Improving the Testing of Clustered Systems Through the Effective Usage of Java Benchmarks

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Title: Improving the Testing of Clustered Systems Through the Effective Usage of Java Benchmarks
Authors: Portillo Dominguez, Andres OmarAyala-Rivera, Vanessa
Permanent link: http://hdl.handle.net/10197/9110
Date: 27-Oct-2017
Online since: 2017-12-14T15:11:47Z
Abstract: Nowadays, cluster computing has become a cost-effective and powerful solution for enterprise-level applications. Nevertheless, the usage of this architecture model also increases the complexity of the applications, complicating all activities related to performance optimisation. Thus, many research works have pursued to develop advancements for improving the performance of clusters. Comprehensively evaluating such advancements is key to understand the conditions under which they can be more useful. However, the creation of an appropriate test environment, that is, one which offers different application behaviours (so that the obtained conclusions can be better generalised) is typically an effort-intensive task. To help tackle this problem, this paper presents a tool that helps to decrease the effort and expertise needed to build useful test environments to perform more robust cluster testing. This is achieved by enabling the effective usage of Java Benchmarks to easily create clustered test environments; hence, diversifying the application behaviours that can be evaluated. We also present the results of a practical validation of the proposed tool, where it has been successfully applied to the evaluation of two cluster-related advancements.
Funding Details: Science Foundation Ireland
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Keywords: JavaClustersPerformanceSoftware testing
Other versions: http://redmis2016.com.mx/conisoft2017/
Language: en
Status of Item: Peer reviewed
Conference Details: 5th International Conference in Software Engineering Research and Innovation 2017 (CONISOFT), Merida, Yucatan, Mexico, October, 2017
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science Research Collection

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