@inproceedings{48f31c3aee1d4c6abee6fac0d5b66f66,
title = "Hidden markov model based automated fault localization for integration testing",
abstract = "Integration testing is an expensive activity in software testing, especially for fault localization in complex systems. Model-based diagnosis (MBD) provides various benefits in terms of scalability and robustness. In this work, we propose a novel MBD approach for the automated fault localization in integration testing. Our method is based on Hidden Markov Model (HMM) which is an abstraction of system's component to simulate component's behaviour. The core of this method is a fault localization algorithm that gives out the set of suspect faulty components and a backward algorithm that calculates the matching degree between the HMM and the real system to evaluate the confidence degree of the localization conclusion. The proposed method is evaluated on a specific test bed and is applied to a simple helicopter control system case study.",
keywords = "Automated Fault Localization, Hidden Markov Model, Integration Testing, Model-Based Diagnosis",
author = "Ning Ge and Shin Nakajima and Marcmarc Pantel",
year = "2013",
doi = "10.1109/ICSESS.2013.6615284",
language = "英语",
isbn = "9781467349970",
series = "Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS",
pages = "184--187",
booktitle = "ICSESS 2013 - Proceedings of 2013 IEEE 4th International Conference on Software Engineering and Service Science",
note = "2013 4th IEEE International Conference on Software Engineering and Service Science, ICSESS 2013 ; Conference date: 23-05-2013 Through 25-05-2013",
}