No abstract

Software-intensive embedded systems have become an essential aspect of our lives. To cope with its growing complexity, modeling and model-driven engineering (MDE) are widely used for analysis, design, implementation, and testing of these systems. Since a large variety of software modeling practices is used in the domain of embedded software, it is important to understand and characterize thestate-of-the-practices and also the benefits, challenges and consequences of using software modeling approaches in this domain. The goal of this study is to investigate those practices in the embedded software engineering projects by identifying to what degree, why and how software modeling and MDE are used. To achieve this objective, we designed and conducted an online survey. Opinions of 627 practicing embedded software engineers from 27 different countries are included in the survey. The survey results reveal important and interesting findings about the state of software modeling and MDE practices in the worldwide embedded software industry. Among the results: (1) Different modeling approaches (from informal sketches to formalized models) are widely used in the embedded software industry with different needs and all of the usages could be effective depending on the various modeling characteristics; (2) The majority of participants use UML; and the second most frequently selected response is "Sketch/No formal modeling language", which shows the widespread informal usage of modeling; (3) In model-driven approaches, it is not so important to have a graphical syntax to represent the model (as in UML) and depending on the type of target embedded industrial sector, modeling stakeholders prefer models, which can represented in a format that is readable by a machine (as in DSL); (4) Sequence diagrams and state-machines are the two most popular diagram types; (5) Top motivations for adopting MDE are: cost savings, achieving shorter development time, reusability and quality improvement. The survey results will shed light on the state of software modeling and MDE practices and provide practical benefits to embedded software professionals (e.g., practitioners, researchers and also educators).

Context: Process models are key in facilitating communication in organizations and in designing process-aware information systems. Organizations are facing increasingly larger and more complex processes, which pose difficulties to the understandability of process models. The literature reports several factors that are considered to influence the understandability of process models. However, these studies typically focus on testing of a limited set of factors. A work that collects, abstracts and synthesizes an in-depth summary of the current literature will help in developing the research in this field. Objective: We conducted a systematic literature review (SLR) focusing on the empirical studies in the existing literature in order to better understand the state of the research on process model understandability, and identify the gaps and opportunities for future research. Method: We searched the studies between the years 1995 and 2015 in established electronic libraries. Out of 1066 publications retrieved initially, we selected 45 publications for thorough analysis. We identified, analyzed and categorized factors that are considered to influence the understandability of process models as studied in the literature using empirical methods. We also analyzed the indicators that are used to quantify process model understandability. Results: Our analysis identifies several gaps in the field, as well as issues of inconsistent findings regarding the effect of some factors, unbalanced emphasis on certain indicators, and methodological concerns. Conclusions: The existing research calls for comprehensive empirical studies to contribute to a better understanding of the factors of process model understandability. Our study is a comprehensive source for researchers working on the understandability of process models and related fields, and a useful guide for practitioners aiming to generate understandable process models.