BPMN 2.0流程的自动回归测试:用于持续交付的捕获和重放框架

Majid Makki, D. Landuyt, W. Joosen
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引用次数: 7

摘要

回归测试是软件质量保证(QA)的一种形式,它涉及将软件工件的新版本的行为与其早期的正确行为进行比较,并在检测到偏差时向QA工程师发出信号。考虑到在运行系统的上下文中自动生成和执行业务流程模型的回归测试用例的巨大潜力,需要强大的工具使其实际可行,更具体地说,需要限制对生产系统的潜在影响,并减少QA工程师所需的手工工作。在本文中,我们提出了一个回归测试自动化框架,该框架在BPMN 2.0上下文中实现了捕获和重放范式,BPMN 2.0是一种用于建模和执行业务流程的领域特定语言。该框架采用并行化技术和高效的通信模式来减少捕获的性能开销。基于QA工程师的输入,它在执行测试之前对BPMN2模型进行操作,以便将后者与外部依赖(例如,人工参与者或昂贵的web服务)隔离开来,并避免不希望出现的副作用。最后,它执行回归检测算法并将结果报告给QA工程师。我们在兼容bpmn2的执行引擎(即jBPM)之上实现了我们的框架,并对其性能和容错性进行了功能验证和评估。结果表明,平均捕获性能开销为3.9%,这表明实现的框架可以成为BPMN 2.0实用回归测试工具的基础,并且是持续交付业务流程驱动的应用程序和服务的关键推动者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated regression testing of BPMN 2.0 processes: a capture and replay framework for continuous delivery
Regression testing is a form of software quality assurance (QA) that involves comparing the behavior of a newer version of a software artifact to its earlier correct behavior, and signaling the QA engineer when deviations are detected. Given the large potential in automated generation and execution of regression test cases for business process models in the context of running systems, powerful tools are required to make this practically feasible, more specifically to limit the potential impact on production systems, and to reduce the manual effort required from QA engineers. In this paper, we present a regression testing automation framework that implements the capture & replay paradigm in the context of BPMN 2.0, a domain-specific language for modeling and executing business processes. The framework employs parallelization techniques and efficient communication patterns to reduce the performance overhead of capturing. Based on inputs from the QA engineer, it manipulates the BPMN2 model before executing tests for isolating the latter from external dependencies (e.g. human actors or expensive web services) and for avoiding undesired side-effects. Finally, it performs a regression detection algorithm and reports the results to the QA engineer. We have implemented our framework on top of a BPMN2-compliant execution engine, namely jBPM, and performed functional validations and evaluations of its performance and fault-tolerance. The results, indicating 3.9% average capturing performance overhead, demonstrate that the implemented framework can be the foundation of a practical regression testing tool for BPMN 2.0, and a key enabler for continuous delivery of business process-driven applications and services.
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