Practitioners’ best practices to Adopt, Use or Abandon Model-based Testing with Graphical models for Software-intensive Systems

• Published in: Empirical software engineering : an international journal Vol. 27; no. 5; p. 103
• Main Authors: Alégroth, Emil, Karl, Kristian, Rosshagen, Helena, Helmfridsson, Tomas, Olsson, Nils
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2022; Springer Nature B.V
• Subjects: Automation; Best practice; Compilers; Computer Science; Embedded systems; Expert knowledge; Guidelines; Industrial study; Interpreters; Model testing; Model-based testing; Organizational aspects; Programming Languages; Semantics; Software; Software Engineering; Software Engineering/Programming and Operating Systems; Test automation; Expert knowledge; Test automation; Industrial study; Model-based testing; Software Engineering
• ISSN: 1382-3256; 1573-7616; 1573-7616
• DOI: 10.1007/s10664-022-10145-2

Model-based testing (MBT) has been extensively researched for software-intensive systems but, despite the academic interest, adoption of the technique in industry has been sparse. This phenomenon has been observed by our industrial partners for MBT with graphical models. They perceive one cause to be a lack of evidence-based MBT guidelines that, in addition to technical guidelines, also take non-technical aspects into account. This hypothesis is supported by a lack of such guidelines in the literature. Objective: The objective of this study is to elicit, and synthesize, MBT experts’ best practices for MBT with graphical models. The results aim to give guidance to practitioners and aspire to give researchers new insights to inspire future research. Method: An interview survey is conducted using deep, semi-structured, interviews with an international sample of 17 MBT experts, in different roles, from software industry. Interview results are synthesised through semantic equivalence analysis and verified by MBT experts from industrial practice. Results: 13 synthesised conclusions are drawn from which 23 best-practice guidelines are derived for the adoption, use and abandonment of the technique. In addition, observations and expert insights are discussed that help explain the lack of wide-spread adoption of MBT with graphical models in industrial practice. Conclusions: Several technical aspects of MBT are covered by the results as well as conclusions that cover process- and organizational factors. These factors relate to the mindset, knowledge, organization, mandate and resources that enable the technique to be used effectively within an organization. The guidelines presented in this work complement existing knowledge and, as a primary objective, provide guidance for industrial practitioners to better succeed with MBT with graphical models.