Christoph Rieger

Conquering the Mobile Device Jungle:Towards a Taxonomy for App-Enabled Devices

Applications for mobile devices (apps) have created an ecosystem that facilitated a trend towards task-oriented, interoperable software. Following smartphones and tablets, many further kinds of devices became (and still become) app-enabled. Examples for this trend are smart TVs and cars. Additionally, new types of devices have appeared, such as Wearables. App-enabled devices typically share some characteristics, and many ways exist to develop for them. So far for smartphones and tablets alone, issues such as device fragmentation are discussed and technology for cross-platform development is scrutinized. Increasingly, app-enabled devices appear to be a jungle: It becomes harder to keep the overview, to distinguish and categorize devices, and to investigate similarities and differences. We, thus, set out with this position paper to close this gap. In our view, a taxonomy for app-enabled devices is required. This paper presents the first steps towards this taxonomy and thereby invites for discussion.

Refining a Reference Architecture for Model-Driven Business Apps

Despite much progress, cross-platform app development frameworks remain a topic of active research. While frameworks that yield native apps are particularly attractive, their spread is very limited. It is apparent that (theoretical) technological superiority needs to be accompanied with profound support for developers and adequate capabilities for maintaining the framework itself. We deem so called reference architectures to be a major step for building better cross-platform app development frameworks, particularly if they are based on techniques of model-driven software development (MDSD). In this paper, we describe a refinement of a reference architecture for business apps. We employ the model-driven cross-platform development framework MD2 for this purpose. Its general design has been described extensively in the literature. The framework has a sound foundation in MDSD, yet lacks a generator support that fulfils the above sketched goals. After describing the required background, we argue in detail for a suitable reference architecture. While it will be a valuable addition to the MD2 framework, the discussion of our findings also makes a contribution for generative app development in general.

A process-oriented modeling approach for graphical development of mobile business apps

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 model-driven 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.

Weighted Evaluation Framework for Cross-Platform App Development Approaches

Cross-platform app development is very challenging, although only two platforms with significant market share (iOS and Android) remain. While device fragmentation – multiple, only partly compatible versions of a platform – has been complicating matters already, the need to target different device classes is a new emergence. Smartphones and tablets are relatively similar but app-enabled devices such as TVs and even cars typically have differing capabilities. To facilitate usage of cross-platform app development approaches, we present work on an evaluation framework. Our framework provides a set of up-to-date evaluation criteria. Unlike prior work on this topic, it offers weighted assessment to cater for varieties in targeted device classes. Besides motivating and explaining the evaluation criteria, we present an exemplary application for one development approach and, as benchmarks, for native apps and Webapps. Our findings suggest that the proliferation of app-enabled devices amplifies the need for improved development support.

Business apps with MAML: a model-driven approach to process-oriented mobile app development

Business apps support the digitalization of business operations by utilizing the potential of ubiquitous mobile devices. Whereas many frameworks for programming cross-platform apps exist, few modeling approaches focus on platform-agnostic representations of mobile apps. In addition, development is mainly executed by software developers, while domain experts are rarely involved in the actual app creation. The MAML framework is proposed as model-driven approach also targeting non-technical users. Data, views, business logic, and user interactions are jointly modeled from a process perspective using a graphical domain-specific language. An inference mechanism is presented to merge partial data models into a global specification. Through model transformations, apps are then automatically generated for multiple platforms without writing code manually.

Challenges and Opportunities of Modularizing Textual Domain-Specific Languages

Over time, domain-specific languages (DSL) tend to grow beyond the initial scope in order to provide new features. In addition, many fundamental language concepts are reimplemented over and over again. This raises questions regarding opportunities of DSL modularization for improving software quality and fostering language reuse – similar to challenges traditional programming languages face but further complicated by the surrounding editing infrastructure and model transformations. Mature frameworks for developing textual DSLs such as Xtext provide a wealth of features but have only recently considered support for language composition. We therefore perform a case study on a large-scale DSL for model-driven development of mobile applications called MD2, and review the current state of DSL composition techniques. Subsequently, challenges and advantages of modularizing MD2 are discussed and generalized recommendations are provided.

Towards Model-Driven Business Apps for Wearables

With the rise of wearable devices expected to continue in the near future, traditional approaches of manually developing apps from scratch for each platform reach their limits. On the other hand, current cross-platform approaches are usually limited to platforms for smartphones and tablets. The model-driven paradigm seems well suited for developing apps for novel and heterogeneous devices. However, one of the main challenges for establishing a model-driven framework for wearables consists of bridging the variety of user interfaces and considering different capabilities of device input and output. This paper seeks to investigate the challenges of app development for wearable devices regarding user interfaces and discusses a possible mapping of typical application building blocks in the domain of business apps. Ultimately, apps modelled on a task-oriented level of abstraction using platform-independent notations such as MAML or CTT can then be transformed into code that adopts device class specific representations.

Interoperability of BPMN and MAML for Model-Driven Development of Business Apps

With process models widely used as means for documentation and monitoring of business activities, the conversion into executable software often still remains a manual and time-consuming task. The MAML framework was developed to ease the creation of mobile business apps by jointly modeling process, data, and user interface perspectives in a graphical, process-oriented model for subsequent code generation. However, this domain-specific notation cannot benefit from existing process knowledge which is often encoded in BPMN models. The purpose of this paper is to analyze conceptual differences between both notations from a software development perspective and provide a solution for interoperability through a model-to-model transformation. Therefore, workflow patterns identified in previous research are used to compare both notations. A conceptual mapping of supported concepts is presented and technically implemented using a QVT-O transformation to demonstrate an automated mapping between BPMN and MAML. Consequently, it is possible to simplify the automatic generation of mobile apps by reusing processes specified in BPMN.

A Taxonomy for App-Enabled Devices: Mastering the Mobile Device Jungle

While the term application is known for a long time, what we now refer to as mobile apps has facilitated task-oriented, interoperable software. The term was initially only used for smartphones and tablets, but desktop software now is also referred to as apps. More important than the wording, however, is the trend towards app-enablement of many further kinds of devices such as smart TVs and wearables. App-enabled devices usually share some characteristics and developing apps is often similar. However, many complexities must be mastered: Device fragmentation and cross-platform app development already are challenging when only considering smartphones. When trying to grasp the field as a whole, app-enabled devices appear as a jungle: it becomes increasingly hard to get an overview. Devices might not be easy to categorize let alone to compare. Investigating similarities and differences is not straightforward, as the outer appearance might be deceiving, and technological peculiarities are often complex in nature. This article aims at mastering the jungle. For this purpose, we propose a taxonomy for app-enabled devices. It provides clear terms and facilitates precision when discussing devices. Besides presenting the taxonomy and the rationale behind it, this article invites for discussion.

A Domain-specific Language for Configurable Traceability Analysis.

In safety-critical industries such as the aviation industry or the medical industry traceability is required by law and specific regulations. In addition, process models such as CMMI require traceability information for documentation purposes. Although creating and maintaing so-called traceability information models (TIM) takes a lot of effort, its potential for reporting development progress, supporting project management, and measuring software quality often remains untapped. The domain-specific language presented in this paper builds on an existing traceability solution and allows to define queries, metrics, and rules for companyor project-specific usage. The basis for such an analysis is a query expression to retrieve information from a TIM. Customizable metrics are then defined to compute aggregated values, which are evaluated against companyor project-specific thresholds using the rules part of the domain-specific language. The focus of this paper is to show how the combination of query, metric, and rule expressions is used to define and compute customizable analyses based on individual requirements.