Cyrille Artho, Kazuaki Banzai, Quentin Gros, Guillaume Rousset, L. Ma, Takashi Kitamura, M. Hagiya, Yoshinori Tanabe, M. Yamamoto
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引用次数: 3
Abstract
In this paper, we extend work on model‐based testing for Apache ZooKeeper, to handle watchers (triggers) and improve scalability. In a distributed asynchronous shared storage like ZooKeeper, watchers deliver notifications on state changes. They are difficult to test because watcher notifications involve an initial action that sets the watcher, followed by another action that changes the previously seen state.
期刊介绍：
The journal is the premier outlet for research results on the subjects of testing, verification and reliability. Readers will find useful research on issues pertaining to building better software and evaluating it.
The journal is unique in its emphasis on theoretical foundations and applications to real-world software development. The balance of theory, empirical work, and practical applications provide readers with better techniques for testing, verifying and improving the reliability of software.
The journal targets researchers, practitioners, educators and students that have a vested interest in results generated by high-quality testing, verification and reliability modeling and evaluation of software. Topics of special interest include, but are not limited to:
-New criteria for software testing and verification
-Application of existing software testing and verification techniques to new types of software, including web applications, web services, embedded software, aspect-oriented software, and software architectures
-Model based testing
-Formal verification techniques such as model-checking
-Comparison of testing and verification techniques
-Measurement of and metrics for testing, verification and reliability
-Industrial experience with cutting edge techniques
-Descriptions and evaluations of commercial and open-source software testing tools
-Reliability modeling, measurement and application
-Testing and verification of software security
-Automated test data generation
-Process issues and methods
-Non-functional testing
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