TRANSPARENCY PRIVACY CLASHING PARADIGMS IN A WEB 2.0 WORLD

A University of Utah Honors Think Tank 201

Migration from Legacy to Reactive Applications in OutSystems

A legacy system is an information system that significantly resists evolution. Through a migration, these systems can be moved to a more modernized environment without having to be redeveloped. OutSystems is a software company with a platform to develop and maintain applications using abstraction to increase productivity. In October 2019, OutSystems launched a new paradigm to allow developers to build reactive web applications. Because of this, the applications implemented in the old web paradigm turned into legacy systems. The OutSystems’ approach to this problem was a manual migration. However, it discards a considerable part of the effort previously made on the legacy system. A well-founded case study took place and allowed us to classify the UI as the most prioritized feature, but coincidently, the major bottleneck in migrations. So, this project had the following objectives: (1) The design and implementation of an automatic migration approach capable of converting UI elements to accelerate the manual migration; (2) The integration of the developed tool in the OutSystems platform. To transform the OutSystems paradigm’s elements, model-driven transformation rules must be set to receive the source UI elements and produce the target equivalent implementation in the new paradigm (each according to their model). However, the trans formations may not be straightforward, and a set of elements may need to be migrated to a different implementation due to Reactive Web’s best practices. Via the creation and search of UI patterns, it is possible to make special transformations for such scenarios. As a result, a migration approach was developed, allowing for the migration of UI (and other) elements. To complement this objective, the developed tool was integrated into the OutSystems platform with an easy to use interaction. Performance and usability tests proved the necessity and impact the final result had on the migration problem. This dissertation’s objectives were fully met and even exceeded, accelerating the man ual migration by providing an automatic UI conversion. This provided a quality increase in the existing process and results, giving OutSystems and its users the possibility of evolving their applications with considerable less effort and investment.Um sistema legado é um sistema de informação que resiste à evolução. Através de uma migração, estes sistemas podem ser movidos para um ambiente modernizado sem necessitar de re-implementação. A OutSystems é uma empresa de software com uma plataforma para desenvolver e manter aplicações usando abstracção para aumentar a produtividade. Em Outubro de 2019, a OutSystems lançou um novo paradigma para desenvolver aplicações reactive web. Assim, as aplicações implementadas no antigo paradigma web tornaram-se sistemas legados. A abordagem da OutSystems ao problema foi uma migração manual, no entanto, esta abordagem desconsidera uma parte significativa do investimento feito no sistema legado. Uma análise permitiu classificar a UI como a característica mais priorizada, mas também como o maior obstáculo em migrações. Assim, este projecto tem como objectivos: (1) O desenho e implementação de uma migração automática capaz de converter os elementos de UI para acelerar a migração manual; (2) A integração da ferramenta desenvolvida na plataforma da OutSystems. Para transformar os elementos dos paradigmas OutSystems, transformações de modelos têm de ser definidas para receber os elementos UI e produzir a implementação equivalente no novo paradigma (de acordo com o seu modelo). No entanto, as transformações podem não ser lineares, e um conjunto de elementos pode necessitar de uma migração para uma implementação diferente devido ao Reactive Web. Com a definição e procura de padrões de UI, é possível fazer transformações especiais para esses cenários. Como resultado, a migração foi desenvolvida, permitindo a conversão de elementos de UI (e não só). Para complementar, a ferramenta desenvolvida foi integrada na plataforma da OutSystems com uma interacção de fácil uso. Testes de desempenho e usabilidade provaram a necessidade e impacto da ferramenta no contexto da migração manual. Os objectivos desta dissertação foram completados na totalidade, acelerando a migração manual com a automação da migração de UI. Isto traz um aumento da qualidade no processo existente e nos seus resultados, dando à OutSystems e aos seus utilizadores a possibilidade de evoluírem as suas aplicações com um esforço e investimento menores

The Determinants of Customer Perceptions in a Dynamic Business Environment: An Exploratory Analysis of the ASP Business Model

Outsourcing attracted much attention in 1989 when Kodak outsourced its data center operation to IBM (International Business Machines Corp.). Nowadays, this strategy has become more popular. At the beginning of this century, the ASP (Application Service Provider) model was considered one of the typical solutions of Internet-based IT (Information Technology) outsourcing. Although this model has been transformed and renamed (e.g. SaaS - Software as a Service), the principle concept of providing IT service through the Internet or wide area network is still there. This study attempts to explore the determinants of customer perception of Internet-based IT outsourcing by obtaining a comprehensive understanding of the ASP model. The research dimensions not only include factors affecting users' perception of service quality but also ASP business position (i.e. the firm origin of ASP and its provider type) and services utilized by the customers. Through the study of firm history, two important theoretical themes of this research - path-dependence and Ansoff's product/ market growth matrix - are taken account of in exploring the influence of the determinants. Web-based questionnaire survey research is conducted together with a documentation study to collect data. Targeting the customers of the top 50 ASPs selected by ASPnews.com during the period 2001-2004, the researcher contacted 597 potential respondents, and 196 responses were returned. The valid sample consisted of 175 responses, and 124 of them not only provided full information for satisfaction evaluation but also the information for tracking their ASP vendors' business position. The GLM (General Linear Model) and the Pearson correlation coefficient were the major statistical approaches used to evaluate the survey data for developing a structural model. The research findings indicated that the factors associated with service competitiveness, such as capability and performance, reliability and trustworthiness, affordability, integration and customization, have positive effects on customer perceived satisfaction; whereas lock-in has a negative effect. More specifically, the origin of the ASP firm has a direct effect on capacity and performance, and also directly influences the use of IT adoption services. Based on this finding, a descriptive analysis and qualitative research shows that two mechanisms for path-dependence - existing expertise and perceived expertise - can affect the satisfaction level of capacity and performance of ASP services. On the other hand, provider type has a direct effect on affordability and also directly influences the use of facility supporting services. On this basis, another two mechanisms for path-dependence - transaction cost and standardization - can indirectly impact customer's perception of this business model via affordability. In addition to those major findings, some other determinants (e.g. software applications, brand of applications, and intensity of service used) were also identified in this study. The study result can be used for theoretical understanding about the determinants of ASP customer's perception. It not only indicates a new perspective to enhance the current body of research on this topic, but can also be more broadly applied to any fast-growth firm, rapid-change business, or technology intensive industry. Acknowledgements I would like to sincerely thank the following people for their contribution to this research project. Dr. Scott Koslow, my chief supervisor, for his continued encouragement, patience and guidance to ensure the completion of this project. His speciality in statistics has provided appropriate and valuable guidance in the data analysis for my research. Dr. Steven Lim, my second supervisor, for his advice, coherence, and support over the years. I also appreciate his constructive comments on my drafts and the shaping of my research. Dr. Bob McQueen and Dr. Jim Corner, for their assistance and advice in the early stages of my study. My parents, Yu-Ho and Lee-Chiung Liang, and my brother Ken, my sisters Annie, Eva, and Nancy, my brothers-in-law, J.C. and Chen, and Alice, my sister-in-law, for their emotional support throughout the length of my study. I also thank Bessie, my best friend for her assistance in data collection and her loving support, as well as Ted, Kevin, Mark, Frank, and Shirley, my study mates for their encouragement and friendship. Special thanks goes to Dr. Kuang-Ya Wang, the principal of Yu Da High School of Commerce and Home Economics, Taiwan, and also to the staff over there for their concern and assistance in data collection. Most importantly, my heartfelt appreciation goes to Warren, my husband. I am deeply grateful to him for his understanding, patience, and practical help. Without his enduring support I could not have done this study. Finally, my thanks and gratitude goes to those people who patiently answered my survey questionnaire as their kind assistance made it possible to complete this research

Integrating Network Analysis and Data Mining Techniques into Effective Framework for Web Mining and Recommendation. A Framework for Web Mining and Recommendation

The main motivation for the study described in this dissertation is to benefit from the development in technology and the huge amount of available data which can be easily captured, stored and maintained electronically. We concentrate on Web usage (i.e., log) mining and Web structure mining. Analysing Web log data will reveal valuable feedback reflecting how effective the current structure of a web site is and to help the owner of a web site in understanding the behaviour of the web site visitors. We developed a framework that integrates statistical analysis, frequent pattern mining, clustering, classification and network construction and analysis. We concentrated on the statistical data related to the visitors and how they surf and pass through the various pages of a given web site to land at some target pages. Further, the frequent pattern mining technique was used to study the relationship between the various pages constituting a given web site. Clustering is used to study the similarity of users and pages. Classification suggests a target class for a given new entity by comparing the characteristics of the new entity to those of the known classes. Network construction and analysis is also employed to identify and investigate the links between the various pages constituting a Web site by constructing a network based on the frequency of access to the Web pages such that pages get linked in the network if they are identified in the result of the frequent pattern mining process as frequently accessed together. The knowledge discovered by analysing a web site and its related data should be considered valuable for online shoppers and commercial web site owners. Benefitting from the outcome of the study, a recommendation system was developed to suggest pages to visitors based on their profiles as compared to similar profiles of other visitors. The conducted experiments using popular datasets demonstrate the applicability and effectiveness of the proposed framework for Web mining and recommendation. As a by product of the proposed method, we demonstrate how it is effective in another domain for feature reduction by concentrating on gene expression data analysis as an application with some interesting results reported in Chapter 5