Metamodel Instance Generation: A systematic literature review

Modelling and thus metamodelling have become increasingly important in Software Engineering through the use of Model Driven Engineering. In this paper we present a systematic literature review of instance generation techniques for metamodels, i.e. the process of automatically generating models from a given metamodel. We start by presenting a set of research questions that our review is intended to answer. We then identify the main topics that are related to metamodel instance generation techniques, and use these to initiate our literature search. This search resulted in the identification of 34 key papers in the area, and each of these is reviewed here and discussed in detail. The outcome is that we are able to identify a knowledge gap in this field, and we offer suggestions as to some potential directions for future research.Comment: 25 page

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Extracting Models from Source Code in Software Modernization

International audienceModel-driven software modernization is a discipline in which model-driven development (MDD) techniques are used in the modernization of legacy systems. When existing software artifacts are evolved, they must be transformed into models to apply MDD techniques such as model transformations. Since most modernization scenarios (e.g., application migration) involve dealing with code in general-purpose programming languages (GPL), the extraction of models from GPL code is an essential task in a model-based modernization process. This activity could be performed by tools to bridge grammarware and MDD technical spaces, which is normally carried out by dedicated parsers. Grammar-to-Model Transformation Language (Gra2MoL) is a domain-specific language (DSL) tailored to the extraction of models from GPL code. This DSL is actually a text-to-model transformation language which can be applied to any code conforming to a grammar. Gra2MoL aims to reduce the effort needed to implement grammarware-MDD bridges, since building dedicated parsers is a complex and time-consuming task. Like ATL and RubyTL languages, Gra2MoL incorporates the binding concept needed to write mappings between grammar elements and metamodel elements in a simple declarative style. The language also provides a powerful query language which eases the retrieval of scattered information in syntax trees. Moreover, it incorporates extensibility and grammar reuse mechanisms. This paper describes Gra2MoL in detail and includes a case study based on the application of the language in the extraction of models from Delphi code

Automatic generation of test cases from activity diagrams for UML based testing (UBT)

Activity diagrams are one of UML behavioural models suitable for system testing because it has the capacity to effectively describe the behaviours of systems under development. In this paper, a technique is proposed that generates test cases from activity diagrams by constructing an activity flow tree (AFT) which stores all the information extracted from the model file of the diagram through the help of a parser. Then, we applied an algorithm to generate test cases from the constructed tree. Test cases were generated based on the elements of activity diagrams such as activity sequences, associated descriptions and conditions. The proposed technique generated accurate test cases that completely tallied with the modeled requirements in the diagram. We utilized all-paths, basic pair paths, conditions, branches and transition criteria for generating test cases using ATM withdrawal operation software as a case study

A Model Driven Approach to Model Transformations

The OMG's Model Driven Architecture (MDA) initiative has been the focus of much attention in both academia and industry, due to its promise of more rapid and consistent software development through the increased use of models. In order for MDA to reach its full potential, the ability to manipulate and transform models { most obviously from the Platform Independent Model (PIM) to the Platform Specific Models (PSM) { is vital. Recognizing this need, the OMG issued a Request For Proposals (RFP) largely concerned with finding a suitable mechanism for trans- forming models. This paper outlines the relevant background material, summarizes the approach taken by the QVT-Partners (to whom the authors belong), presents a non-trivial example using the QVT-Partners approach, and finally sketches out what the future holds for model transformations

API2MoL: Automating the building of bridges between APIs and Model-Driven Engineering

International audienceContext: A software artefact typically makes its functionality available through a specialized Application Programming Interface (API) describing the set of services offered to client applications. In fact, building any software system usually involves managing a plethora of APIs, which complicates the development process. In Model-Driven Engineering (MDE), where models are the key elements of any software engineering activity, this API management should take place at the model level. Therefore, tools that facilitate the integration of APIs and MDE are clearly needed. Objective: Our goal is to automate the implementation of API-MDE bridges for supporting both the creation of models from API objects and the generation of such API objects from models. In this sense, this paper presents the API2MoL approach, which provides a declarative rule-based language to easily write mapping definitions to link API specifications and the metamodel that represents them. These definitions are then executed to convert API objects into model elements or vice versa. The approach also allows both the metamodel and the mapping to be automatically obtained from the API specification (bootstrap process). Method: After implementing the API2MoL engine, its correctness was validated using several APIs. Since APIs are normally large, we then developed a tool to implement the bootstrap process, which was also validated. Results: We provide a toolkit (language and bootstrap tool) for the creation of bridges between APIs and MDE. The current implementation focuses on Java APIs, although its adaptation to other statically typed object-oriented languages is straightforward. The correctness, expressiveness and completeness of the approach have been validated with the Swing, SWT and JTwitter APIs. Conclusion: API2MoL frees developers from having to manually implement the tasks of obtaining models from API objects and generating such objects from models. This helps to manage API models in MDE-based solutions

Incremental Model-to-Text Transformation

Model-driven engineering (MDE) promotes the use of abstractions to simplify the development of complex software systems. Through several model management tasks (e.g., model verification, re-factoring, model transformation), many software development tasks can be automated. For example, model-to-text transformations (M2T) are used to realize textual development artefacts (e.g., documentation, configuration scripts, code, etc.) from underlying source models. Despite the importance of M2T transformation, contemporary M2T languages lack support for developing transformations that scale. As MDE is applied to systems of increasing size and complexity, a lack of scalable M2T transformations and other model management tasks hinders industrial adoption. This is largely due to the fact that model management tools do not support efficient propagation of changes from models to other development artefacts. As such, the re-synchronisation of generated textual artefacts with underlying system models can take considerably large amount of time to execute due to redundant re-computations. This thesis investigates scalability in the context of M2T transformation, and proposes two novel techniques that enable efficient incremental change propagation from models to generated textual artefacts. In contrast to existing incremental M2T transformation technique, which relies on model differencing, our techniques employ fundamentally different approaches to incremental change propagation: they use a form of runtime analysis that identifies the impact of source model changes on generated textual artefacts. The structures produced by this runtime analysis, are used to perform efficient incremental transformations (scalable transformations). This claim is supported by the results of empirical evaluation which shows that the techniques proposed in this thesis can be used to attain an average reduction of 60% in transformation execution time compared to non-incremental (batch) transformation

Static Type Checking of Model Transformation Programs

Model transformation is seen as a promising approach to automate software development and verification, thus improving quality and reducing production costs significantly. However, errors of transformation programs can propagate into the generated artifacts complicating the detection of errors. The current paper proposes a static type checking approach for early detection of typing errors of partially typed transformation programs. The approach describes type safety as constraint satisfaction problems, and uses a dedicated back-annotation mechanism for error feedback