Date of Award


Document Type


Degree Name

Master of Science (MS)


Computer Science

First Advisor

Haifeng Guo

Second Advisor

Harvey Siy

Third Advisor

Haorong Li


Fault detection is helpful to cut down the failure causes by logically locating and eliminating defects. In this thesis, we present a novel fault detection technique via structured input data which can be represented by a grammar. We take a set of well-distributed test cases as input, each of which has a set of test requirements. We illustrate that test requirements come from structured data can be effectively used as coverage criteria to reduce the test suites. We then propose an automatic fault detection approach to locate software bugs which are shown in failed test cases. This method can be applied in testing data-input-critical software such as compilers, translators, reactive systems etc. Preliminary experimental study proves that our fault detection approach is able to precisely locate the faults of software under test from failed test cases.


A Thesis Presented to the Department of Computer Science and the Faculty of the Graduate College University of Nebraska In Partial Fulfilment of the Requirements for the Degree Master of Science in Computer Science University of Nebraska at Omaha. Copyright 2013 Songqing Liu.