Model-driven engineering for software migration in a large industrial context

Abstract. As development techniques, paradigms and platforms evolve far more quickly than domain applications, software modernization and migration, is a constant challenge to software engineers. For more than ten years now, the Sodifrance company has been intensively using ModelDriven Engineering (MDE) for both development and migration projects. In this paper we report on the use of MDE as an efficient, flexible and reliable approach for a migration process (reverse-engineering, transformation and code generation). Moreover, we discuss how MDE is economically profitable and is cost-effective over the migration through out-sourced manual re-development. The paper is illustrated with the migration of a large-scale banking system from Mainframe to J2EE

Automatic Data Migration into the Cloud

Relational databases have been used for decades to store data. Using scale up, relational databases require a bigger and bigger server with more CPUs, more memory, and more disk storage to keep all the tables to support more concurrent users. However, big servers tend to be highly complex, proprietary, and disproportionately expensive, unlike the low-cost, commodity hardware. Therefore, it becomes important to store data efficiently and compute with massive amount of data, providing high scalability, providing high performance and availability at low costs. This leads to the invention of cloud databases, for instance NoSQL databases. NoSQL databases have many advantages such as reading and writing data quickly, supporting massive storage and low cost. The scaling approach in cloud databases is scale out, which is used to add multiple servers, and the data structure of storage is in the form of key-value pairs. However, it can be a challenge for enterprises to migrate existing relational databases to highly scalable NoSQL databases on clouds. In this thesis, we propose an automatic data migration model which will assist enterprises to migrate their relational databases efficiently and transparently to the cloud databases. We propose four migration methods to migrate data in four different ways. Each migration method is independent of the others and stores the migrated relational database in different formats in the cloud database. We design a system to implement the automatic data migration model. As a proof of concept, we successfully migrated a relational database from Microsoft SQL Server to a cloud database Amazon SimpleDB using four different migration methods. Furthermore, we have conducted extensive experiments on Amazon SimpleDB to evaluate the performance of our model in terms of computational time, storage cost, sharding and redundancy. Based on these experiments and detailed analysis of each migration method, our system allows enterprises to determine which method is suitable for their data migration. Furthermore, our experimental evaluation shows that our solution is promising and can migrate data from the relational databases to the cloud databases

Model Driven Development and Maintenance of Business Logic for Information Systems

Since information systems become more and more important in today\''s society, business firms, organizations, and individuals rely on these systems to manage their daily business and social activities. The dependency of possibly critical business processes on complex IT systems requires a strategy that supports IT departments in reducing the time needed to implement changed or new domain requirements of functional departments. In this context, software models help to manage system\''s complexity and provide a tool for communication and documentation purposes. Moreover, software engineers tend to use automated software model processing such as code generation to improve development and maintenance processes. Particularly in the context of web-based information systems, a number of model driven approaches were developed. However, we believe that compared to the user interface layer and the persistency layer, there could be a better support of consistent approaches providing a suitable architecture for the consistent model driven development of business logic. To ameliorate this situation, we developed an architectural blueprint consisting of meta models, tools, and a method support for model driven development and maintenance of business logic from analysis until system maintenance. This blueprint, which we call Amabulo infrastructure, consists of five layers and provides concepts and tools to set up and apply concrete infrastructures for model driven development projects. Modeling languages can be applied as needed. In this thesis we focus on business logic layers of J2EE applications. However, concrete code generation rules can be adapted easily for different target platforms. After providing a high-level overview of our Amabulo infrastructure, we describe its layers in detail: The Visual Model Layer is responsible for all visual modeling tasks. For this purpose, we discuss requirements for visual software models for business logic, analyze several visual modeling languages concerning their usefulness, and provide an UML profile for business logic models. The Abstract Model Layer provides an abstract view on the business logic model in the form of a domain specific model, which we call Amabulo model. An Amabulo model is reduced to pure logical information concerning business logic aspects. It focuses on information that is relevant for the code generation. For this purpose, an Amabulo model integrates model elements for process modeling, state modeling, and structural modeling. It is used as a common interface between visual modeling languages and code generators. Visual models of the Visual Model Layer are automatically transformed into an Amabulo model. The Abstract System Layer provides a formal view onto the system in the form of a Coloured Petri Net (CPN). A Coloured Petri Net representation of the modeled business logic is a formal structure and independent of the actual business logic implementation. After an Amabulo model is automatically transformed into a CPN, it can be analyzed and simulated before any line of code is generated. The Code Generation Layer is responsible for code generation. To support the design and implementation of project-specific code generators, we discuss several aspects of code integration issues and provide object-oriented design approaches to tackle the issues. Then, we provide a conceptual mapping of Amabulo model elements into architectural elements of a J2EE infrastructure. This mapping explicitly considers robustness features, which support a later manual integration of generated critical code artifacts and external systems. The Application Layer is the target layer of an Amabulo infrastructure and comprises generated code artifacts. These artifacts are instances of a specific target platform specification, and they can be modified for integration purposes with development tools. Through the contributions in this thesis, we aim to provide an integrated set of solutions to support an efficient model driven development and maintenance process for the business logic of information systems. Therefore, we provide a consistent infrastructure blueprint that considers modeling tasks, model analysis tasks, and code generation tasks. As a result, we see potential for reducing the development and maintenance efforts for changed domain requirements and simultaneously guaranteeing robustness and maintainability even after several changes

Search-Based Information Systems Migration: Case Studies on Refactoring Model Transformations

Information systems are built to last for decades; however, the reality suggests otherwise. Companies are often pushed to modernize their systems to reduce costs, meet new policies, improve the security, or to be more competitive. Model-driven engineering (MDE) approaches are used in several successful projects to migrate systems. MDE raises the level of abstraction for complex systems by relying on models as first-class entities. These models are maintained and transformed using model transformations (MT), which are expressed by means of transformation rules to transform models from source to target meta-models. The migration process for information systems may take years for large systems. Thus, many changes are going to be introduced to the transformations to reflect the new business requirements, fix bugs, or to meet the updated metamodels. Therefore, the quality of MT should be continually checked and improved during the evolution process to avoid future technical debts. Most MT programs are written as one large module due to the lack of refactoring/modularization and regression testing tools support. In object-oriented systems, composition and modularization are used to tackle the issues of maintainability and testability. Moreover, refactoring is used to improve the non-functional attributes of the software, making it easier and faster for developers to work and manipulate the code. Thus, we proposed an intelligent computational search approach to automatically modularize MT. Furthermore, we took inspiration from a well-defined quality assessment model for object-oriented design to propose a quality assessment model for MT in particular. The results showed a 45% improvement in the developer’s speed to detect or fix bugs, and developers made 40% less errors when performing a task with the optimized version. Since refactoring operations changes the transformation, it is important to apply regression testing to check their correctness and robustness. Thus, we proposed a multi-objective test case selection technique to find the best trade-off between coverage and computational cost. Results showed a drastic speed-up of the testing process while still showing a good testing performance. The survey with practitioners highlighted the need of such maintenance and evolution framework to improve the quality and efficiency of the existing migration process.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/149153/1/Bader Alkhazi Final Dissertation.pdfDescription of Bader Alkhazi Final Dissertation.pdf : Restricted to UM users only