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

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

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.

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.

Traceability is an important concern in projects that span dierent engineering domains. Traceability can also be mandated, exploited and managed across the engineering lifecycle, and may involve defining connections between heterogeneous models. As a result, traceability can be considered to be multi-domain.

This thesis introduces the concept and challenges of multi-domain traceability and explains how it can be used to support typical traceability scenarios. It proposes a model-based approach to develop a traceability solution which eectively operates across multiple engineering domains. The approach introduced a collection of tasks and structures which address the identified challenges for a traceability solution in multi-domain projects. The proposed approach demonstrates that modelling principles and MDE techniques cab help to address current challenges and consequently improve the eectiveness of a multi-domain traceability solution.

A prototype of the required tooling to support the approach is implemented with EMF and atop Epsilon; it consists of an implementation of the proposed structures (models) and model management operations to support traceability. Moreover, the approach is illustrated in the context of two safety-critical projects where multi-domain traceability is required to underpin certification arguments.

Traceability is an important concern in projects that span different engineering domains. In such projects, traceability can be used across the engineering lifecycle and therefore is multi-domain, involving heterogeneous models. We introduce the concept and challenges of multi-domain traceability and explain how it can be used to support traceability scenarios. We describe how to build a multi-domain traceability framework using Model-Driven Engineering. The approach is illustrated in the context of the safety-critical systems engineering domain where multi-domain traceability is required to underpin certification arguments.

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.