Program Behavior Representation Learning for Software Testing

软件测试的程序行为表示学习

• 批准号: RGPIN-2020-04552
• 负责人: Hemmati, Hadi
• 金额: $ 2.55万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752119
• 关键词: Program; Behavior; Representation; Learning; Software

Software has been incorporated into an ever-increasing number of mission and safety-critical systems such as self-driving cars, air traffic control systems, communication platforms, e-banking infrastructures and e-commerce systems. Such systems provide central and crucial services to our society and thus require high quality software. However, history is full of software failures that have caused numerous problems: aircraft have crashed, patients have died from incorrect medication, and key financial systems have broken down. My research is directed towards improving the quality of software. My program focuses on software testing as the most commonly used method of quality assurance in the software industry. Recent research has shown that systematic test automation potentially increases the effectiveness of testing and reduces its cost. The ultimate goal in software testing is to make sure the actual behaviour of the software at run-time matches the expected behavior of the software. However, manually defining the behavior is quite costly. Thus, most existing test automation techniques are source code-driven and miss many challenging behavioral defects. The core idea of this research is to change the current tradition of source code-driven testing of software programs to behavior-driven testing, without the extra cost of manual modeling. I propose an approach where using machine learning, the behavioral model of the program can be inferred and optimized. Such inferred models can then be used to further test the software. The models will be optimized toward test generation. In other words, they distinctly identify the part of behavior space that requires more testing. In addition, they provide mechanisms to actually generate such tests. The proposed techniques will be empirically evaluated on large software systems and compared against existing software test automation techniques. Since software testing is one of the most commonly used techniques in almost every software development process, Canadian software communities in many sectors will be well positioned to benefit from the outcomes of this research, through decreased costs and increased software quality leading to enhanced competitiveness, internationally. Though this proposal is only about functional testing, the long-term goal is to generalize its core idea of learning a specialized behavioral model to run-time analysis in other domains such as debugging, program comprehension, and security. Thus, this research has the potential to affect many sub-domains within computer science and software engineering. The proposed research program will train 11 highly qualified personnel (HQP): 2 PhD and 4 Master and 5 undergrad summer students. All HQPs will work closely with Canadian companies, gaining an appreciation of the challenges facing practitioners on a daily basis and helping them to improve their products and processes.

软件已被纳入越来越多的任务和安全关键系统，如自动驾驶汽车、空中交通管制系统、通信平台、电子银行基础设施和电子商务系统。这些系统为我们的社会提供了核心和关键的服务，因此需要高质量的软件。然而，历史上充斥着软件故障导致的无数问题：飞机坠毁，病人死于错误的药物治疗，以及关键的金融系统崩溃。我的研究方向是提高软件的质量。我的课程侧重于软件测试，这是软件行业中最常用的质量保证方法。最近的研究表明，系统的测试自动化潜在地提高了测试的有效性，并降低了测试的成本。软件测试的最终目标是确保软件在运行时的实际行为与软件的预期行为相匹配。然而，手动定义行为的成本相当高。因此，大多数现有的测试自动化技术都是源代码驱动的，并且忽略了许多具有挑战性的行为缺陷。本研究的核心思想是将当前软件程序的源代码驱动测试的传统改变为行为驱动测试，而不需要额外的手工建模成本。我提出了一种使用机器学习的方法，可以推断和优化程序的行为模型。这样的推断模型可以用来进一步测试软件。这些模型将针对测试生成进行优化。换句话说，它们清楚地确定了需要更多测试的行为空间部分。此外，它们还提供了实际生成此类测试的机制。建议的技术将在大型软件系统上进行经验评估，并与现有的软件测试自动化技术进行比较。由于软件测试是几乎所有软件开发过程中最常用的技术之一，加拿大许多部门的软件社区将很好地从这项研究的结果中受益，通过降低成本和提高软件质量来提高国际竞争力。虽然这个建议只是关于功能测试，但长期目标是将其核心思想推广到其他领域的运行时分析，如调试、程序理解和安全性。因此，这项研究有可能影响计算机科学和软件工程中的许多子领域。本项目拟培养高层次人才（HQP） 11人，其中博士2人，硕士4人，本科暑期生5人。所有hqp将与加拿大公司密切合作，了解从业者每天面临的挑战，并帮助他们改进产品和流程。