Managing software evolution through midleware and policy-based software adaptation framework

Software evolution is a process that is needed in order for software to remain useful. Thus, software evolution should be properly planned and controlled to prevent its negative impact from affecting any organization. Software adaptation concept is one of the promising ways to control software evolution. In this approach, software is made adaptable to minimize the impact of change. A lot of researches on software adaptation focus on adaptability of mobile based and network application due to its context sensitivity and quality-of-service requirements. However, there is still lack of work in enterprise system domain with multiple delivery channels, which focus on adaptability of its context environment such as the changes introduced to its devices. Hence, the purpose of this research is to develop a middleware and policy-based, adaptation framework to manage negative effects of software evolution in an enterprise system. The main research focus is on the changes introduced at the device layer. The concept of policy is used to specify adaptations requirements. This research provides a framework called Middleware and Policy-Based Framework to Manage Software Evolution (MiPAF), which can be used to develop adaptive software, allowing parameterized and compositional adaptation. Furthermore, the framework can be used by client-server and web-based application. A policy language called MiPAF Policy Language (MPL) is created to be used with the framework. MiPAF is formally specified using Z Notation and the policy language is described using pseudo code. A tool is provided to assist developers in creating the policy. For evaluation of the framework, a set of runtime components were developed and implemented for Unit Trust System (UTS) Front-end and web-based UTS, two industrial-based case studies. The evaluation result shows that MiPAF excellently fulfil all the evaluation criteria described in this thesis

Visual representation of a customizable software maintenance process model

Managing the evolution of complex and large software systems involves many different types of resources and knowledge such as software artefacts, user expertise, tools and techniques, etc. Variations and interrelationships among these types of resources and knowledge create well-known challenges for maintainers. Current research mainly focuses on establishing comprehension model, and developing tools to tackle a specific aspect of maintenance problems. Little research has been conducted to study how resources and knowledge work collaboratively together to provide guidance to maintainers to complete specific maintenance tasks in a given context. In this research, we introduce a customizable maintenance process model, which extends an existing IEEE standard process model, to allow visually link various resources (e.g. tools, artifacts, maintainers etc.) and knowledge to relevant maintenance process elements. A visual metaphor has been created to graphically represent the process model. Finally, a tool environment has been developed to provide utilities for maintainers to create, customize and apply our maintenance process to provide guidance for maintainers for their maintenance tasks

A Unified Metamodel for Assessing and Predicting Software Evolvability Quality

Software quality is a key assessment factor for organizations to determine the ability of software ecosystems to meet the constantly changing requirements. Many quality models exist that capture and assess the changing factors affecting the quality of a software product. Common to these models is that they, contrary to the software ecosystems they are assessing, are not evolvable or reusable. The thesis first defines what constitutes a unified, evolvable, and reusable quality metamodel. We then introduce SE-EQUAM, a novel, ontological, quality assessment metamodel that was designed from the ground up to support quality unification, reuse, and evolvability. We then validate the reus-ability of our metamodel through instantiating a domain specific quality assessment model called OntEQAM that assesses evolvability as a non-functional software quality based on product and com-munity dimensions. A fuzzy logic based assessment process that addresses uncertainties around score boundaries supports the evolvability quality assessment. The presented assessment process also uses the unified representation of the input knowledge artifacts, the metamodel, and the model to provide a fuzzy assessment score. Finally, we further interpret and predict the evolvability as-sessment scores using a novel, cross-disciplinary approach that re-applies financial technical analy-sis, which are indicators, and patterns typically used for price analysis and the forecasting of stocks in financial markets. We performed several case studies to illustrate and evaluate the applicability of our proposed evolvability score prediction approach