Albin Lönnfält , Viktor Tu , Gregory Gay , Animesh Singh , Sahar Tahvili
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引用次数: 0
摘要
为确保对任何软件产品进行适当的测试,必须在不同的测试级别(如单元测试或集成测试)涵盖各种功能和非功能要求。确保适当的测试需要做出一系列决策,例如,将功能分配给不同的持续集成(CI)配置,或确定哪些测试规范需要自动化。这些决策一般都是手动做出的,需要深入的领域知识。本研究介绍、实施并评估了 ITMOS(智能测试管理优化系统),这是一种智能测试管理系统,旨在优化软件测试过程中的决策。ITMOS 可高效处理以自然语言呈现的新需求,并根据预定义的质量标准将每个需求分离成适当的 CI 配置。此外,ITMOS 还能为测试自动化提出一套测试规范。爱立信公司在一个工业电信项目中对所提解决方案的可行性和潜在适用性进行了实证评估。在这种情况下,ITMOS 在决策任务方面取得了准确的结果,超过了领域专家设定的要求。
An intelligent test management system for optimizing decision making during software testing
To ensure the proper testing of any software product, it is imperative to cover various functional and non-functional requirements at different testing levels (e.g., unit or integration testing). Ensuring appropriate testing requires making a series of decisions—e.g., assigning features to distinct Continuous Integration (CI) configurations or determining which test specifications to automate. Such decisions are generally made manually and require in-depth domain knowledge. This study introduces, implements, and evaluates ITMOS (Intelligent Test Management Optimization System), an intelligent test management system designed to optimize decision-making during the software testing process. ITMOS efficiently processes new requirements presented in natural language, segregating each requirement into appropriate CI configurations based on predefined quality criteria. Additionally, ITMOS has the capability to suggest a set of test specifications for test automation. The feasibility and potential applicability of the proposed solution were empirically evaluated in an industrial telecommunications project at Ericsson. In this context, ITMOS achieved accurate results for decision-making tasks, exceeding the requirements set by domain experts.
期刊介绍:
The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to:
•Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution
•Agile, model-driven, service-oriented, open source and global software development
•Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems
•Human factors and management concerns of software development
•Data management and big data issues of software systems
•Metrics and evaluation, data mining of software development resources
•Business and economic aspects of software development processes
The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.