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» A Machine Learning Approach for Statistical Software Testing
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ICST
2009
IEEE
14 years 2 months ago
Test Input Generation Using UML Sequence and State Machines Models
We propose a novel testing approach that combines information from UML sequence models and state machine models. Current approaches that rely solely on sequence models do not cons...
Aritra Bandyopadhyay, Sudipto Ghosh
ELPUB
2007
ACM
13 years 11 months ago
The Fight against Spam - A Machine Learning Approach
The paper presents a brief survey of the fight between spammers and antispam software developers, and also describes new approaches to spam filtering. In the first two sections we...
Karel Jezek, Jiri Hynek
ACL
2007
13 years 8 months ago
Supertagged Phrase-Based Statistical Machine Translation
Until quite recently, extending Phrase-based Statistical Machine Translation (PBSMT) with syntactic structure caused system performance to deteriorate. In this work we show that i...
Hany Hassan, Khalil Sima'an, Andy Way
ACL
2009
13 years 5 months ago
Phrase-Based Statistical Machine Translation as a Traveling Salesman Problem
An efficient decoding algorithm is a crucial element of any statistical machine translation system. Some researchers have noted certain similarities between SMT decoding and the f...
Mikhail Zaslavskiy, Marc Dymetman, Nicola Cancedda
ASWEC
2005
IEEE
14 years 1 months ago
A UML Approach to the Generation of Test Sequences for Java-Based Concurrent Systems
Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this speci...
Soon-Kyeong Kim, Luke Wildman, Roger Duke