Less is More: A Minimalistic Approach to UML Model-Based Conformance Test Generation

Kaplan, Marc; Klinger, Tim; Paradkar, Amit; Sinha, Avik; Williams, Clay; Yılmaz, Cemal

doi:10.1109/icst.2008.48

Cited by 17 publications

(13 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar to UMTG, Kaplan et al [89] propose another approach, i.e., Archetest, which generates test sequences and test inputs from a domain model and use case specifications together with invariants, guardconditions and postconditions. Yue et al [20] propose a test case generation tool (aToucan4Test), which takes RUCM use case specifications annotated with OCL constraints as input and generates automatically executable test cases.…”

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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…Some research tools already create test cases from models, such as UML models [12]. Since we generate models from text, we should be able to use such test generation tools directly.…”

Section: Test Cases From Modelsmentioning

confidence: 99%

Text to software

Tichy

Koerner

2010

Proceedings of the FSE/SDP Workshop on Future of Software Engineering Research

View full text Add to dashboard Cite

Software development relies heavily on manual processes for transforming requirements into software artifacts such as models, source code, or test cases. Requirements are the starting point for these transformations, and they are typically written in natural language. However, hardly any automated tools exist that translate natural language texts into software artifacts.We propose to adapt recent advances in natural language processing and semantic technologies to generate UML models, test cases, and perhaps even source code, from natural language input. Though earlier efforts in automatic programming had limited success, we are now in a situation where extracting meaning from text has made substantial progress. For example, encouraging results for generating UML models from textual requirements have been achieved. It might even be possible to generate executable test cases. An intermediate step would be to generate tests from API documentation (which would also be a useful capability in itself). An even greater advance would be to automate rote coding.In all of these cases, entirely new classes of software tools would be needed to extract and process the semantics inherent in natural language texts, augment them with tacit knowledge from ontologies and domain models, and, where necessary, ask humans to clarify ambiguities.Though speculative, a determined, long-term effort in translating text to software could automate and accelerate software development to an unprecedented degree.

show abstract

“…The original approaches to symbolic execution were proposed in the 70s and 80s and address sequential programs with simple inputs of a limited set of primitive types [BEL75,Cla76,Kin76,RHC76]. This is mostly because of limitations of automated theorem provers in dealing with complex path conditions and some program types (for instance, floating point arithmetics).…”

Section: Symbolic Executionmentioning

confidence: 99%

“…Test generation techniques that rely on symbolic execution execute the program with symbolic input values, and compute expressions on the input values that indicate the conditions to execute a given path [Kin76]. Symbolic executors rely on automated theorem provers to generate test cases that cover the corresponding program paths.…”

Section: Symbolic Executionmentioning

confidence: 99%

Dynamic data-flow testing

Vivanti

2014

Companion Proceedings of the 36th International Conference on Software Engineering

View full text Add to dashboard Cite

Less is More: A Minimalistic Approach to UML Model-Based Conformance Test Generation

Cited by 17 publications

References 10 publications

Automatic generation of system test cases from use case specifications

Automatic generation of system test cases from use case specifications

Text to software

Dynamic data-flow testing

Contact Info

Product

Resources

About