UML model refactoring as refinement: a coalgebraic perspective

Although increasingly popular, Model Driven Architecture (MDA) still lacks suitable formal foundations on top of which rigorous methodologies for the description, analysis and transformation of models could be built. This paper aims to contribute in this direction: building on previous work by the authors on coalgebraic refinement for software components and architectures, it discusses refactoring of models within a coalgebraic semantic framework. Architectures are defined through aggregation based on a coalgebraic semantics for (subsets of) UML. On the other hand, such aggregations, no matter how large and complex they are, can always be dealt with as coalgebras themselves. This paves the way to a discipline of models’ transformations which, being invariant under either behavioural equivalence or refinement, are able to formally capture a large number of refactoring patterns. The main ideas underlying this research are presented through a detailed example in the context of refactoring of UML class diagrams.The work reported in this paper is partially supported by a grant from the GLANCE funding program of NWO, through project CooPer (600.643.000.05N12)

Handling High-Level Model Changes Using Search Based Software Engineering

Model-Driven Engineering (MDE) considers models as first-class artifacts during the software lifecycle. The number of available tools, techniques, and approaches for MDE is increasing as its use gains traction in driving quality, and controlling cost in evolution of large software systems. Software models, defined as code abstractions, are iteratively refined, restructured, and evolved. This is due to many reasons such as fixing defects in design, reflecting changes in requirements, and modifying a design to enhance existing features. In this work, we focus on four main problems related to the evolution of software models: 1) the detection of applied model changes, 2) merging parallel evolved models, 3) detection of design defects in merged model, and 4) the recommendation of new changes to fix defects in software models. Regarding the first contribution, a-posteriori multi-objective change detection approach has been proposed for evolved models. The changes are expressed in terms of atomic and composite refactoring operations. The majority of existing approaches detects atomic changes but do not adequately address composite changes which mask atomic operations in intermediate models. For the second contribution, several approaches exist to construct a merged model by incorporating all non-conflicting operations of evolved models. Conflicts arise when the application of one operation disables the applicability of another one. The essence of the problem is to identify and prioritize conflicting operations based on importance and context – a gap in existing approaches. This work proposes a multi-objective formulation of model merging that aims to maximize the number of successfully applied merged operations. For the third and fourth contributions, the majority of existing works focuses on refactoring at source code level, and does not exploit the benefits of software design optimization at model level. However, refactoring at model level is inherently more challenging due to difficulty in assessing the potential impact on structural and behavioral features of the software system. This requires analysis of class and activity diagrams to appraise the overall system quality, feasibility, and inter-diagram consistency. This work focuses on designing, implementing, and evaluating a multi-objective refactoring framework for detection and fixing of design defects in software models.Ph.D.Information Systems Engineering, College of Engineering and Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/136077/1/Usman Mansoor Final.pdfDescription of Usman Mansoor Final.pdf : Dissertatio

Challenges in Software Evolution

Today’s information technology society increasingly relies on software at all levels. Nevertheless, software quality generally continues to fall short of expectations, and software systems continue to suffer from symptoms of aging as they are adapted to changing requirements and environments. The only way to overcome or avoid the negative effects of software aging is by placing change and evolution in the center of the software development process. In this article we describe what we believe to be some of the most important research challenges in software evolution. The goal of this document is to provide novel research directions in the software evolution domain

Quality Assurance of Software Models - A Structured Quality Assurance Process Supported by a Flexible Tool Environment in the Eclipse Modeling Project

The paradigm of model-based software development (MBSD) has become more and more popular since it promises an increase in the efficiency and quality of software development. In this paradigm, software models play an increasingly important role and software quality and quality assurance consequently leads back to the quality and quality assurance of the involved models. The fundamental aim of this thesis is the definition of a structured syntax-oriented process for quality assurance of software models that can be adapted to project-specific and domain-specific needs. It is structured into two sub-processes: a process for the specification of project-specific model quality assurance techniques, and a process for applying them on concrete software models within a MBSD project. The approach concentrates on quality aspects to be checked on the abstract model syntax and is based on quality assurance techniques model metrics, smells, and refactorings well-known from literature. So far, these techniques are mostly considered in isolation only and therefore the proposed process integrates them in order to perform model quality assurance more systematically. Three example cases performing the process serve as proof-of-concept implementations and show its applicability, its flexibility, and hence its usefulness. Related to several issues concerning model quality assurance minor contributions of this thesis are (1) the definition of a quality model for model quality that consists of high-level quality attributes and low-level characteristics, (2) overviews on metrics, smells, and refactorings for UML class models including structured descriptions of each technique, and (3) an approach for composite model refactoring that concentrates on the specification of refactoring composition. Since manually reviewing models is time consuming and error prone, several tasks of the proposed process should consequently be automated. As a further main contribution, this thesis presents a flexible tool environment for model quality assurance which is based on the Eclipse Modeling Framework (EMF), a common open source technology in model-based software development. The tool set is part of the Eclipse Modeling Project (EMP) and belongs to the Eclipse incubation project EMF Refactor which is available under the Eclipse public license (EPL). The EMF Refactor framework supports both the model designer and the model reviewer by obtaining metrics reports, by checking for potential model deficiencies (called model smells) and by systematically restructuring models using refactorings. The functionality of EMF Refactor is integrated into standard tree-based EMF instance editors, graphical GMF-based editors as used by Papyrus UML, and textual editors provided by Xtext. Several experiments and studies show the suitability of the tools for supporting the techniques of the structured syntax-oriented model quality assurance process

Example-based model refactoring using heuristic search

Software maintenance is considered the most expensive activity in software systems development: more than 80% of the resources are devoted to it. During the maintenance activities, software models are very rarely taken into account. The evolution of these models and the transformations that manipulate them are at the heart of model-driven engineering (MDE). However, as the source code, the model changes and tends to become increasingly complex. These changes generally have a negative impact on the quality of models and they cause damage to the software. In this context, refactoring is the most used technique to maintain an adequate quality of these models. The refactoring process is usually done in two steps: the detection of elements of the model to correct (design defects), then the correction of these elements. In this thesis, we propose two main contributions related to detection and correction of defects in class diagrams. The first contribution aims to automate the design defect detection. We propose to adapt genetic algorithms (e.g., genetic programming) to detect parts of the model that may correspond to design defects. The second contribution concerns the automation of the correction of these design defects. We propose to adapt three heuristic methods to suggest refactorings: 1. A single-objective optimization method based on structural similarities between a given model (i.e., the model to be refactored) and a set of examples of models (i.e., models that have undergone some refactorings); 2. An interactive single-objective optimization method based on structural similarity and the opinion of the designer; and 3. A multi-objective optimization method that maximizes both the structural and semantic similarities between the model under study and the models in the set of examples. All the proposed methods were implemented and evaluated on models generated from existing open-source projects and the obtained results confirm their efficiency