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Models to code : with no mysterious gaps
Learn how to translate an executable model of your application into running code. This is not a book about theory, good intentions or possible future developments. You'll benefit from translation technology and solid software engineering principles that are demonstrated with concrete examples using an open source tool chain. Models don't deliver enough value if they are not on a direct path to code production. But to waste time building models that are merely pictures of your code doesn't add much value either. In this book, you'll translate detailed, yet platform-independent models that solve real application problems. Using a pragmatic approach, Models to Code quickly dives into two case studies of Executable UML models. The models and code are extensively annotated and illustrate key principles that are emphasized throughout the book. You'll work with code production using \"C\" as the implementation language and targeting microcomputer class processors. This might not be your particular target language or platform, but you can use you can use what you learn here to engineer or re-evaluate your own code translation system to dramatically increase the value of both your modeling and code generation solution. Written by three leading experts, Models to Code is an exceptional resource for producing software by model translation-- add it to your library today.
Book
On the assessment of generative AI in modeling tasks: an experience report with ChatGPT and UML
Most experts agree that large language models (LLMs), such as those used by Copilot and ChatGPT, are expected to revolutionize the way in which software is developed. Many papers are currently devoted to analyzing the potential advantages and limitations of these generative AI models for writing code. However, the analysis of the current state of LLMs with respect to software modeling has received little attention. In this paper, we investigate the current capabilities of ChatGPT to perform modeling tasks and to assist modelers, while also trying to identify its main shortcomings. Our findings show that, in contrast to code generation, the performance of the current version of ChatGPT for software modeling is limited, with various syntactic and semantic deficiencies, lack of consistency in responses and scalability issues. We also outline our views on how we perceive the role that LLMs can play in the software modeling discipline in the short term, and how the modeling community can help to improve the current capabilities of ChatGPT and the coming LLMs for software modeling.
Journal Article
RM4ML: requirements model for machine learning-enabled software systems
Machine learning (ML)-enabled is one of the appealing characteristics of modern software systems, which usually contain ML components to make the system more intelligent for easier living. Requirements for ML-enabled software systems involve functional, quality, environmental, and data requirements. UML is a de facto approach for requirements analysis and system design, but its current modeling capabilities do not yet cover ML-enabled software systems to describe software quality requirements, environmental requirements, and data requirements. In this paper, we propose a requirements model for ML-enabled software systems and a modeling process for this model based on an extension of UML. In addition, we demonstrate the proposed model and modeling process through the case of the Tesla Autopilot system. The results show that the proposed model is expressive and usable and has a low learning curve when the software developers have basic knowledge of UML. Our proposed model can be further implemented and used in industrial settings.
Journal Article
Uncertainty representation in software models: a survey
This paper provides a comprehensive overview and analysis of research work on how uncertainty is currently represented in software models. The survey presents the definitions and current research status of different proposals for addressing uncertainty modeling and introduces a classification framework that allows to compare and classify existing proposals, analyze their current status and identify new trends. In addition, we discuss possible future research directions, opportunities and challenges.
Journal Article
Execution of UML models: a systematic review of research and practice
Several research efforts from different areas have focused on the execution of UML models, resulting in a diverse and complex scientific body of knowledge. With this work, we aim at identifying, classifying, and evaluating existing solutions for the execution of UML models. We conducted a systematic review in which we selected 63 research studies and 19 tools among over 5400 entries by applying a systematic search and selection process. We defined a classification framework for characterizing solutions for UML model execution, and we applied it to the 82 selected entries. Finally, we analyzed and discussed the obtained data. From the analyzed data, we drew the following conclusions: (i) There is a growing scientific interest on UML model execution; (ii) solutions providing translational execution clearly outnumber interpretive solutions; (iii) model-level debugging is supported in very few cases; (iv) only a few research studies provide evidence of industrial use, with very limited empirical evaluations; (v) the most common limitation deals with coverage of the UML language. Based on these observations, we discuss potential research challenges and implications for the future of UML model execution. Our results provide a concise overview of states of the art and practice for UML model execution intended for use by both researchers and practitioners.
Journal Article
iStar2uml: toward automatic generation of UML model from iStar model
Requirements engineering focuses on eliciting, specifying, transforming and validating user and system requirements correctly and efficiently. Transforming user requirements to system requirements is a critical step in this process. It is a challenging because the high-level intentions of users often lack the detailed information to help specify system requirements. In practice, the successful transformation from user requirements to system requirements is labor-intensive, which requires the sophisticated human efforts of domain experts and developers for information processing and supplementation. It is desirable to have a method for automatically transforming user requirements into system requirements. In this paper, we propose an approach iStar2UML that can automatically transform the user requirements of iStar into the system requirements specified by UML models. iStar is a well-known goal-oriented model for eliciting and specifying user requirements; it concentrates on analyzing intentions and social dependencies of stakeholders. Unified Modeling Language (UML) is a de facto standard for object-oriented system requirements modeling and design. We evaluate the proposed approach through five case studies. The results indicate that 82.9% of UML models were successfully generated from iStar models and confirmed by domain experts. Additionally, the proposed transformation approach reduced transformation errors by an average of 11.7% and time costs by 21.4% compared to a fully manual approach. Overall, the results suggest the approach is effective, though further validation is necessary. The proposed approach can be extended and applied for the requirements engineering processes in the software industry.
Journal Article
A novel approach with an extensive case study and experiment for automatic code generation from the XMI schema Of UML models
Software models at different levels of abstraction and from different perspectives contribute to the creation of compilable code in the implementation phase of the SDLC. Traditionally, the development of the code is a human-intensive act and prone to misinterpretation and defects. The defect elimination process is again an arduous time-consuming task with increased time-to-deliver and cost. Hence, a novel approach is proposed to generate the code with the activity diagram and sequence diagram as the focus. The activity diagram and sequence diagrams and are defined as part of the UML definition to define the object flow of the system and interaction between the objects, respectively. An XMI schema is a text representation of any software model that is exported from a modeling tool. The modeling tool BoUML exports the required schema from the given input models such as sequence diagrams and activity diagrams. The proposed JC_Gen extracts artifacts from the XMI schema of these two models to generate the code automatically. The focus is mainly on class definition, member declaration, methods’ definition, and function call in generated code.
Journal Article
Design of classical-quantum systems with UML
Developers of the many promising quantum computing applications that currently exist are urging companies in many different sectors seriously consider integrating this new technology into their business. For these applications to function, not only are quantum computers required, but quantum software also. Accordingly, quantum software engineering has become an important research field, in that it attempts to apply or adapt existing methods and techniques (or propose new ones) for the analysis, design, coding, and testing of quantum software, as well as playing a key role in ensuring quality in large-scale productions. The design of quantum software nevertheless poses two main challenges: the modelling of software quantum elements must be done in high-level modelling languages; and the need to further develop so-called “hybrid information systems”, which combine quantum and classical software. To address these challenges, we first propose a quantum UML profile for analysing and designing hybrid information systems; we then demonstrate its applicability through various structural and behavioural diagrams such as use case, class, sequence, activity, and deployment. In comparison to certain other quantum domain-specific languages, this UML profile ensures compliance with a well-known international standard that is supported by many tools and is followed by an extensive community.
Journal Article