| 1. |
- Aichernig, Bernhard K., et al.
(författare)
-
Model Learning and Model-Based Testing
- 2018
-
Ingår i: Machine Learning for Dynamic Software Analysis. - Heidelberg : Springer. - 9783319965611 - 9783319965628 ; , s. 74-100
-
Konferensbidrag (refereegranskat)abstract
- We present a survey of the recent research efforts in integrating model learning with model-based testing. We distinguished two strands of work in this domain, namely test-based learning (also called test-based modeling) and learning-based testing. We classify the results in terms of their underlying models, their test purpose and techniques, and their target domains. © Springer International Publishing AG
|
|
| 2. |
- Ali, Nauman bin, et al.
(författare)
-
On the search for industry-relevant regression testing research
- 2019
-
Ingår i: Empirical Software Engineering. - New York, NY : Springer. - 1382-3256 .- 1573-7616. ; 24:4, s. 2020-2055
-
Tidskriftsartikel (refereegranskat)abstract
- Regression testing is a means to assure that a change in the software, or its execution environment, does not introduce new defects. It involves the expensive undertaking of rerunning test cases. Several techniques have been proposed to reduce the number of test cases to execute in regression testing, however, there is no research on how to assess industrial relevance and applicability of such techniques. We conducted a systematic literature review with the following two goals: firstly, to enable researchers to design and present regression testing research with a focus on industrial relevance and applicability and secondly, to facilitate the industrial adoption of such research by addressing the attributes of concern from the practitioners' perspective. Using a reference-based search approach, we identified 1068 papers on regression testing. We then reduced the scope to only include papers with explicit discussions about relevance and applicability (i.e. mainly studies involving industrial stakeholders). Uniquely in this literature review, practitioners were consulted at several steps to increase the likelihood of achieving our aim of identifying factors important for relevance and applicability. We have summarised the results of these consultations and an analysis of the literature in three taxonomies, which capture aspects of industrial-relevance regarding the regression testing techniques. Based on these taxonomies, we mapped 38 papers reporting the evaluation of 26 regression testing techniques in industrial settings. © The Author(s) 2019
|
|
| 3. |
- Araujo, Hugo, et al.
(författare)
-
A Process for Sound Conformance Testing of Cyber-Physical Systems
- 2017
-
Ingår i: 2017 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW). - Los Alamitos, CA : IEEE Computer Society. - 9781509066766 - 9781509066773 ; , s. 46-50
-
Konferensbidrag (refereegranskat)abstract
- We present a process for sound conformance testing of cyber-physical systems, which involves functional but also non-functional aspects. The process starts with a hybrid model of cyber-physical systems in which the correct behavior of the system (at its interface level) is specified. Such a model captures both discrete behavior and evolution of continuous dynamics of the system in time. Since conformance testing inherently involves comparing continuous dynamics, the key parameters of the process are (1) the conformance bounds defining when two signals are sufficiently close to each other, and (2) the permitted error margin in the conformance analysis introduced by sampling of continuous signals. The final parameter of this process is (3) finding (and adjusting) the sampling rate of the dynamic behavior. In the specified process, we provide different alternatives for fixing the error margin of the conformance testing if the sampling rate is fixed, establishing the sampling rate if the error margin is fixed and finding conformance bounds once the sampling rate and the error margin are fixed. © 2017 IEEE.
|
|
| 4. |
- Taromirad, Masoumeh, 1982-, et al.
(författare)
-
Agile Requirements Traceability Using Domain-Specific Modelling Languages
- 2012
-
Ingår i: XM '12. - New York, NY : ACM Press. - 9781450318044 ; , s. 45-50
-
Konferensbidrag (refereegranskat)abstract
- Requirements traceability is an important mechanism for managing verification, validation and change impact analysis challenges in system engineering. Numerous model-based approaches have been proposed to support requirements traceability, but significant challenges remain, including finding the appropriate level of granularity for modelling traceability and coping with the lack of uniformity in requirements management tools. This paper argues for an agile modelling approach to managing requirements traceability and, in this context, proposes a domain/project-specific requirements traceability modelling approach. The preliminary approach is illustrated briefly in the context of the safety-critical systems engineering domain, where agile traceability from functional and safety requirements is necessary to underpin certification. © 2012 ACM.
|
|
| 5. |
- Taromirad, Masoumeh, 1982-, et al.
(författare)
-
Gray-Box Conformance Testing for Symbolic Reactive State Machines
- 2017
-
Ingår i: Fundamentals of Software Engineering. - Heidelberg : Springer Berlin/Heidelberg. - 9783319689715 - 9783319689722 ; , s. 228-243
-
Konferensbidrag (refereegranskat)abstract
- Model-based testing (MBT) is typically a black-box testing technique. Therefore, generated test suites may leave some untested gaps in a given implementation under test (IUT). We propose an approach to use the structural and behavioural information exploited from the implementation domain to generate effective and efficient test suites. Our approach considers both specification models and implementation models, and generates an enriched test model which is used to automatically generate test suites. We show that the proposed approach is sound and exhaustive and cover both the specification and the implementation. We examine the applicability and the effectiveness of our approach by applying it to a well-known example from the railway domain. © 2017, IFIP International Federation for Information Processing.
|
|
