دانلود رایگان مقاله انگلیسی رویکرد مدلسازی فرایند محور برای توسعه گرافیکی برنامه های کسب و کار موبایلی - الزویر 2018

abstract

Mobile app development is an activity predominantly performed by software developers. Domain experts and future users are merely considered in early development phases as source of requirements or consulted for evaluating the resulting product. In the domain of business apps, many cross-platform programming frameworks exist but approaches also targeted at non-technical users are rare. Existing graphical notations for describing apps either lack the simplicity to be understandable by domain experts or are not expressive enough to support automated processing. The MAML framework is proposed as modeldriven approach for describing mobile apps in a platform-agnostic fashion not only for software developers but also for process modelers and domain experts. Data, views, business logic, and user interactions are jointly modeled from a process perspective using a graphical domain-specific language. To aggregate multiple use cases and provide advanced modeling support, an inference mechanism is utilized to deduce a global data model. Through model transformations, native apps are then automatically generated for multiple platforms without manual programming. Our approach is compared to the IFML notation in an observational study, with promising results regarding readability and usability.

Conclusion and outlook

In this article, the MAML framework was proposed to model mobile apps using a declarative graphical DSL. In contrast to the current practice of graphically configuring user interfaces by positioning UI elements on a screen-like canvas, MAML focuses on a process-centric definition of business apps. Using a sequence of platform-agnostic process elements, the notation aligns with the business perspective of managing processes and data flows, and makes app development accessible to domain users without software engineering experience. The approach is based on existing work on cross-platform business app generation and uses model-driven techniques to transform the models first into an intermediate textual representation before generating platform-specific source code. In particular, a data model inference mechanism was presented that enables real-time validation and consistency checks on partial data models, and overcomes the need for explicitly modeling a global data schema. Moreover, the inferred data can be used to provide contextual modeling support and enhanced semantic validation in the editor component. An empirical evaluation study supports the advantage of MAML over the related technical IFML notation, specifically with regard to its readability by domain experts. MAML therefore achieves the desired balance of abstracting programming-heavy tasks to understandable process flows while keeping the technical expressiveness required for automatic source code generation for multiple target platforms.