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Learning-based Software Testing using Symbolic Constraint Solving Methods
Software testing remains one of the most important but expensive approaches to ensure high-quality software today. In order to reduce the cost of testing, over the last several decades, various techniques such as formal verification and inductive learning have been used for test automation in previous research.
In this thesis, we present a specification-based black-box testing approach,
Contributors
- Meinke Karl Professor
- Hähnle Reiner Professor
- KTH Skolan för datavetenskap och kommunikation (CSC) Teoretisk datalogi, TCS
Creator
- Niu Fei , KTH, Teoretisk datalogi, TCS
Publisher
- KTH Royal Institute of Technology
Type of item
- Other academic
- Licentiate thesis, comprehensive summary
- dissertation
- Thesis
Date
- 2011
- 2011-11-07
- 2011-10-12
- 2011-10-12
- 2011-11-07
- 2011
Contributors
- Meinke Karl Professor
- Hähnle Reiner Professor
- KTH Skolan för datavetenskap och kommunikation (CSC) Teoretisk datalogi, TCS
Creator
- Niu Fei , KTH, Teoretisk datalogi, TCS
Publisher
- KTH Royal Institute of Technology
Type of item
- Other academic
- Licentiate thesis, comprehensive summary
- dissertation
- Thesis
Date
- 2011
- 2011-11-07
- 2011-10-12
- 2011-10-12
- 2011-11-07
- 2011
Providing institution
Aggregator
Rights statement for the media in this item (unless otherwise specified)
- http://rightsstatements.org/vocab/InC/1.0/
- http://rightsstatements.org/vocab/InC/1.0/
Identifier
- oai:DiVA.org:kth-41932
Format
- electronicvii, 47
- electronic
- vii, 47
Language
- en
- en
Is part of
- http://data.theeuropeanlibrary.org/Collection/a1041
Relations
- Trita-CSC-A1653-57232011:15
Year
- 2011
Providing country
- Sweden
Collection name
First time published on Europeana
- 2014-09-07T11:22:13.253Z
Last time updated from providing institution
- 2014-09-07T11:22:13.253Z