MuSRGM: A Genetic Algorithm-Based Dynamic Combinatorial Deep Learning Model for Software Reliability Engineering

In the software testing phase, software reliability growth models (SRGMs) are commonly used to evaluate the reliability of software systems. Traditional SRGMs are restricted by their assumption of a continuous growth pattern for the failure detection rate (FDR) throughout the testing phase. However,...

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Veröffentlicht in:	IEICE Transactions on Information and Systems 2024/06/01, Vol.E107.D(6), pp.761-771
Hauptverfasser:	FU, Ning, RYU, Duksan, KIM, Suntae
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy attention Combinatorial analysis Datasets Deep learning Failure detection genetic algorithm Genetic algorithms Growth models LSTM Machine learning Performance prediction Reliability analysis Reliability engineering Software engineering Software reliability software reliability growth models Software testing System reliability
Online-Zugang:	Volltext
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