Using the FOMDA Approach to Support Object-Oriented Real-Time Systems Development

Abstract

This paper tackles the problem of ever changing embedded systems non-functional requirements, specially the architectural ones. It proposes a solution based on Features Model and MDA standards, which is called FeaturesOriented Model-Driven Architecture (FOMDA). This proposal can be used to help application designer in defining the mappings and transformations of UML models to as many target platforms as wished. This is done by configuring model-to-model and model-to-code transformations over tiers, where every tier represents some target platform properties that the system must be mapped and transformed to. To validate the proposal a case study related to the development of an embedded real-time system is presented, detailing how to transform a generic high-level UML model to a model specific for a given target platform. Obtained results are optimistic and conclude that the FOMDA approach can make designers re-think their current development process to make it more decoupled from a specific target platform.

Extending JUnit 4 with Java annotations and reflection to test variant model transformation assets

“…This experience reported by example is relevant for studies related to reuse techniques, applied in model transformations in following works [11] [14][32] [37] [2]. FOMDA (Features-Oriented Model-Driven Architecture) is a methodology to specify generative and dynamic model transformation chains [4]. In order to support these specifications, WCT is a tool that allows designing and also executing transformations based on three kinds of assets: Feature Model [18] A platform domain model (PDM) [35] is represented a Features Model (illustrated in Figure 1 (A) and Figure 2) that exposes the system's characteristics.…”

“…With support of WCT, one can fragment a transformation into independent modules that are used in runtime or combined through generative techniques discussed in [4] [5]. These elements are also abstractions illustrated in Figure 3 (A) with model elements named "implSpecPoint" and "extSpecPoint".…”

“…We introduce this solution into a model transformation engine, namely WCT [5]. The validation of this work is a set of automated test cases that deals with a complex and real scenario in adapting large scale transformations, presenting some results in comparison with previous experiences in [4]. This paper is organized as follows.…”

“…Moreover, their study is focused in reusing textual guidance for test cases, not in adapting automated test cases.Our work is complementary and presents a contribution in comparison to related works. In order to provide a specific solution to test variant model transformation assets, our contribution facilitates the specification of automated JUnit test cases.In this sense, our contribution is directly important to test model transformation assets specified and generated through some related works as follows: 1) Almeida et al proposed a solution to compose model transformations in MTCs[1]; 2) Boas proposed the design of a MTC using workflow to model a transformation process according MDA views[8]; 3) Basso et al[4] and Völter et al[37] applied SPL-based techniques to specify dynamic MTC; 4) Vanhooff et al proposed a MTC modeling language to generate specifications used by some transformation execution engines[36] and Wagelaar et al proposed a framework to chain black-box model transformations[38], similar as those exemplified in Section 3; 5) Etien et al complemented these works to include validation for metamodels interoperated among different transformation compositions[11], similarly as Yie et al that applied validation between transformation IO parameters considering an MTC specification[39]; 6) Rosenmüller et al applied techniques to control dynamic SPLs[32] and, despite not being related to model transformation reuse, can also be applied in this context; 7) Aranega et al[2] and Basso et al[6] applied SPLbased techniques to fragment and merge model transformation assets. Although these works present an important contribution as a means of reuse techniques, they have not tackled automated test cases to validate the generated assets.…”

Supporting large scale model transformation reuse

“…Variability management is a requirement to support reuse even in different contexts [24,39]. Accordingly, other approaches support transformation asset variability in two different scopes: a) Runtime variant points are checked at runtime to execute variant transformation sequences [5,48]; b) Generative approach for transformation chains that are adapted to execute certain sequences [2,46]. Our experiences show that both scopes are important and complementary.…”