CAREER: Testing Evolving Complex Software Systems

职业：测试不断发展的复杂软件系统

• 批准号: 1652149
• 负责人: Tingting Yu
• 金额: $ 50.18万
• 依托单位: University of Kentucky Research Foundation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1652149&HistoricalAwards=false
• 关键词: CAREER; Testing; Evolving; Complex; Software

Modern computer systems span a wide range of domains, ranging from consumer electronics (e.g., smart-phones) to safety-critical systems (e.g., avionics). These systems evolve rapidly because the competition for market share pushes developers to come up with new features or improve capabilities over existing ones. These software changes may require hardware replacements or upgrades to capitalize on software upgrade opportunities. As such, developers must ensure that changes do not cause any unintended impact to the existing quality of the systems. Regression testing has been widely used to assess whether changes have adversely affected system behavior. While significant work has been accomplished by the software engineering community in improving effectiveness and efficiency of regression testing, most of the existing techniques focus on traditional software that is environment-independent and non-distributed. Real-world software systems, however, are far more complex: they frequently interact with the environment via hardware devices, and employ various concurrency mechanisms to coordinate interrupts, signals, threads, and processes. These characteristics affect various techniques on which existing regression testing approaches rely. Therefore, applying these approaches may lead to problems during maintenance and thus impair software quality.The overall goal of this proposal is to create a novel regression testing framework that can be applied to real-world complex software systems, focusing on the hardware dependence and concurrent control characteristics, throughout their lifetimes. Specifically, this research will develop, evaluate, and make available a family of techniques and tools that can: 1) create comprehensive models of the whole system to analyze change impact across hardware and software layers and across concurrent events, 2) retest the systems accordingly using existing test cases, and 3) generate new test cases when needed. The analytical underpinnings of this research will be applicable not only to the software engineering community, but to industry and other disciplines in which software dependability plays an important role. The associated education agenda paves the way for teaching that cross traditional boundaries among multicore computing, embedded systems and software engineering, which may ultimately, through the dissemination of new curricular materials, have impacts to the broader scientific community.

现代计算机系统涵盖广泛的领域，从消费电子产品（例如智能手机）到安全关键系统（例如航空电子设备）。这些系统发展迅速，因为市场份额的竞争促使开发人员推出新功能或改进现有功能。这些软件更改可能需要更换或升级硬件才能利用软件升级机会。因此，开发人员必须确保更改不会对系统的现有质量造成任何意外影响。回归测试已被广泛用于评估更改是否对系统行为产生不利影响。虽然软件工程社区在提高回归测试的有效性和效率方面已经完成了大量工作，但大多数现有技术都集中在与环境无关且非分布式的传统软件上。然而，现实世界的软件系统要复杂得多：它们频繁地通过硬件设备与环境交互，并采用各种并发机制来协调中断、信号、线程和进程。这些特征影响现有回归测试方法所依赖的各种技术。因此，应用这些方法可能会导致维护过程中出现问题，从而损害软件质量。该提案的总体目标是创建一个新颖的回归测试框架，可以应用于现实世界的复杂软件系统，重点关注硬件依赖性和并发性控制特性，贯穿其整个生命周期。具体来说，这项研究将开发、评估并提供一系列技术和工具，这些技术和工具可以：1）创建整个系统的综合模型，以分析跨硬件和软件层以及跨并发事件的变更影响，2）相应地重新测试系统使用现有的测试用例，3) 在需要时生成新的测试用例。这项研究的分析基础不仅适用于软件工程界，而且适用于软件可靠性发挥重要作用的行业和其他学科。相关的教育议程为跨越多核计算、嵌入式系统和软件工程之间的传统界限的教学铺平了道路，最终可能通过新课程材料的传播对更广泛的科学界产生影响。

项目成果

Automatic detection and validation of race conditions in interrupt-driven embedded software

• DOI: 10.1145/3092703.3092724
• 发表时间: 2017-07
• 期刊: Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis
• 作者: Yu Wang;Linzhang Wang;Tingting Yu;Jianhua Zhao;Xuandong Li

ConfProf: White-Box Performance Profiling of Configuration Options

• DOI: 10.1145/3427921.3450255
• 发表时间: 2021-01-01
• 期刊: PROCEEDINGS OF THE ACM/SPEC INTERNATIONAL CONFERENCE ON PERFORMANCE ENGINEERING (ICPE '21)
• 作者: Han, Xue;Yu, Tingting;Pradel, Michael
• 通讯作者: Pradel, Michael

SCMiner: Localizing System-Level Concurrency Faults from Large System Call Traces

• DOI: 10.1109/ase.2019.00055
• 发表时间: 2019-11
• 期刊: 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: T. S. Zaman;Xue Han;Tingting Yu

PerfLearner: Learning from Bug Reports to Understand and Generate Performance Test Frames

• DOI: 10.1145/3238147.3238204
• 发表时间: 2018-09
• 期刊: 2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: Xue Han;Tingting Yu;D. Lo

ConTesa: Directed Test Suite Augmentation for Concurrent Software

ConTesa：并发软件的定向测试套件增强

• DOI: 10.1109/tse.2018.2861392
• 发表时间: 2018
• 期刊: IEEE transactions on software engineering
• 影响因子: 7.4
• 作者: Yu, Tingting;Huang, Zunchen;Wang, Chao
• 通讯作者: Wang, Chao