Semester

Fall

Date of Graduation

2006

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Lane Department of Computer Science and Electrical Engineering

Committee Chair

Hany H. Ammar.

Abstract

In this research effort, we focus on model-based risk assessment. Risk assessment is essential in any plan intended to manage software development or maintenance process. Subjective techniques are human intensive and error-prone. Risk assessment should be based on architectural attributes that we can quantitatively measure using architectural level metrics. Software architectures are emerging as an important concept in the study and practice of software engineering nowadays, due to their emphasis on large-scale composition of software product, and to their support for emerging software engineering paradigms, such as product line engineering, component based software engineering, and software evolution.;In this dissertation, we generalize our earlier work on reliability-based risk assessment. We introduce error propagation probability in the assessment methodology to account for the dependency among the system components. Also, we generalize the reliability-based risk assessment to account for inherent functional dependencies.;Furthermore, we develop a generic framework for maintainability-based risk assessment which can accommodate different types of software maintenance. First, we introduce and define maintainability-based risk assessment for software architecture. Within our assessment framework, we investigate the maintainability-based risk for the components of the system, and the effect of performing the maintenance tasks on these components. We propose a methodology for estimating the maintainability-based risk when considering different types of maintenance. As a proof of concept, we apply the proposed methodology on several case studies. Moreover, we automate the estimation of the maintainability-based risk assessment methodology.

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