C&amp;L: Generating model based test cases from natural language requirements descriptions

Sarmiento, Edgar; Leite, Julio Cesar Sampaio do Prado; Almentero, Eduardo

doi:10.1109/ret.2014.6908677

Cited by 36 publications

(27 citation statements)

References 10 publications

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“…Not all studies start, however, with already specified requirements. [28] and [29] present methods to generate model-based test cases from natural language (NL) requirements to bring RE and ST closer. Use cases can also be used to deal with ambiguities of NL requirements.…”

Section: Focus Of Research (Rq2)mentioning

confidence: 99%

What Do We Know about Alignment of Requirements Engineering and Software Testing?

Karhapää

Haghighatkhah

Oivo

2017

Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering

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Context:The alignment of different software engineering activities for coordinated functioning and optimized product development is of great importance, particularly in industrialscale development. The link between intermediate activities has been researched extensively, but the link between requirements engineering (RE) and software testing (ST) is a relatively less explored area. Objective: The objective of this study is to aggregate, structure, and classify all existing research regarding alignment of RE and ST published by the end of 2015. Method: We conducted a systematic mapping study (SMS) and aggregated all studies relevant to our scope. The primary studies are analyzed in terms of publication trend, focus area, i.e., how alignment is supported, the application domain and benefits and challenges, methodological data, and scientific rigor and industrial relevance. Results: There is a growing interest towards the topic. Several different techniques have been identified to improve RE and ST alignment. Test generation from requirements specification has received most attention. Alignment of RE and ST is particularly important for large safety-critical domains. While many challenges have been reported, the supporting evidence for benefits is scarce. Frameworks/methods/techniques is the most frequent contribution type. Solution proposal and evaluation research were the most frequently applied research type. Case study research was the most frequently applied research method, however, almost half of the studies did not clearly report any research method. Conclusion: Despite the numerous approaches that are proposed, it is not clear what approach is suitable in what context and why. To support industry in RE and ST alignment, guidelines and tool support are needed. The supporting evidence for claimed benefits is very limited. Overall, the research area is in its early stages and an increase in both the number and rigor of empirical studies are required.

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Section: Focus Of Research (Rq2)mentioning

confidence: 99%

What Do We Know about Alignment of Requirements Engineering and Software Testing?

Karhapää

Haghighatkhah

Oivo

2017

Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering

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“…Software system functionalities are specified through requirements engineering artifacts, which are a valuable starting point for the software development [1]. Natural language is often used to write system requirements specifications as well as user requirements [2].…”

Section: Introductionmentioning

confidence: 99%

“…Natural language is often used to write system requirements specifications as well as user requirements [2]. According to [1], most of the software requirements specifications are written in natural language.…”

Section: Introductionmentioning

confidence: 99%

Automated Acceptance Tests as Software Requirements: An Experiment to Compare the Applicability of Fit Tables and Gherkin Language

Santos

Vilain

2018

Lecture Notes in Business Information Processing

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Abstract. It is estimated that 85% of the defects in the developed software are originated from ambiguous, incomplete and wishful thinking software requirements. Natural language is often used to write software requirements specifications as well as user requirements. However, natural language specifications can be confusing and hard to understand. Some agile methodologists consider that acceptance tests are more precise and accurate sources of information about the customer's needs than descriptions in natural language. Several studies have addressed the use of acceptance tests as software requirements specification. Therefore, none of the previous studies has performed experiments to compare the applicability of different acceptance testing techniques in order to support an organization in the selection of one technique over another. This paper addresses this problem reporting an experiment conducted with undergraduate students in Computer Science. This experiment compares the applicability of two acceptance testing techniques (Fit tables and Gherkin language) as software requirements specification. This research tries to answer three questions: (a) Which technique is the easiest to learn in order to specify acceptance test scenarios? (b) Which technique requires less effort to specify acceptance tests? (c) Which technique is the best one to communicate software requirements? The results show that there is no sufficient evidence to affirm that one technique is easier to specify test scenarios or better to communicate software requirements. Whereas, the comparison of effort in terms of time to specify acceptance testing shows that the mean time to specify test scenarios using Gherkin language is lower than Fit tables.

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“…Table 67 in Appendix 2). (2009) (Eshuis and Dehnert, 2003). They provided an algorithm for the generation of a reactive Petri-Net from textual use cases described using a formal syntax, and taking into account include and extend UML relationships and sequencing constraints using pre/post-conditions.…”

Section: Dynamic Analysis Of Software Requirements Specificationmentioning

confidence: 99%

“…Sinnig et al (2009) and Somé (2010) give some details for the integration of sequentially related scenarios.  The state explosion issue is a big problem when reachability graphs are generated for analysis of complex systems.…”

Section: Research Gapsmentioning

confidence: 99%

Analysis of Natural Language Scenarios

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C&L: Generating model based test cases from natural language requirements descriptions

Cited by 36 publications

References 10 publications

What Do We Know about Alignment of Requirements Engineering and Software Testing?

What Do We Know about Alignment of Requirements Engineering and Software Testing?

Automated Acceptance Tests as Software Requirements: An Experiment to Compare the Applicability of Fit Tables and Gherkin Language

Analysis of Natural Language Scenarios

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