CSR --- SMA: Predictive Testing of System Software

如今的软件系统存在可靠性和安全性差的问题，软件错误每年给美国经济造成的损失高达600亿美元。这种情况可能会变得更糟，因为软件系统的复杂性增加了，而软件质量工具和技术的有效性却没有相应的增加。这种情况对并发系统来说尤其具有挑战性，这对软件质量工具提出了明显更高的难度，但随着多核机器的使用越来越广泛。静态分析软件质量工具非常精确，但不能很好地扩展到大型代码。测试很容易使用，但为了更好地覆盖，需要大量的测试套件。我们建议通过将临时测试和静态分析结合在一种名为预测测试的新的可扩展技术中来弥合这两者之间的差距。预测性测试使用静态程序分析来最大化给定测试套件的有效性，以便在测试阶段发现可能在实际生产运行中表现出来的错误。尽管预测性测试工具在内部使用复杂静态分析和自动定理证明技术，但所有这些复杂性都通过测试用法模型对用户隐藏。出于这个原因，我们希望这样的工具可以很容易地集成到现有的软件工程过程中，并且即使是不成熟的开发人员也可以使用。

Today's software systems suffer from poor reliability and security,with software errors costing the U.S. economy upwards of $60 billionannually. This situation is likely to get worse, as the complexity ofsoftware systems increases without a matching increase in theeffectiveness of software quality tools and techniques. The situationis particularly challenging for concurrent systems, which posesignificantly higher difficulties for software quality tools, yet arebecoming more widespread with the growing use of multicore machines.Static analysis software-quality tools are very precise but do notscale well to large codes. Testing is easy to use but for goodcoverage requires extensive test suites. We propose to bridge the gapbetween ad hoc testing and static analysis by combining them in a newscalable technique called predictive testing. Predictive testing usesstatic program analysis to maximize the effectiveness of a giventest-suite for finding in the testing stage bugs that could manifestin real production runs. Although predictive testing tools use complexstatic analysis and automated theorem proving techniques internally,all of this complexity is hidden from the user by a testing usagemodel. For this reason, we expect that such tools can be easilyintegrated into existing software engineering processes and will beusable even by unsophisticated developers.