Evolving models in Model-Driven Engineering : State-of-the-art and future challenges

The artefacts used in Model-Driven Engineering (MDE) evolve as a matter of course: models are modified and updated as part of the engineering process; metamodels change as a result of domain analysis and standardisation efforts; and the operations applied to models change as engineering requirements change. MDE artefacts are inter-related, and simultaneously constrain each other, making evolution a challenge to manage. We discuss some of the key problems of evolution in MDE, summarise the key state-of-the-art, and look forward to new challenges in research in this area

A research roadmap towards achieving scalability in model driven engineering

International audienceAs Model-Driven Engineering (MDE) is increasingly applied to larger and more complex systems, the current generation of modelling and model management technologies are being pushed to their limits in terms of capacity and eciency. Additional research and development is imperative in order to enable MDE to remain relevant with industrial practice and to continue delivering its widely recognised productivity , quality, and maintainability benefits. Achieving scalabil-ity in modelling and MDE involves being able to construct large models and domain-specific languages in a systematic manner, enabling teams of modellers to construct and refine large models in a collaborative manner, advancing the state of the art in model querying and transformations tools so that they can cope with large models (of the scale of millions of model elements), and providing an infrastructure for ecient storage, indexing and retrieval of large models. This paper attempts to provide a research roadmap for these aspects of scalability in MDE and outline directions for work in this emerging research area

Change-centric improvement of team collaboration

In software development, teamwork is essential to the successful delivery of a final product. The software industry has historically built software utilizing development teams that share the workplace. Process models, tools, and methodologies have been enhanced to support the development of software in a collocated setting. However, since the dawn of the 21st century, this scenario has begun to change: an increasing number of software companies are adopting global software development to cut costs and speed up the development process. Global software development introduces several challenges for the creation of quality software, from the adaptation of current methods, tools, techniques, etc., to new challenges imposed by the distributed setting, including physical and cultural distance between teams, communication problems, and coordination breakdowns. A particular challenge for distributed teams is the maintenance of a level of collaboration naturally present in collocated teams. Collaboration in this situation naturally d r ops due to low awareness of the activity of the team. Awareness is intrinsic to a collocated team, being obtained through human interaction such as informal conversation or meetings. For a distributed team, however, geographical distance and a subsequent lack of human interaction negatively impact this awareness. This dissertation focuses on the improvement of collaboration, especially within geographically dispersed teams. Our thesis is that by modeling the evolution of a software system in terms of fine-grained changes, we can produce a detailed history that may be leveraged to help developers collaborate. To validate this claim, we first c r eate a model to accurately represent the evolution of a system as sequences of fine- grained changes. We proceed to build a tool infrastructure able to capture and store fine-grained changes for both immediate and later use. Upon this foundation, we devise and evaluate a number of applications for our work with two distinct goals: 1. To assist developers with real-time information about the activity of the team. These applications aim to improve developers’ awareness of team member activity that can impact their work. We propose visualizations to notify developers of ongoing change activity, as well as a new technique for detecting and informing developers about potential emerging conflicts. 2. To help developers satisfy their needs for information related to the evolution of the software system. These applications aim to exploit the detailed change history generated by our approach in order to help developers find answers to questions arising during their work. To this end, we present two new measurements of code expertise, and a novel approach to replaying past changes according to user-defined criteria. We evaluate the approach and applications by adopting appropriate empirical methods for each case. A total of two case studies – one controlled experiment, and one qualitative user study – are reported. The results provide evidence that applications leveraging a fine-grained change history of a software system can effectively help developers collaborate in a distributed setting

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

Mining domain-specific edit operations from model repositories with applications to semantic lifting of model differences and change profiling

Model transformations are central to model-driven software development. Applications of model transformations include creating models, handling model co-evolution, model merging, and understanding model evolution. In the past, various (semi-) automatic approaches to derive model transformations from meta-models or from examples have been proposed. These approaches require time-consuming handcrafting or the recording of concrete examples, or they are unable to derive complex transformations. We propose a novel unsupervised approach, called Ockham, which is able to learn edit operations from model histories in model repositories. Ockham is based on the idea that meaningful domain-specifc edit operations are the ones that compress the model diferences. It employs frequent subgraph mining to discover frequent structures in model diference graphs. We evaluate our approach in two controlled experiments and one real-world case study of a large-scale industrial model-driven architecture project in the railway domain. We found that our approach is able to discover frequent edit operations that have actually been applied before. Furthermore, Ockham is able to extract edit operations that are meaningful—in the sense of explaining model diferences through the edit operations they comprise—to practitioners in an industrial setting. We also discuss use cases (i.e., semantic lifting of model diferences and change profles) for the discovered edit operations in this industrial setting. We fnd that the edit operations discovered by Ockham can be used to better understand and simulate the evolution of models

A graph-based aspect interference detection approach for UML-based aspect-oriented models

Aspect Oriented Modeling (AOM) techniques facilitate separate modeling of concerns and allow for a more flexible composition of these than traditional modeling technique. While this improves the understandability of each submodel, in order to reason about the behavior of the composed system and to detect conflicts among submodels, automated tool support is required. Current techniques for conflict detection among aspects generally have at least one of the following weaknesses. They require to manually model the abstract semantics for each system; or they derive the system semantics from code assuming one specific aspect-oriented language. Defining an extra semantics model for verification bears the risk of inconsistencies between the actual and the verified design; verifying only at implementation level hinders fixng errors in earlier phases. We propose a technique for fully automatic detection of conflicts between aspects at the model level; more specifically, our approach works on UML models with an extension for modeling pointcuts and advice. As back-end we use a graph-based model checker, for which we have defined an operational semantics of UML diagrams, pointcuts and advice. In order to simulate the system, we automatically derive a graph model from the diagrams. The result is another graph, which represents all possible program executions, and which can be verified against a declarative specification of invariants.\ud To demonstrate our approach, we discuss a UML-based AOM model of the "Crisis Management System" and a possible design and evolution scenario. The complexity of the system makes con°icts among composed aspects hard to detect: already in the case of two simulated aspects, the state space contains 623 di®erent states and 9 different execution paths. Nevertheless, in case the right pruning methods are used, the state-space only grows linearly with the number of aspects; therefore, the automatic analysis scales

Efficient Change Management of XML Documents

XML-based documents play a major role in modern information architectures and their corresponding work-flows. In this context, the ability to identify and represent differences between two versions of a document is essential. A second important aspect is the merging of document versions, which becomes crucial in parallel editing processes. Many different approaches exist that meet these challenges. Most rely on operational transformation or document annotation. In both approaches, the operations leading to changes are tracked, which requires corresponding editing applications. In the context of software development, however, a state-based approach is common. Here, document versions are compared and merged using external tools, called diff and patch. This allows users for freely editing documents without being tightened to special tools. Approaches exist that are able to compare XML documents. A corresponding merge capability is still not available. In this thesis, I present a comprehensive framework that allows for comparing and merging of XML documents using a state-based approach. Its design is based on an analysis of XML documents and their modification patterns. The heart of the framework is a context-oriented delta model. I present a diff algorithm that appears to be highly efficient in terms of speed and delta quality. The patch algorithm is able to merge document versions efficiently and reliably. The efficiency and the reliability of my approach are verified using a competitive test scenario