Metrics-Guided Quality Management for Component-Based Software Systems

The growing reliance on commercial-off-the-shelf (COTS) components for developing large-scale projects introduces a new paradigm in software Engineering; which requires the design of new software development and business processes. Large scale component reuse leads to savings in development resources, enabling these resources to be applied to areas such as quality improvement. These savings come at the price of integration difficulties, performance constraints, and incompatibility of components from multiple vendors. Relying on COTS components also increases the system\u27\u27s vulnerability to risks arising from third-party development, which can negatively affect the quality of the system, as well as causing expenses not incurred in traditional software development. We aim to alleviate such concerns by using software metrics to accurately quantify factors contributing to the overall quality of a component-based system, guiding quality and risk management by identifying and eliminating sources of ris

A Graph-Based Model for Component-Based Software Development

Software metrics can be used to objectively quantify the quality of software components and systems, alleviating quality and risk concerns and raising assurance in component-based systems. In this paper, we present a graph-based model for component-based software development. We assume that a number of components have been characterized in terms of non-functional metrics of importance to the software system being developed, and that the interfaces connecting various components have been similarly characterized. The emphasis of this work is on cost and quality of the system under development, and reaching an acceptable compromise between the two

Metrics and Models for Cost and Quality of Component-Based Software

Quality and risk concerns currently limit the application of commercial off-the-shelf (COTS) software components to non-critical applications. Software metrics can quantify factors contributing to the overall quality of a component-based system, and models for tradeoffs between cost and various aspects of quality can guide quality and risk management by identifying and eliminating sources of risk. This paper discusses metrics and models that can be used to alleviate quality concerns for COTS-based systems, enabling the use of COTS components in a broader range of applications

A systematic review of software development cost estimation studies

This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods

Software quality and reliability prediction using Dempster -Shafer theory

As software systems are increasingly deployed in mission critical applications, accurate quality and reliability predictions are becoming a necessity. Most accurate prediction models require extensive testing effort, implying increased cost and slowing down the development life cycle. We developed two novel statistical models based on Dempster-Shafer theory, which provide accurate predictions from relatively small data sets of direct and indirect software reliability and quality predictors. The models are flexible enough to incorporate information generated throughout the development life-cycle to improve the prediction accuracy.;Our first contribution is an original algorithm for building Dempster-Shafer Belief Networks using prediction logic. This model has been applied to software quality prediction. We demonstrated that the prediction accuracy of Dempster-Shafer Belief Networks is higher than that achieved by logistic regression, discriminant analysis, random forests, as well as the algorithms in two machine learning software packages, See5 and WEKA. The difference in the performance of the Dempster-Shafer Belief Networks over the other methods is statistically significant.;Our second contribution is also based on a practical extension of Dempster-Shafer theory. The major limitation of the Dempsters rule and other known rules of evidence combination is the inability to handle information coming from correlated sources. Motivated by inherently high correlations between early life-cycle predictors of software reliability, we extended Murphy\u27s rule of combination to account for these correlations. When used as a part of the methodology that fuses various software reliability prediction systems, this rule provided more accurate predictions than previously reported methods. In addition, we proposed an algorithm, which defines the upper and lower bounds of the belief function of the combination results. To demonstrate its generality, we successfully applied it in the design of the Online Safety Monitor, which fuses multiple correlated time varying estimations of convergence of neural network learning in an intelligent flight control system

Електронна комерція

Робота публікується згідно наказу ректора від 21.01.2020 р. №008/од "Про перевірку кваліфікаційних робіт на академічний плагіат 2019-2020р.р. навчальному році". Керівник проекту:к.т.н., професор, Харченко Олександр Григорович.Метою роботи є дослідження та обґрунтування моделей якості програмних систем для оцінювання якості платформ e-commerce, розробка та обґрунтування методів оцінювання якості таких платформ, методу вибору оптимальних рішень при побудові та впровадженні систем електронної комерції

Reliability models and analyses of the computing systems

Ph.DDOCTOR OF PHILOSOPH