In that model, we then detect specific states (called faulty states) where a choice is possible between executing a correct behaviour or falling into an erroneous part of the model. By using this model, we propose in this paper some techniques to count the number of bugs in the original specification. The core idea of the approach is to change the specification for some specific actions that may cause the property violation, and compare the model before and after modification to detect whether this potential bug is one real bug or not. Beyond introducing in details the solution, this paper also presents tool support and experiments.
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使用反例分析计算行为模型中的错误
设计和开发分布式软件一直是一项乏味且容易出错的任务,而不断增加的软件复杂性使事情变得更糟。模型检查自动地验证从高级规范语言获得的模型,例如,标记转换系统(labeled Transition System, LTS),是否满足给定的时间属性。当模型违反该属性时,模型检查器返回一个反例,但是这个反例并不能精确地识别错误的来源。在这项工作中,我们提出了一些简化这些模型调试的技术。这些技术首先从整个行为模型中提取出不满足给定属性的部分。在该模型中,我们然后检测特定的状态(称为错误状态),在这些状态中,可以在执行正确的行为或落入模型的错误部分之间进行选择。利用这个模型,我们提出了一些计算原始规范中bug数量的技术。该方法的核心思想是对一些可能导致属性冲突的特定操作更改规范,并比较修改前后的模型,以检测该潜在错误是否是一个真正的错误。本文除了详细介绍了解决方案外,还提供了工具支持和实验。
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