Evaluation of Frame- and Feature-based Software Product Line Tools from the Viewpoint of Mass Customization by End Users

Customers expect Information and Communications Technology (ICT) platforms and applications to deliver services customized to their needs. Software product line (SPL) paradigm uses platforms and variability management to develop mass-customizable software applications. The paradigm necessitates effective software tools to manage platform and application artifacts and traceability and variability information. This paper constructs a comprehensive but lightweight tool evaluation framework and uses it to evaluate two tools, XML-based variant configuration language (XVCL) and FeaturePlugin – a feature modeling plug-in for Eclipse Integrated Development Environment. The paper analyzes the capabilities of the tools for enabling the mass customization of software applications by the end users performing complex workflows. Both the XVCL and FeaturePlugin tool envisage more efficient software system development by means of reusability, support for abstraction, and configuration mechanisms. Future research is needed to refine and validate the evaluation framework in the context of other types of SPL tools

FORMALIZATION AND DETECTION OF COLLABORATIVE PATTERNS IN SOFTWARE

Ph.DDOCTOR OF PHILOSOPH

Analysis and debugging of meta-programs in XVCL

Master'sMASTER OF SCIENC

Generative aspect-oriented component adaptation

Due to the availability of components and the diversity of target applications, mismatches between pre-qualified existing components and the particular reuse context in applications are often inevitable and have been a major hurdle of component reusability and successful composition. Although component adaptation has acted as a key solution for eliminating these mismatches, existing practices are either only capable for adaptation at the interface level, or require too much intervention from software engineers. Another weakness of existing approaches is the lack of reuse of component adaptation knowledge. Aspect Oriented Programming (AOP) is a new methodology that provides separation of crosscutting concerns by introducing a new unit of modularization - an Aspect that crosscuts other modules. In this way, all the associated complexity of the crosscutting concerns is isolated into the Aspects, hence the final system becomes easier to design, implement and maintain. The nature of AOP makes it particularly suitable for addressing non-functional mismatches with component-based systems. However, current AOP techniques are not powerful enough for efficient component adaptation due to the weaknesses they have, including the limited reusability of Aspects, platform specific Aspects, and naive weaving processes. Therefore, existing AOP technology needs to be expanded before it can be used for efficient component adaptation. This thesis presents a highly automated approach to component adaptation through product line based Generative Aspect Oriented Component adaptation. In the approach, the adaptation knowledge is captured in Aspects and aims to be reusable in various adaptation circumstances. Automatic generation of adaptation Aspects is developed as a key technology to improve the level of automation of the approach and the reusability of adaptation knowledge. This generation is realised by developing a two dimensional Aspect model, which incorporates the technologies of software product line and generative programming. The adaptability and automation of the approach is achieved in an Aspect oriented component adaptation framework by generating and then applying the adaptation Aspects under a designed weaving process according to specific adaptation requirements. To expand the adaptation power of AOP, advanced Aspect weaving processes have been developed with the support of an enhanced aspect weaver. To promote the reusability of adaptation Aspects, an expandable repository of reusable adaptation Aspects has been developed based on the proposed two-dimensional Aspect model. A prototype tool is built as a leverage of the approach and automates the adaptation process. Case studies have been done to illustrate and evaluate the approach, in terms of its capability of building highly reusable Aspects across various AOP platforms and providing advanced weaving process. In summary, the proposed approach applies Generative Aspect Oriented Adaptation to targeted components to correct the mismatch problem so that the components can be integrated into a target application easily. The automation of the adaptation process, the deep level of the adaptation, and the reusability of adaptation knowledge are the advantages of the approach.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Generative aspect-oriented component adaptation

Due to the availability of components and the diversity of target applications, mismatches between pre-qualified existing components and the particular reuse context in applications are often inevitable and have been a major hurdle of component reusability and successful composition. Although component adaptation has acted as a key solution for eliminating these mismatches, existing practices are either only capable for adaptation at the interface level, or require too much intervention from software engineers. Another weakness of existing approaches is the lack of reuse of component adaptation knowledge.Aspect Oriented Programming (AOP) is a new methodology that provides separation of crosscutting concerns by introducing a new unit of modularization - an Aspect that crosscuts other modules. In this way, all the associated complexity of the crosscutting concerns is isolated into the Aspects, hence the final system becomes easier to design, implement and maintain. The nature of AOP makes it particularly suitable for addressing non-functional mismatches with component-based systems. However, current AOP techniques are not powerful enough for efficient component adaptation due to the weaknesses they have, including the limited reusability of Aspects, platform specific Aspects, and naive weaving processes. Therefore, existing AOP technology needs to be expanded before it can be used for efficient component adaptation.This thesis presents a highly automated approach to component adaptation through product line based Generative Aspect Oriented Component adaptation. In the approach, the adaptation knowledge is captured in Aspects and aims to be reusable in various adaptation circumstances.Automatic generation of adaptation Aspects is developed as a key technology to improve the level of automation of the approach and the reusability of adaptation knowledge. This generation is realised by developing a two dimensional Aspect model, which incorporates the technologies of software product line and generative programming. The adaptability and automation of the approach is achieved in an Aspect oriented component adaptation framework by generating and then applying the adaptation Aspects under a designed weaving process according to specific adaptation requirements. To expand the adaptation power of AOP, advanced Aspect weaving processes have been developed with the support of an enhanced aspect weaver. To promote the reusability of adaptation Aspects, an expandable repository of reusable adaptation Aspects has been developed based on the proposed two-dimensional Aspect model.A prototype tool is built as a leverage of the approach and automates the adaptation process. Case studies have been done to illustrate and evaluate the approach, in terms of its capability of building highly reusable Aspects across various AOP platforms and providing advanced weaving process.In summary, the proposed approach applies Generative Aspect Oriented Adaptation to targeted components to correct the mismatch problem so that the components can be integrated into a target application easily. The automation of the adaptation process, the deep level of the adaptation, and the reusability of adaptation knowledge are the advantages of the approach

Towards an aspect weaving BPEL engine

This position paper proposes the use of dynamic aspects and the visitor design pattern to obtain a highly configurable and extensible BPEL engine. Using these two techniques, the core of this infrastructural software can be customised to meet new requirements and add features such as debugging, execution monitoring, or changing to another Web Service selection policy. Additionally, it can easily be extended to cope with customer-specific BPEL extensions. We propose the use of dynamic aspects not only on the engine itself but also on the workflow in order to tackle the problems of Web Service hot deployment and hot fixes to long running processes. In this way, composing aWeb Service "on-the-fly" means weaving its choreography interface into the workflow

Automatic generation of software interfaces for supporting decisionmaking processes. An application of domain engineering & machine learning

[EN] Data analysis is a key process to foster knowledge generation in particular domains or fields of study. With a strong informative foundation derived from the analysis of collected data, decision-makers can make strategic choices with the aim of obtaining valuable benefits in their specific areas of action. However, given the steady growth of data volumes, data analysis needs to rely on powerful tools to enable knowledge extraction. Information dashboards offer a software solution to analyze large volumes of data visually to identify patterns and relations and make decisions according to the presented information. But decision-makers may have different goals and, consequently, different necessities regarding their dashboards. Moreover, the variety of data sources, structures, and domains can hamper the design and implementation of these tools. This Ph.D. Thesis tackles the challenge of improving the development process of information dashboards and data visualizations while enhancing their quality and features in terms of personalization, usability, and flexibility, among others. Several research activities have been carried out to support this thesis. First, a systematic literature mapping and review was performed to analyze different methodologies and solutions related to the automatic generation of tailored information dashboards. The outcomes of the review led to the selection of a modeldriven approach in combination with the software product line paradigm to deal with the automatic generation of information dashboards. In this context, a meta-model was developed following a domain engineering approach. This meta-model represents the skeleton of information dashboards and data visualizations through the abstraction of their components and features and has been the backbone of the subsequent generative pipeline of these tools. The meta-model and generative pipeline have been tested through their integration in different scenarios, both theoretical and practical. Regarding the theoretical dimension of the research, the meta-model has been successfully integrated with other meta-model to support knowledge generation in learning ecosystems, and as a framework to conceptualize and instantiate information dashboards in different domains. In terms of the practical applications, the focus has been put on how to transform the meta-model into an instance adapted to a specific context, and how to finally transform this later model into code, i.e., the final, functional product. These practical scenarios involved the automatic generation of dashboards in the context of a Ph.D. Programme, the application of Artificial Intelligence algorithms in the process, and the development of a graphical instantiation platform that combines the meta-model and the generative pipeline into a visual generation system. Finally, different case studies have been conducted in the employment and employability, health, and education domains. The number of applications of the meta-model in theoretical and practical dimensions and domains is also a result itself. Every outcome associated to this thesis is driven by the dashboard meta-model, which also proves its versatility and flexibility when it comes to conceptualize, generate, and capture knowledge related to dashboards and data visualizations

Ontology-based methodology for error detection in software design

Improving the quality of a software design with the goal of producing a high quality software product continues to grow in importance due to the costs that result from poorly designed software. It is commonly accepted that multiple design views are required in order to clearly specify the required functionality of software. There is universal agreement as to the importance of identifying inconsistencies early in the software design process, but the challenge is how to reconcile the representations of the diverse views to ensure consistency. To address the problem of inconsistencies that occur across multiple design views, this research introduces the Methodology for Objects to Agents (MOA). MOA utilizes a new ontology, the Ontology for Software Specification and Design (OSSD), as a common information model to integrate specification knowledge and design knowledge in order to facilitate the interoperability of formal requirements modeling tools and design tools, with the end goal of detecting inconsistency errors in a design. The methodology, which transforms designs represented using the Unified Modeling Language (UML) into representations written in formal agent-oriented modeling languages, integrates object-oriented concepts and agent-oriented concepts in order to take advantage of the benefits that both approaches can provide. The OSSD model is a hierarchical decomposition of software development concepts, including ontological constructs of objects, attributes, behavior, relations, states, transitions, goals, constraints, and plans. The methodology includes a consistency checking process that defines a consistency framework and an Inter-View Inconsistency Detection technique. MOA enhances software design quality by integrating multiple software design views, integrating object-oriented and agent-oriented concepts, and defining an error detection method that associates rules with ontological properties