Powering the static driver verifier using corral

A. Lal, S. Qadeer
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引用次数: 34

Abstract

The application of software-verification technology towards building realistic bug-finding tools requires working through several precision-scalability tradeoffs. For instance, a critical aspect while dealing with C programs is to formally define the treatment of pointers and the heap. A machine-level modeling is often intractable, whereas one that leverages high-level information (such as types) can be inaccurate. Another tradeoff is modeling integer arithmetic. Ideally, all arithmetic should be performed over bitvector representations whereas the current practice in most tools is to use mathematical integers for scalability. A third tradeoff, in the context of bounded program exploration, is to choose a bound that ensures high coverage without overwhelming the analysis. This paper works through these three tradeoffs when we applied Corral, an SMT-based verifier, inside Microsoft's Static Driver Verifier (SDV). Our decisions were guided by experimentation on a large set of drivers; the total verification time exceeded well over a month. We justify that each of our decisions were crucial in getting value out of Corral and led to Corral being accepted as the engine that powers SDV in the Windows 8.1 release, replacing the SLAM engine that had been used inside SDV for the past decade.
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使用畜栏为静态驱动验证器供电
将软件验证技术应用于构建现实的bug查找工具需要在精度和可伸缩性之间进行权衡。例如,处理C程序的一个关键方面是正式定义指针和堆的处理方式。机器级建模通常是难以处理的,而利用高级信息(如类型)的建模可能是不准确的。另一个权衡是对整数运算进行建模。理想情况下,所有算术都应该在位向量表示上执行,而目前大多数工具的实践是使用数学整数来实现可伸缩性。在有界程序探索的上下文中,第三个权衡是选择一个确保高覆盖率而不压倒分析的范围。当我们在微软的静态驱动验证器(SDV)中应用Corral(一个基于smt的验证器)时,本文通过这三个权衡进行了研究。我们的决定是在大量驱动因素的实验指导下做出的;核查总时间超过了一个多月。我们证明,我们的每一个决定都对从Corral中获得价值至关重要,并导致Corral被接受为Windows 8.1版本中驱动SDV的引擎,取代了过去十年中在SDV中使用的SLAM引擎。
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