Software Fault Diagnosis via Intelligent Data Mining Algorithms
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-8825-7_56
Reference24 articles.
1. Duraes JA, Madeira HS (2006) Emulation of software faults: a field data study and a practical approach. IEEE Trans Softw Eng 32:849–867. https://doi.org/10.1109/TSE.2006.113
2. Iannillo AK (2014) A fault injection tool for java software applications. Ph.D. thesis
3. Chakkor S, University of Abdelmalek Essaâdi, Faculty of Sciences, Department of Physics, Communication and Detection Systems Laboratory, Tetouan, Morocco, Baghouri M, Hajraoui A (2015) High resolution identification of wind turbine faults based on optimized ESPRIT algorithm. Int J Image Graph Signal Process 7:32–41
4. Randell B (1975) System structure for software fault tolerance. IEEE Trans Softw Eng SE-1:220–232. http://doi.org/10.1109/TSE.1975.6312842
5. Natella R, Cotroneo D, Duraes J, Madeira H (2013) On fault representativeness of software fault injection. IEEE Trans Softw Eng 39:80–96. https://doi.org/10.1109/TSE.2011.124
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