ERA

Download the full-sized PDF of Test case generation using symbolic grammars and quasirandom sequencesDownload the full-sized PDF

Analytics

Share

Permanent link (DOI): https://doi.org/10.7939/R3611F

Download

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Graduate Studies and Research, Faculty of

Collections

This file is in the following collections:

Theses and Dissertations

Test case generation using symbolic grammars and quasirandom sequences Open Access

Descriptions

Other title
Subject/Keyword
firewall policies
data generation
grammar-based testing
grammars
testing
test data
symbolic grammars
quasi-random sequences
model-based testing
adaptive testing
firewall testing
firewalls
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Felix Reyes, Alejandro
Supervisor and department
Miller, James (Electrical and Computer Engineering)
Examining committee member and department
Hoover, H. James (Computing Science)
Cockburn, Bruce F. (Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization

Date accepted
2010-12-22T22:36:30Z
Graduation date
2011-06
Degree
Master of Science
Degree level
Master's
Abstract
This work presents a new test case generation methodology, which has a high degree of automation (cost reduction); while providing increased “power” in terms of defect detection (benefits increase). Our solution is a variation of model-based testing, which takes advantage of symbolic grammars (a context-free grammar where terminals are replaced by regular expressions that represent their solution space) and quasi-random sequences to generate test cases. Previous test case generation techniques are enhanced with adaptive random testing to maximize input space coverage; and selective and directed sentence generation techniques to optimize sentence generation. Our solution was tested by generating 200 firewall policies containing up to 20 000 rules from a generic firewall grammar. Our results show how our system generates test cases with superior coverage of the input space, increasing the probability of defect detection while reducing considerably the needed number the test cases compared with other previously used approaches.
Language
English
DOI
doi:10.7939/R3611F
Rights
License granted by Alejandro Felix Reyes (afelix@ualberta.ca) on 2010-12-22T22:22:00Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication

File Details

Date Uploaded
Date Modified
2014-04-29T19:09:20.601+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 1016703
Last modified: 2015:10:12 15:27:05-06:00
Filename: Felix_Alejandro_Spring 2011.pdf
Original checksum: bbf224ad648448ca3778231012bd804f
Well formed: true
Valid: true
File title: Microsoft Word - Test Case Generation using Symbolic Grammars and QuasiRandom Sequences - Revised - Copy
File author: user
Page count: 129
Activity of users you follow
User Activity Date