Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/29917
Title: Software reliability modeling and release time determination
Authors: LI XIANG
Keywords: Software Reliability, Open Source Software, DDSRM, Parameter Uncertainty, Release Time Determination, Multi-Objective Optimization
Issue Date: 30-Mar-2011
Source: LI XIANG (2011-03-30). Software reliability modeling and release time determination. ScholarBank@NUS Repository.
Abstract: This thesis aims to improve software reliability modeling, and to study its corresponding release time determination problem by extending traditional software reliability models and decision models. From this standpoint, research has been conducted as follows. Software reliability models can be classified into two categories: analytical software reliability models (ASRMs) and data-driven software reliability models (DDSRMs). Both of them are studied in this thesis. In particular, for ASRMs, the modeling framework for open source software reliability is introduced, and the corresponding version-updating problem is investigated as well. Besides the research on ASRMs, improvement on DDSRMs is also carried out, and a generic DDSRM is developed with model mining technique. Developing models is not the ultimate goal of software reliability modeling. It is more important to apply these models to solve corresponding decision-making problems, and software release time determination is a typical application. However, with an increasing number of parameters involved in these models, the uncertainty of parameters could greatly affect the decision. It is important to study the impact of these model parameters. Therefore, sensitivity analysis of release time is studied, and a risk-based approach is proposed for release time determination with delay cost considerations. Last but not least, for software release time determination problem, most existing research formulates it as single objective optimization problems. However, these formulations can hardly describe the management?s attitude accurately. Therefore, multi-objective optimization model is developed. In order to solve this multi-objective optimization problem, different multi-objective optimization approaches are used and compared. By comparing these approaches, management can apply them more appropriately in practice considering their own unique properties.
URI: http://scholarbank.nus.edu.sg/handle/10635/29917
Appears in Collections:Ph.D Theses (Open)

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