Paper Info
Title
Testing service oriented architectures using stateful service visualization via machine learning.
Abstract
Today's enterprise software systems are much complicated than the past. Increasing number of dependent applications, heterogeneous technologies and wide usage of Service Oriented Architectures (SOA), where numerous services communicate with each other, makes testing of such systems challenging. For testing these software systems, the concept of service virtualization is gaining popularity. Service virtualization is an automated technique to mimic the behavior of a given real service. Services can be classified as stateless or stateful services. Many services are stateful in nature. Although there are works in the literature for virtualization of state-less services, no such solution exists for stateful services. To the best of our knowledge, this is the first work for stateful service virtualization. We employ classification based and sequence-to-sequence based machine learning algorithms in developing our solutions. We demonstrate the validity of our approach on two data sets collected from real life services and obtain promising results.
Year
DOI
Venue
2018
10.1145/3194733.3194737
AST@ICSE
Keywords
Field
DocType
Software Testing, Service Virtualization, Machine Learning
Virtualization,Service virtualization,Computer science,Enterprise software,Popularity,Software system,Artificial intelligence,Stateful firewall,Stateless protocol,Machine learning,Service-oriented architecture
Conference
ISSN
ISBN
Citations 
2377-8628
978-1-4503-5743-2
1
PageRank 
References 
Authors
0.35
23
2
Name
Order
Citations
PageRank
Hasan Ferit Eniser1133.56
Alper Sen227836.73