Date of Award

1-1-2020

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Computer Science

Content Description

1 online resource (x, 129 pages) : illustrations (some color)

Dissertation/Thesis Chair

MeiHwa Chen

Committee Members

Jeong-Hyon Hwang, Feng Chen

Keywords

multi-objective function, online software anomaly detection, program invariant, Selective regression testing, Anomaly detection (Computer security), Computer software, Software failures, Debugging in computer science, Regression analysis

Subject Categories

Computer Engineering | Computer Sciences

Abstract

Software has been extensively used in various domains to provide online services. With the growing popularity of these types of applications, the quality of the software has a great impact on many of our daily activities [1]. Reliable software executions that deliver expected outcomes are essential for quality services. Software is considered abnormal when its behavior deviates from what is expected at any point during its execution. When anomalous behavior propagates to an exit point of the software and produces an incorrect output or an unexpected termination of the execution, it is considered a software failure. An anomaly may or may not induce a failure, but when a failure occurs there must be at least one point in the program execution that is abnormal. Software anomalous behaviors can be caused by residual code defects or anomalies propagated from the execution context.

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