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

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

Enabling collaborative modelling for a multi-site model-driven software development approach for electronic control units.

An important aspect of support for distributed work is to enable users at different sites to work collaboratively, across different sites, even different countries but where they may be working on the same artefacts. Where the case is the design of software systems, design models need to be accessible by more than one modeller at a time allowing them to work independently from each other in what can be called a collaborative modelling process supporting parallel evolution. In addition, as such design is a largely creative process users are free to create layouts which appear to better depict their understanding of certain model elements presented in a diagram. That is, that the layout of the model brings meaning which exceed the simple structural or topological connections. However, tools for merging such models tend to do so from a purely structural perspective, thus losing an important aspect of the meaning which was intended to be conveyed by the modeller. This thesis presents a novel approach to model merging which allows the preservation of such layout meaning when merging. It first presents evidence from an industrial study which demonstrates how modellers use layout to convey meanings. An important finding of the study is that diagram layout conveys domain-specific meaning and is important for modellers. This thesis therefore demonstrates the importance of diagram layout in model-based software engineering. It then introduces an approach to merging which allows for the preservation of domain-specific meaning in diagrams of models, and finally describes a prototype tool and core aspects of its implementation

Constrained set-up of the tGAP structure for progressive vector data transfer

A promising approach to submit a vector map from a server to a mobile client is to send a coarse representation first, which then is incrementally refined. We consider the problem of defining a sequence of such increments for areas of different land-cover classes in a planar partition. In order to submit well-generalised datasets, we propose a method of two stages: First, we create a generalised representation from a detailed dataset, using an optimisation approach that satisfies certain cartographic constraints. Second, we define a sequence of basic merge and simplification operations that transforms the most detailed dataset gradually into the generalised dataset. The obtained sequence of gradual transformations is stored without geometrical redundancy in a structure that builds up on the previously developed tGAP (topological Generalised Area Partitioning) structure. This structure and the algorithm for intermediate levels of detail (LoD) have been implemented in an object-relational database and tested for land-cover data from the official German topographic dataset ATKIS at scale 1:50 000 to the target scale 1:250 000. Results of these tests allow us to conclude that the data at lowest LoD and at intermediate LoDs is well generalised. Applying specialised heuristics the applied optimisation method copes with large datasets; the tGAP structure allows users to efficiently query and retrieve a dataset at a specified LoD. Data are sent progressively from the server to the client: First a coarse representation is sent, which is refined until the requested LoD is reached

Automating Regression Test Selection for Web Services

As Web services grow in maturity and use, so do the methods which are being used to test and maintain them. Regression Testing is a major component of most major testing systems but has only begun to be applied to Web services. The majority of the tools and techniques applying regression test to Web services are focused on test-case generation, thus ignoring the potential savings of regression test selection. Regression test selection optimizes the regression testing process by selecting a subset of all tests, while still maintaining some level of confidence about the system performing no worse than the unmodified system. A safe regression test selection technique implies that after selection, the level of confidence is as high as it would be if no tests were removed. Since safe regression test selection techniques generally involve code-based (white-box) testing, they cannot be directly applied to Web services due to their loosely-coupled, standards-based, and distributed nature. A framework which automates both the regression test selection and regression testing processes for Web services in a decentralized, end-to-end manner is proposed. As part of this approach, special consideration is given to the concurrency issues which may occur in an autonomous and decentralized system. The resulting synchronization method will be presented along with a set of algorithms which manage the regression testing and regression test selection processes throughout the system. A set of empirical results demonstrate the feasibility and benefit of the approach

Blending State Differences and Change Operations for Metamodel Independent Merging of Software Models

A typical model merging session: requires a great deal of knowledgeable input; does not provide rapid feedback; quickly overwhelms the user with details; fails to properly match elements; performs minimal conflict detection; offers conflict resolution choices that are inadequate and without semantics; and exhibits counter-intuitive behavior. Viewing model merging as a process, this research defines a hybrid merge workflow that blends the best of the main approaches to merging, expressing its phases as algebraic operators for performing transformations on model and relationship data types. Normalization and denormalization phases decouple models from their originating tool and metamodel. State-based phases capture model differences in the model itself, establish element correspondence using multiply matching strategies, and extract change operations. Operation-based phases then partition and order the changes prior to the detection and automatic resolution of conflicts. The work has culminated in a prototype that validates the workflow, while realizing several novel model merging ideas, which are evaluated with simple and involved test cases. Combining the hybrid merge approach with the semantic expressiveness of decision tables---open to user modification---and an interactive and batch mode of operation allows the tool, named Mirador, to successfully address, to varying degrees, all of the previously cited shortcomings