Bridging the Gap between Requirements Modeling and Behavior-driven Development

被引:7
作者
Alferez, Mauricio [1 ]
Pastore, Fabrizio [1 ]
Sabetzadeh, Mehrdad [1 ]
Briand, Lionel C. [1 ,2 ]
Riccardi, Jean-Richard [3 ]
机构
[1] Univ Luxembourg, SnT Ctr Secur Reliabil & Trust, Luxembourg, Luxembourg
[2] Univ Ottawa, Sch Engn & Comp Sci, Ottawa, ON, Canada
[3] Clearstream Serv SA, Luxembourg, Luxembourg
来源
2019 ACM/IEEE 22ND INTERNATIONAL CONFERENCE ON MODEL DRIVEN ENGINEERING LANGUAGES AND SYSTEMS (MODELS 2019) | 2019年
基金
欧洲研究理事会;
关键词
Software testing; BDD; modeling; requirements engineering; text generation; Gherkin; and FinTech; GENERATION;
D O I
10.1109/MODELS.2019.00008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Acceptance criteria (AC) are implementation agnostic conditions that a system must meet to be consistent with its requirements and be accepted by its stakeholders. Each acceptance criterion is typically expressed as a natural-language statement with a clear pass or fail outcome. Writing AC is a tedious and error-prone activity, especially when the requirements specifications evolve and there are different analysts and testing teams involved. Analysts and testers must iterate multiple times to ensure that AC are understandable and feasible, and accurately address the most important requirements and workflows of the system being developed. In many cases, analysts express requirements through models, along with natural language, typically in some variant of the UML. AC must then be derived by developers and testers from such models. In this paper, we bridge the gap between requirements models and AC by providing a UML-based modeling methodology and an automated solution to generate AC. We target AC in the form of Behavioral Specifications in the context of Behavioral-Driven Development (BDD), a widely used agile practice in many application domains. More specially we target the well-known Gherkin language to express AC, which then can be used to generate executable test cases. We evaluate our modeling methodology and AC generation solution through an industrial case study in the financial domain. Our results suggest that (1) our methodology is feasible to apply in practice, and (2) the additional modeling effort required by our methodology is outweighed by the benefits the methodology brings in terms of automated and systematic AC generation and improved model precision.
引用
收藏
页码:239 / 249
页数:11
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