From legal contracts to smart contracts and back again: Towards an automated approach

Blockchain smart contracts, programs with the potential to automate transactions and beyond, have gained tremendous popularity over the past years. Central to the original of smart contracts is that every computable clause of a contract or agreement is encoded into arbitrary computer logic with the aim of coding this logic into computer programs, and let the program decide and execute what happens during the contract's life span. The term smart legal contract has been coined to describe smart contracts that aim to capture legally binding agreements between parties. This dissertation presents a method to facilitate the creation of smart legal contracts that constitute a legally binding contract and that can (partially) self-enforce their terms and conditions within that contract, regardless of the blockchain platform. Understanding how blockchain technology works is pivotal to grapple the ramifications of this choice for smart contracts. Chapter 2 presents an overview of the literature on blockchain to delineate architectural perspectives on the technology, and to define its properties. Finally, the chapter points out the current challenges for the technology and gaps in literature. In Chapter 3, a background on smart contracts will be provided using a motivational example. Chapter 4 expounds the research methodology, the research paradigm adopted for the research, and the philosophy underpinning the method called Model Driven Architecture. Following, in Chapter 5 a domain model for smart legal contracts is presented. The chapter demonstrates how the contents of a legal contract could be captured in a model using a motivational example. Chapter 6 is devoted to describing the models that can be employed to write smart contracts. The chapter presents a platform specific model for the Ethereum and Hyperledger Fabric blockchain platforms. A platform agnostic model for blockchain technology is thereafter presented that captures the commonalities between these platforms. Chapter 7 discusses how the main research question is addressed. Derived from the insights of the discussion some opportunities for future research are discussed. Finally, Chapter 8 concludes the dissertation

Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn

AbstractBio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study

Model Transformation Languages with Modular Information Hiding

Model transformations, together with models, form the principal artifacts in model-driven software development. Industrial practitioners report that transformations on larger models quickly get sufficiently large and complex themselves. To alleviate entailed maintenance efforts, this thesis presents a modularity concept with explicit interfaces, complemented by software visualization and clustering techniques. All three approaches are tailored to the specific needs of the transformation domain

Model Transformation Languages with Modular Information Hiding

Model transformations, together with models, form the principal artifacts in model-driven software development. Industrial practitioners report that transformations on larger models quickly get sufficiently large and complex themselves. To alleviate entailed maintenance efforts, this thesis presents a modularity concept with explicit interfaces, complemented by software visualization and clustering techniques. All three approaches are tailored to the specific needs of the transformation domain

Effect of customer satisfaction on customer loyalty and the moderating role of customer experience in the Nigerian hotel industry

The dynamism of the hospitality industry has called for the need to have satisfied and loyal customers in order to achieve competitiveness. Therefore, this study aims to propose and validate a customer loyalty model in the hotel sector. Drawing from social exchange theory and confirmation-disconfirmation theory, this study examined the mediating role of customer satisfaction on the relationships among perceived service quality, perceived value, customer engagement, image, and customer experience on customer loyalty. In addition, the moderating effect of customer experience on the relationship between customer satisfaction and loyalty was also examined. Data obtained from 334 guests in the 82 hotels operating in Kano was analysed using PLS-SEM. Findings showed significant direct relationships between perceived service quality, customer satisfaction, image, and customer loyalty. However, perceived value and customer engagement reported an insignificant relationship. It was also found that the direct relationships between perceived service quality, perceived value, customer engagement, image, and customer satisfaction were established. As postulated, the mediating role of customer satisfaction on perceived service quality, perceived value and customer engagement relationships were supported. However, customer satisfaction did not mediate the link between image and customer loyalty. Similarly, moderating relationship of customer experience on customer satisfaction and loyalty was not supported. The use of customer engagement and customer experience in predicting loyalty is a noble contribution to knowledge and hospitality domain. The finding is of immense benefits to the management as it aids toward developing strategies to satisfy their customers and to retain them

Towards Automated Formal Analysis of Model Transformation Specifications

In Model-Driven Engineering, model transformation is a key model management operation, used to translate models between notations. Model transformation can be used for many engineering activities, for instance as a preliminary to merging models from different meta- models, or to generate codes from diagrammatic models. A mapping model needs to be developed (the transformation specification) to represent relations between concepts from the metamodels. The evaluation of the mapping model creates new challenges, for both conventional verification and validation, and also in guaranteeing that models generated by applying the transformation specification to source models still retain the intention of the initial transformation requirements. Most model transformation creates and evaluates a transformation specification in an ad-hoc manner. The specifications are usu- ally unstructured, and the quality of the transformations can only be assessed when the transformations are used. Analysis is not systematically applied even when the transformations are in use, so there is no way to determine whether the transformations are correct and consistent. This thesis addresses the problem of systematic creation and analysis of model transformation, via a facility for planning and designing model transformations which have conceptual-level properties that are tractable to formal analysis. We proposed a framework that provides steps to systematically build a model transformation specification, a visual notation for specifying model transformation and a template-based approach for producing a formal specification that is not just structure-equivalent but also amenable to formal analysis. The framework allows evaluation of syntactic and semantic correctness of generated models, metamodel coverage, and semantic correctness of the transformations themselves, with the help of snapshot analysis using patterns