CAREER: Scalable and Systematic Test Authoring and Maintenance

验证软件质量最常用的方法是测试。从概念上讲，测试很简单。然而，在实践中，测试有两个关键的限制：它是昂贵的，通常占开发成本的一半以上，并且是无效的，经常不能找到可能导致重大损害的关键错误。这个项目通过开发一种基于测试摘要（期望测试的抽象属性）的新的测试自动化框架来解决这些限制。开发人员将摘要编写为定义所需输入和要检查的属性的逻辑约束，并且工具针对可能发现许多错误的密集套件执行测试。项目开发：(1)有效系统测试的核心算法，生成高质量输入，进行深度白盒检查，合成可执行的测试预言机；(2)有效的系统测试优化策略，将其扩展到大型应用；(3)支持演进的增量技术，它为代码更改提供有效的测试更新；(4)增强可用性的基础设施支持，它帮助开发人员编写测试摘要。使用各种应用程序的案例研究用于评估。使用测试摘要的系统测试将大大增加测试覆盖率和准确性，这将显著提高软件质量。PI的工业合作和参与UT的执行硕士课程使技术迅速转移到工业。

The most commonly used methodology for validating the quality of software is testing. Conceptually, testing is simple. In practice, however, testing has two key limitations: it is expensive, often amounting to over a half of the development cost, and ineffective, often failing to find crucial bugs that can cause significant damage.This project addresses these limitations by developing a novel test automation framework based on test summaries -- abstract properties of desired tests. Developers write summaries as logical constraints that define desired inputs and properties to check, and the tools perform testing against dense suites that are likely to find many bugs. The project develops: (1) core algorithms for effective systematic testing, which generate high quality inputs, perform deep white-box checking, and synthesize executable test oracles; (2) optimization strategies for efficient systematic testing, which scale it to large applications; (3) incremental techniques for supporting evolution, which provide efficient test updates with respect to code changes; and (4) infrastructure support for enhancing usability, which assists developers with writing test summaries. Case studies using a variety of applications are used for evaluation.Systematic testing using test summaries will substantially increase test coverage and accuracy, which will significantly improve software quality. The PI's industrial collaborations and participation in UT's Executive Masters program enable a swift technology transfer to industry.