Requirements engineering aspects for sustainable eLearning systems

Sustainability in software engineering is about (1) continued functionality and maintainability in changing circumstances, and (2) functionality's effect on the surrounded environment, economic and people. Frequent changes of software requirements negatively affect sustainability of software systems. To reduce the number of requirements' changes and improve sustainability, sustainability requirements have to be considered from the beginning of the requirements engineering stage of software development. Sustainability in requirements engineering has five dimensions including individual, social, technical, economic and environmental dimensions. Most of the existing work analysed only one or two dimensions and ignore the interrelated effects among other dimensions. To address this issue, we selected eLearning systems because they provide comprehensive example to study. This thesis focuses on analysing sustainability requirements of eLearning systems with regard to the five sustainability dimensions. The following studies were performed: (1) identifying theoretically the sustainability requirements of eLearning systems, (2) investigating empirically the sustainability of eLearning systems, (3) constructing a methodology for the analysis and evaluation of sustainability requirements on eLearning systems, and (4) evaluating the constructed methodology. To the best of our knowledge, this is the first research conducted to investigate sustainability requirements of eLearning systems covering the five sustainability dimensions. Our findings highlighted that (1) technical, economic and environmental sustainability requirements are similar to other software domains, where individual and social sustainability requirements are specific for the domain of eLearning systems, (2) individual and social sustainability requirements need to be carefully considered and analysed together because of the strong correlation, and (3) culture and gender diversity play an important role for sustainability requirements. On this basis, we developed a framework for analysing sustainability requirements of software systems as well as a web-based tool SuSoftPro (the name stands from Software Sustainability Profiling) that allows requirements engineers to: investigate sustainability of software systems based on the systems' requirements, analyse the sustainability dimensions of software systems, measure the sustainability of each individual requirement, visualise analysis results to support decision making towards high-quality software, involve stakeholders to rate their requirements for one or more of the five sustainability dimensions, and manage requirement and stakeholder details easily. We evaluated the SuSoftPro framework through case studies, comparative evaluation and a quantitative questionnaire. Our framework successfully provides a comprehensive view of analysing sustainability requirements to improve the attention to sustainability and allow practitioners to develop sustainable software

RML: Runtime Monitoring Language

Runtime verification is a relatively new software verification technique that aims to prove the correctness of a specific run of a program, rather than statically verify the code. The program is instrumented in order to collect all the relevant information, and the resulting trace of events is inspected by a monitor that verifies its compliance with respect to a specification of the expected properties of the system under scrutiny. Many languages exist that can be used to formally express the expected behavior of a system, with different design choices and degrees of expressivity. This thesis presents RML, a specification language designed for runtime verification, with the goal of being completely modular and independent from the instrumentation and the kind of system being monitored. RML is highly expressive, and allows one to express complex, parametric, non-context-free properties concisely. RML is compiled down to TC, a lower level calculus, which is fully formalized with a deterministic, rewriting-based semantics. In order to evaluate the approach, an open source implementation has been developed, and several examples with Node.js programs have been tested. Benchmarks show the ability of the monitors automatically generated from RML specifications to effectively and efficiently verify complex properties

Predictive indicators of success in science & engineering projects - application to the SKA initiative

Projects that have scientific goals and are characterised by new engineering technologies, significant infrastructure, and big budgets are typically found to undergo much scrutiny prior to approval. What is less clear is whether concept reviews, approval, funding, or early stage planning takes proper advantage of potential indicators of success based on learnings from relevant past experience. In other words, is the likelihood of success in meeting all project goals considered at the outset, and can early stage project development/planning be made more effective?Through examination of published literature, interviews with past and present project managers, scientists and engineers, and investigation of selected case studies in Australia, Chile, South Africa and Europe, this thesis attempts to (i) identify critical success factors relevant to large, complex high-technology projects, (ii) investigate the use of experience as success indicators within contemporary case studies, and (iii) distil the results into a set of predictive test indicators of likely project success.While there is considerable literature concerning general management of large projects, and covering execution of complex undertakings, there is little specific material dealing with success drivers for large and complex high-technology projects. This thesis aims to fill this important gap in the current understanding.The present study distils an epistemic view of high-technology ‘mega-projects’, and through case examination and inductive and deductive reasoning, shows that serious attention paid to specific aspects of project-shaping can lift the probability of success. An additional output is a practical checklist tool for ‘high-tech’ mega-project practitioners.The findings from this research have direct applicability to current and future approvers and managers of large scale high-technology projects, and in particular the Square Kilometre Array (SKA) radio telescope project to be built in either Australasia or Southern Africa, and planned to commence preconstruction in 2012

A Framework for Evaluating and Improving University-Industry Collaboration

University-Industry Collaboration (UIC) has been a topic of interest for decades and has gained additional attention in recent times as the educational, research, industry, economic, and social benefits of such collaboration are increasingly recognized. While there are continuing efforts both globally and locally within Australia to encourage such collaboration, establishing successful UIC remains a challenge. The poor ranking of Australia against Organisation for Economic Co-operation and Development (OECD) comparators in most business-to-research collaboration indicators confirms that collaboration is an ongoing concern and that there is a lot more work to be done to improve collaborations, particularly in Australia. The research presented in this thesis addresses this problem by developing a framework for evaluation and improvement of UIC. This was achieved using a Design Science Research (DSR) approach. The proposed UIC Framework comprises a set of newly developed tools based on a literature review and initial qualitative research. These tools can be used in conjunction with the Cynefin sense-making framework to understand, evaluate and improve UIC of various types and complexity. The first tool is a UIC Systems Model, which will help users to analyse and gain a better understanding of a UIC. The second tool is a comprehensive UIC Practices Framework that can be used to improve the effectiveness of a UIC. The final tool is a UIC Maturity Model (UICMM), which can be used to assess the UIC maturity of an organisation, and guide improvements. By using this Systems Model, Practices Framework, and Maturity Model in conjunction with the Cynefin sense-making framework, stakeholders will be able to better understand their UIC activities, make improvements through informed decision-making, and evaluate the impact of such improvements. The developed UIC Framework has been evaluated using descriptive and expert evaluations. These evaluations demonstrate the utility and applicability of the framework. A strategy for continuous real-world evaluation and improvement of the framework has also been developed and documented in this thesis. This strategy is being piloted with two industry partners and will be used for future improvement of the UIC Framework

e-Process selection using decision making methods : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems at Massey University, Palmerston North, New Zealand

The key objective of this research is to develop a selection methodology that can be used to support and aid the selection of development processes for e-Commerce Information Systems (eCIS) effectively using various decision methods. The selection methodology supports developers in their choice of an e-Commerce Information System Development Process (e-Process) by providing them with a few different decision making methods for choosing between defined e-Processes using a set of quality aspects to compare and evaluate the different options. The methodology also provides historical data of previous selections that can be used to further support their specific choice. The research was initiated by the fast growing Information Technology environment, where e-Commerce Information Systems is a relatively new development area and developers of these systems may be using new development methods and have difficulty deciding on the best suited process to use when developing new eCIS. These developers also need documentary support for their choices and this research helps them with these decision-making processes. The e-Process Selection Methodology allows for the comparison of existing development processes as well as the comparison of processes as defined by the developers. Four different decision making methods, the Value-Benefit Method (Weighted Scoring), the Analytical Hierarchy Process, Case-Based Reasoning and a Social Choice method are used to solve the problem of selecting among e-Commerce Development Methodologies. The Value-Benefit Method, when applied to the selection of an e-Process from a set of e-Processes, uses multiple quality aspects. Values are assigned to each aspect for each of the e-Processes by experts. The importance of each of the aspects, to the eCIS, is defined in terms of weights. The selected e-Process is the one with the highest score when the values and weights are multiplied and then summed. The Analytic Hierarchy Process is used to quantify a selection of quality aspects and then these are used to evaluate alternative e-Processes and thus determining the best matching solution to the problem. This process provides for the ranking and determining of the relative worth of each of the quality aspects. Case-Based Reasoning requires the capturing of the resulting knowledge of previous cases, in a knowledge base, in order to make a decision. The case database is built in such a way that the concrete factual knowledge of previous individual cases that were solved previously is stored and can be used in the decision process. Case-based reasoning is used to determine the best choices. This allows the user to either use the selection methodology or the case base database to resolve their problems or both. Social Choice Methods are based on voting processes. Individuals vote for their preferences from a set of e-Processes. The results are aggregated to obtain a final result that indicates which e-Process is the preferred one. The e-Process Selection Methodology is demonstrated and validated by the development of a prototype tool. This tool can be used to select the most suitable solution for a case at hand. The thesis includes the factors that motivated the research and the process that was followed. The e-Process Selection Methodology is summarised as well as the strengths and weaknesses discussed. The contribution to knowledge is explained and future developments are proposed. To conclude, the lessons learnt and reinforced are considered

Factors impacting on tacit knowledge transfer within Scrum software development teams

Over time, there has been a high failure rate of information systems development (ISD) projects, although Agile development has brought recent improvements. Knowledge management is also known to be one of the critical factors to Agile and project success; however, there are some knowledge transfer studies in Agile development. Therefore, the purpose of this research is to present a theoretical model examining what makes individuals successful at transferring knowledge in teams using Scrum, Agile’s most popular methodology. Twelve semi-structured interviews were conducted at two Scrum companies in Cape Town. Participants interviewed ranged from project managers and Scrum masters to software developers, business analyst and testers. The interviews were all transcribed, then analysed using thematic analysis. The findings produced new relationships between characteristics already well known to impact knowledge transfer as well as newly defined characteristics impacting knowledge transfer in Scrum teams: empathy and articulation skills of the source. The results have shown that the recipient should perceive the person wanting to transfer knowledge as having these characteristics to enable successful knowledge transfer: empathy, motivation, capability, credibility, articulate and ability to communicate enough. The contribution of this study to practice is a list of attributes for HR managers to help improve the knowledge transfer of Scrum team members. The contribution to Scrum research is a new theoretical model that suggests which characteristics a person needs to transfer knowledge successfully in Scrum teams, adapted from Joshi, Sarker and Sarker’s (2007) knowledge transfer model. This model can also be extended in the future by looking more deeply into the new relationships between constructs, such as how motivation together with capability of the source affect knowledge transfer in Scrum teams

Exploiting similarity patterns in web applications for enhanced genericity and maintainability

Ph.DDOCTOR OF PHILOSOPH

Proceedings of the Salford Postgraduate Annual Research Conference (SPARC) 2011

These proceedings bring together a selection of papers from the 2011 Salford Postgraduate Annual Research Conference(SPARC). It includes papers from PhD students in the arts and social sciences, business, computing, science and engineering, education, environment, built environment and health sciences. Contributions from Salford researchers are published here alongside papers from students at the Universities of Anglia Ruskin, Birmingham City, Chester,De Montfort, Exeter, Leeds, Liverpool, Liverpool John Moores and Manchester