Automatic Software Test Data Generation

Access: Use of this item is restricted to the UNT Community
Description:

In software testing, it is often desirable to find test inputs that exercise specific program features. Finding these inputs manually, is extremely time consuming, especially, when the software being tested is complex. Therefore, there have been numerous attempts automate this process. Random test data generation consists of generating test inputs at random, in the hope that they will exercise the desired software features. Often the desired inputs must satisfy complex constraints, and this makes a random approach seem unlikely to succeed. In contrast, combinatorial optimization techniques, such as those using genetic algorithms, are meant to solve difficult problems involving simultaneous satisfaction of many constraints.

Creator(s): Munugala, Ajay Kumar
Creation Date: December 2002
Partner(s):
UNT Libraries
Collection(s):
UNT Theses and Dissertations
Usage:
Total Uses: 72
Past 30 days: 5
Yesterday: 0
Creator (Author):
Publisher Info:
Publisher Name: University of North Texas
Place of Publication: Denton, Texas
Date(s):
  • Creation: December 2002
  • Digitized: July 24, 2007
Description:

In software testing, it is often desirable to find test inputs that exercise specific program features. Finding these inputs manually, is extremely time consuming, especially, when the software being tested is complex. Therefore, there have been numerous attempts automate this process. Random test data generation consists of generating test inputs at random, in the hope that they will exercise the desired software features. Often the desired inputs must satisfy complex constraints, and this makes a random approach seem unlikely to succeed. In contrast, combinatorial optimization techniques, such as those using genetic algorithms, are meant to solve difficult problems involving simultaneous satisfaction of many constraints.

Degree:
Level: Master's
Discipline: Computer Science
Note:

Problem in Lieu of Thesis

Language(s):
Subject(s):
Keyword(s): Software development | software testing | software test data
Contributor(s):
Partner:
UNT Libraries
Collection:
UNT Theses and Dissertations
Identifier:
  • ARK: ark:/67531/metadc3276
Resource Type: Thesis or Dissertation
Format: Text
Rights:
Access: Use restricted to UNT Community
License: Copyright
Holder: Munugala, Ajay Kumar
Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.