ON THE THEORETICAL FOUNDATIONS OF RESEARCH INTO THE UNDERSTANDABILITY OF BUSINESS PROCESS MODELS

Against the background of the growing significance of Business Process Management (BPM) for Information Systems (IS) research and practice, especially the field of Business Process Modeling gains more and more importance. Business process models support communication about as well as the coordination of processes and have become a widely adopted tool in practice. As the understandability of business process models plays a crucial role in communication processes, more and more studies on process model understandability have been conducted in IS research. This article aims at investigating underlying theories of research into business process model understandability by means of an in-depth analysis of 126 systematically retrieved research articles on the topic. It shows in how far process model understandability research is multi-theoretically founded. Identified theories differ regarding addressed subject matters, their coverage, their focus as well as the underlying notion of model understanding, which is exemplarily demonstrated and discussed in this article. Moreover, implications of the findings are discussed and an outlook on future business process model understandability research and on the integration potential of theories in this field is given

An examination of the complexity and comprehensibility of various software models

In a discussion of the creation and evolution of the statechart, David Harel, the creator of the model, talks about his primary goals for making a good model. He emphasizes that a good model should be clear, precise, visualizable, and executable. A clear model is one that can be easily understood by someone unfamiliar with the system being modeled. A precise model shows the entirety of the system under consideration, without including extraneous information. A visualizable model is one that can be interpreted by a user using primarily visual information, meaning some words must exist for thing like labels, but the majority of the information contained in the model is expressed through symbols that are easily understandable. An executable model is one that can be developed and then applied to help users understand or even create the system that is modeled. These ideas are indeed very important to the usefulness of a model, as a model that is lacking in one or more of these areas could be difficult to understand, use, or both. Today, however, there are dozens of different models that aim to show different aspects of systems, and many of these models may not have been designed with the same goals that Harel outlines. This paper aims to examine the complexity of various software models, including UML models and other commonly used models. I will look at each model and attempt to determine areas of the model that are particularly hard to understand, or areas where ambiguity is possible within the model. I will discuss the implications that model complexity has on a persons ability to learn the model and to recall it at a later date. I will also discuss ways to improve a persons ability to remember the aspects of a model when they are an infrequent user or when they have not encountered that model in a long time

How Conceptual Modeling Is Used

Conceptual models play an increasingly important role for business process engineering, information systems development, and customizing of Enterprise Resource Planning (ERP) systems. Despite the widespread interest in conceptual modeling, relatively little is known to date on the level and nature of conceptual modeling use in practice. Therefore our study investigates how practitioners use conceptual modeling. In particular, we address the following three key questions: To what extent do practitioners use conceptual modeling techniques and tools? How relevant is conceptual modeling for certain purposes? Are there barriers and success factors in using conceptual modeling? This paper informs information systems professionals about recent trends in the area of conceptual modeling. The results of our study should be considered when developing syllabuses for modeling courses as well as when judging the relevance of various research streams in the area of conceptual modeling

Investigating expressiveness and understandability of hierarchy in declarative business process models

Hierarchy has widely been recognized as a viable approach to deal with the complexity of conceptual models. For instance, in declarative business process models, hierarchy is realized by sub-processes. While technical implementations of declarative sub-processes exist, their application, semantics, and the resulting impact on understandability are less understood yet—this research gap is addressed in this work. More specifically, we discuss the semantics and the application of hierarchy and show how subprocesses enhance the expressiveness of declarative modeling languages. Then, we turn to the influence of hierarchy on the understandability of declarative process models. In particular, we present a cognitive-psychology-based framework that allows to assess the impact of hierarchy on the understandability of a declarative process model. To empirically test the proposed framework, a combination of quantitative and qualitative research methods is followed. While statistical tests provide numerical evidence, think-aloud protocols give insights into the reasoning processes taking place when reading declarative process models

Assessing the effectiveness of sequence diagrams in the comprehension of functional requirements: results from a family of five experiments

Modeling is a fundamental activity within the requirements engineering process and concerns the construction of abstract descriptions of requirements that are amenable to interpretation and validation. The choice of a modeling technique is critical whenever it is necessary to discuss the interpretation and validation of requirements. This is particularly true in the case of functional requirements and stakeholders with divergent goals and different backgrounds and experience. This paper presents the results of a family of experiments conducted with students and professionals to investigate whether the comprehension of functional requirements is influenced by the use of dynamic models that are represented by means of the UML sequence diagrams. The family contains five experiments performed in different locations and with 112 participants of different abilities and levels of experience with UML. The results show that sequence diagrams improve the comprehension of the modeled functional requirements in the case of high ability and more experienced participants.The authors wish to thank all the participants in the experiments. This research was partially supported by the MULTIPLE project (with ref. TIN2009-13838).Abrahao Gonzales, SM.; Gravino, .C.; Insfrán Pelozo, CE.; Scaniello, .G.; Tortora, .G. (2013). Assessing the effectiveness of sequence diagrams in the comprehension of functional requirements: results from a family of five experiments. IEEE Transactions on Software Engineering. 39(3):327-342. https://doi.org/10.1109/TSE.2012.27S32734239

A test case generation framework based on UML statechart diagram

Early software fault detection offers more flexibility to correct errors in the early development stages. Unfortunately, existing studies in this domain are not sufficiently comprehensive in describing the major processes of the automated test case generation. Furthermore, the algorithms used for test case generation are not provided or well described. Current studies also hardly address loops and parallel paths issues, and achieved low coverage criteria. Therefore, this study proposes a test case generation framework that generates minimized and prioritized test cases from UML statechart diagram with higher coverage criteria. This study, conducted a review of the previous research to identify the issues and gaps related to test case generation, model-based testing, and coverage criteria. The proposed framework was designed from the gathered information based on the reviews and consists of eight components that represent a comprehensive test case generation processes. They are relation table, relation graph, consistency checking, test path minimization, test path prioritization, path pruning, test path generation, and test case generation. In addition, a prototype to implement the framework was developed. The evaluation of the framework was conducted in three phases: prototyping, comparison with previous studies, and expert review. The results reveal that the most suitable coverage criteria for UML statechart diagram are all-states coverage, all-transitions coverage, alltransition-pairs coverage, and all-loop-free-paths coverage. Furthermore, this study achieves higher coverage criteria in all coverage criteria, except for all-state coverage, when compared with the previous studies. The results of the experts’ review show that the framework is practical, easy to implement due to it is suitability to generate the test cases. The proposed algorithms provide correct results, and the prototype is able to generate test case effectively. Generally, the proposed system is well accepted by experts owing to its usefulness, usability, and accuracy. This study contributes to both theory and practice by providing an early alternative test case generation framework that achieves high coverage and can effectively generate test cases from UML statechart diagrams. This research adds new knowledge to the software testing field, especially for testing processes in the model-based techniques, testing activity, and testing tool support

Understanding understandability of conceptual models - what are we actually talking about? - Supplement

Investigating and improving the quality of conceptual models has gained tremendous importance in recent years. In general, model understandability is regarded one of the most important model quality goals and criteria. A considerable amount of empirical studies, especially experiments, have been conducted in order to investigate factors in-fluencing the understandability of conceptual models. However, a thorough review and reconstruction of 42 experiments on conceptual model understandability shows that there is a variety of different understandings and conceptualizations of the term model understandability. As a consequence, this term remains ambiguous, research results on model understandability are hardly comparable and partly imprecise, which shows the necessity of clarification what the conceptual modeling community is actually talking about when the term model understandability is used. This contribution represents a supplement to the article „ Understanding understandability of conceptual models – What are we actually talking about?” published in the Proceedings of the 31st International Conference on Conceptual Modeling (ER 2012) which aimed at overcoming the above mentioned shortcoming by investigating and further clarifying the concept of model understandability. This supplement contains a complete overview of Table 1 (p. 69 in the original contribution) which could only be partly presented in the conference proceedings due to space limitations. Furthermore, an erratum concerning the overview in Table 2 (p. 71 in the original contribution) is presented

UML models consistency management: guidelines for software quality manager

Unified Modeling Language (UML) has become the de-facto standard to design today’s large-size object-oriented systems. However, focusing on multiple UML diagrams is a main cause of breaching the consistency problem, which ultimately reduces the overall software model’s quality. Consistency management techniques are widely used to ensure the model consistency by correct model-to-model and model-to-code transformation. Consistency management becomes a promising area of research especially for model-driven architecture. In this paper, we extensively review UML consistency management techniques. The proposed techniques have been classified based on the parameters identified from the research literature. Moreover, we performed a qualitative comparison of consistency management techniques in order to identify current research trends, challenges and research gaps in this field of study. Based on the results, we concluded that researchers have not provided more attention on exploring inter-model and semantic consistency problems. Furthermore, state-of-the-art consistency management techniques mostly focus only on three UML diagrams (i.e., class, sequence and state chart) and the remaining UML diagrams have been overlooked. Consequently, due to this incomplete body of knowledge, researchers are unable to take full advantage of overlooked UML diagrams, which may be otherwise useful to handle the consistency management challenge in an efficient manner