From use case maps to executable test procedures: a scenario-based approach

Kesserwan, Nader; Dssouli, Rachida; Stepien, Bernard; Labrèche, Pierre

doi:10.1007/s10270-017-0620-y

Cited by 9 publications

(9 citation statements)

References 19 publications

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“…Kesserwan et al [78] provide a model-driven testing methodology that supports test automation based on system requirements in NL. Using the methodology, the engineer first specifies system requirements according to Cockburn use case notation [79] and then manually refines them into Use Case Map (UCM) scenario models [80].…”

Section: Related Workmentioning

confidence: 99%

Automatic generation of system test cases from use case specifications

Wang

Pastore

Göknil

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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In safety critical domains, system test cases are often derived from functional requirements in natural language (NL) and traceability between requirements and their corresponding test cases is usually mandatory. The definition of test cases is therefore time-consuming and error prone, especially so given the quickly rising complexity of embedded systems in many critical domains. Though considerable research has been devoted to automatic generation of system test cases from NL requirements, most of the proposed approaches require significant manual intervention or additional, complex behavioral modelling. This significantly hinders their applicability in practice.In this paper, we propose Use Case Modelling for System Tests Generation (UMTG), an approach that automatically generates executable system test cases from use case specifications and a domain model, the latter including a class diagram and constraints. Our rationale and motivation are that, in many environments, including that of our industry partner in the reported case study, both use case specifications and domain modelling are common and accepted practice, whereas behavioural modelling is considered a difficult and expensive exercise if it is to be complete and precise. In order to extract behavioral information from use cases and enable test automation, UMTG employs Natural Language Processing (NLP), a restricted form of use case specifications, and constraint solving.

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Section: Related Workmentioning

confidence: 99%

Automatic generation of system test cases from use case specifications

Wang

Pastore

Göknil

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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“…To evaluate the extended testing methodology in this work, the experiment method described in [8] is reused to generate the test case. The new obtained result is a trace model (tracemodel.ecore) which relates UCM scenario models to TTCN-3 test cases grouped in test suites.…”

Section: B Traceability Links and Alignment With Test Resultsmentioning

confidence: 99%

“…In this paper, model transformation techniques are used to create traceability links among MBT artifacts during the test generation process. The approach extends previous testing methodology presented in [8] that generates tests based on behavioral models. This paper's contribution is building a traceability model to support the creation and persistence of such relationships among heterogeneous models representing various testing artifacts.…”

Section: Introductionmentioning

confidence: 94%

“…The TDL test scenario [DeploymentSucceeded] is transformed into a test case in TTCN-3. The approach defined in [8] applies structural transformation where each TDL element is transformed into a number of TTCN-3 modules. Based on transformation rules, the resulting test case is composed of three types of modules: (1) a Test Configuration module, (2) a Test Description module, (3) and a Data module.…”

Section: A Test Cases and Trace Model Generationmentioning

confidence: 99%

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Model-driven Framework for Requirement Traceability

Kesserwan¹,

Al-Jaroodi²

2021

IJACSA

Self Cite

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In software development, requirements traceability is often mandated. It is important to apply to support various software development activities like result evaluation, regression testing and coverage analysis. Model-Driven Testing is one approach to provide a way to verify and validate requirements. However, it has many challenges in test generation in addition to the creation and maintenance of traceability information across test-related artifacts. This paper presents a model-based methodology for requirements traceability that relies on leveraging model transformation traceability techniques to achieve compliance with DO-178C standard as defined in the software verification process. This paper also demonstrates and evaluates the proposed methodology using avionics case studies focusing on the functional aspects of the requirements specified with the UCM (Use Case Maps) modeling language.

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“…Kesserwan et al [86] provide a model-driven testing methodology that supports test automation based on system requirements in NL. Using the methodology, the engineer first specifies system requirements according to Cockburn use case notation [87] and then manually refines them into Use Case Map (UCM) scenario models [88].…”

Section: Related Workmentioning

confidence: 99%

Automatic Generation of Acceptance Test Cases From Use Case Specifications: An NLP-Based Approach

Wang

Pastore

Göknil

et al. 2022

IIEEE Trans. Software Eng.

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Acceptance testing is a validation activity performed to ensure the conformance of software systems with respect to their functional requirements. In safety critical systems, it plays a crucial role since it is enforced by software standards, which mandate that each requirement be validated by such testing in a clearly traceable manner. Test engineers need to identify all the representative test execution scenarios from requirements, determine the runtime conditions that trigger these scenarios, and finally provide the input data that satisfy these conditions. Given that requirements specifications are typically large and often provided in natural language (e.g., use case specifications), the generation of acceptance test cases tends to be expensive and error-prone. In this paper, we present Use Case Modeling for System-level, Acceptance Tests Generation (UMTG), an approach that supports the generation of executable, system-level, acceptance test cases from requirements specifications in natural language, with the goal of reducing the manual effort required to generate test cases and ensuring requirements coverage. More specifically, UMTG automates the generation of acceptance test cases based on use case specifications and a domain model for the system under test, which are commonly produced in many development environments. Unlike existing approaches, it does not impose strong restrictions on the expressiveness of use case specifications. We rely on recent advances in natural language processing to automatically identify test scenarios and to generate formal constraints that capture conditions triggering the execution of the scenarios, thus enabling the generation of test data. In two industrial case studies, UMTG automatically and correctly translated 95% of the use case specification steps into formal constraints required for test data generation; furthermore, it generated test cases that exercise not only all the test scenarios manually implemented by experts, but also some critical scenarios not previously considered.

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From use case maps to executable test procedures: a scenario-based approach

Cited by 9 publications

References 19 publications

Automatic generation of system test cases from use case specifications

Automatic generation of system test cases from use case specifications

Model-driven Framework for Requirement Traceability

Automatic Generation of Acceptance Test Cases From Use Case Specifications: An NLP-Based Approach

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