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

Predictive long-term asset maintenance strategy: development of a fuzzy logic condition-based control system

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceTechnology has accelerated the growth of the Facility Management industry and its roles are broadening to encompass more responsibilities and skill sets. FM budgets and teams are becoming larger and more impactful as new technological trends are incorporated into data-driven strategies. This new scenario has motivated institutions such as the European Central Bank to initiate projects aimed at optimising the use of data to improve the monitoring, control and preservation of the assets that enable the continuity of the Bank's activities. Such projects make it possible to reduce costs, plan, manage and allocate resources, reinforce the control, and efficiency of safety and operational systems. To support the long-term maintenance strategy being developed by the Technical Facility Management section of the ECB, this thesis proposes a model to calculate the Left wear margin of the equipment. This is accomplished through the development of an algorithm based on a fuzzy logic system that uses Python language and presents the system's structure, its reliability, feasibility, potential, and limitations. For Facility Management, this project constitutes a cornerstone of the ongoing digital transformation program

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

Designing Reusable Systems that Can Handle Change - Description-Driven Systems : Revisiting Object-Oriented Principles

In the age of the Cloud and so-called Big Data systems must be increasingly flexible, reconfigurable and adaptable to change in addition to being developed rapidly. As a consequence, designing systems to cater for evolution is becoming critical to their success. To be able to cope with change, systems must have the capability of reuse and the ability to adapt as and when necessary to changes in requirements. Allowing systems to be self-describing is one way to facilitate this. To address the issues of reuse in designing evolvable systems, this paper proposes a so-called description-driven approach to systems design. This approach enables new versions of data structures and processes to be created alongside the old, thereby providing a history of changes to the underlying data models and enabling the capture of provenance data. The efficacy of the description-driven approach is exemplified by the CRISTAL project. CRISTAL is based on description-driven design principles; it uses versions of stored descriptions to define various versions of data which can be stored in diverse forms. This paper discusses the need for capturing holistic system description when modelling large-scale distributed systems.Comment: 8 pages, 1 figure and 1 table. Accepted by the 9th Int Conf on the Evaluation of Novel Approaches to Software Engineering (ENASE'14). Lisbon, Portugal. April 201

Semantic model-driven development of service-centric software architectures

Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context

On the role of Prognostics and Health Management in advanced maintenance systems

The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognized as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyze how maintenance will change by using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the Condition Based Maintenance (CBM) and (iii) how PHM can be integrated into Reliability Centered Maintenance (RCM) programs. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.EU Framework Programme Horizon 2020, 645733 - Sustain-Owner - H2020-MSCA-RISE-201

Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.Comment: 10 pages; 6 figures in Proceedings of the 5th Annual International Conference on ICT: Big Data, Cloud and Security (ICT-BDCS 2015), Singapore July 2015. arXiv admin note: text overlap with arXiv:1402.5764, arXiv:1402.575

Towards an ontology-based platform-independent framework for developing KBE systems in the aerospace industry

Aerospace engineering is considered to be one of the most complex and advanced branches of engineering. The use of knowledge based engineering (KBE) technologies has played a major role in automating routine design activities in view of supporting the cost-effective and timely development of a product. However, technologies employed within KBE systems are usually platform-specific. The nature of these platform-specific models has significantly limited knowledge abstraction and reusability in KBE systems. This research paper presents a novel approach that illustrates the use of platform-independent knowledge models for the development of KBE systems in the aerospace industry. The use of semantic technologies through the definition of generic-purposed ontologies has been employed to support the notion of independent knowledge models that strengthens knowledge reusability in KBE systems. This approach has been validated qualitatively through experts’ opinion and its benefit realised in the abstraction, reusability and maintainability of KBE systems

Knowledge Representation Concepts for Automated SLA Management

Outsourcing of complex IT infrastructure to IT service providers has increased substantially during the past years. IT service providers must be able to fulfil their service-quality commitments based upon predefined Service Level Agreements (SLAs) with the service customer. They need to manage, execute and maintain thousands of SLAs for different customers and different types of services, which needs new levels of flexibility and automation not available with the current technology. The complexity of contractual logic in SLAs requires new forms of knowledge representation to automatically draw inferences and execute contractual agreements. A logic-based approach provides several advantages including automated rule chaining allowing for compact knowledge representation as well as flexibility to adapt to rapidly changing business requirements. We suggest adequate logical formalisms for representation and enforcement of SLA rules and describe a proof-of-concept implementation. The article describes selected formalisms of the ContractLog KR and their adequacy for automated SLA management and presents results of experiments to demonstrate flexibility and scalability of the approach.Comment: Paschke, A. and Bichler, M.: Knowledge Representation Concepts for Automated SLA Management, Int. Journal of Decision Support Systems (DSS), submitted 19th March 200