Treffer: Model-based statistical testing of a cluster utility

Title:
Model-based statistical testing of a cluster utility
Authors:
SWAIN, W. Thomas, SCOTT, Stephen L
Source:
Computational science (Atlanta GA, 22-25 May 2005)Lecture notes in computer science. :443-450
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 6 ref 3
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Analyse fonctionnelle, Functional analysis, Análisis funcional, Analyse quantitative, Quantitative analysis, Análisis cuantitativo, Analyse statistique, Statistical analysis, Análisis estadístico, Approche probabiliste, Probabilistic approach, Enfoque probabilista, Automatisation, Automation, Automatización, Calcul réparti, Distributed computing, Cálculo repartido, Certification, Certificación, Détection défaut, Defect detection, Detección imperfección, Fiabilité logiciel, Software reliability, Fiabilidad logicial, Haute performance, High performance, Alto rendimiento, Modélisation, Modeling, Modelización, Système réparti, Distributed system, Sistema repartido, Test statistique, Statistical test, Test estadístico, Grappe calculateur, Cluster computing, Racimo calculadura, Génération test, Test generation, Generación prueba
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Software Quality Research Laboratory, University of Tennessee Department of Computer Science, Knoxville, Tennessee 37996, United States
Network and Cluster Computing Group, Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=16991238
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16991238
Database:
PASCAL Archive

Weitere Informationen

As High Performance Computing becomes more collaborative, software certification practices are needed to quantify the credibility of shared applications. To demonstrate quantitative certification testing, Model-Based Statistical Testing (MBST) was applied to cexec, a cluster control utility developed in the Network and Cluster Computing Group of Oak Ridge National Laboratory. MBST involves generation of test cases from a usage model. The test results are then analyzed statistically to measure software reliability. The population of cexec uses was modeled in terms of input selection choices. The J Usage Model Builder Library (JUMBL) provided the capability to generate test cases directly as Python scripts. Additional Python functions and shell scripts were written to complete a test automation framework. The resulting certification capability employs two large test suites. One consists of weighted test cases to provide an intensive fault detection capability, while the other consists of random test cases to provide a statistically meaningful assessment of reliability.