Improving the Testing of Java Garbage Collection Through an Efficient Benchmark Generation

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Title: Improving the Testing of Java Garbage Collection Through an Efficient Benchmark Generation
Authors: Portillo-Dominguez, A. OmarAyala-Rivera, Vanessa
Permanent link: http://hdl.handle.net/10197/10606
Date: 26-Oct-2018
Online since: 2019-05-22T09:59:50Z
Abstract: Garbage Collection (GC) is a core feature of multiple modern technologies (e.g., Java, Android). On one hand, it offers significant software engineering benefits over explicitly memory management, like preventing most types of memory leaks. On the other hand, GC is a known cause of performance degradation. However, it is considerably challenging to understand its exact impact on the overall application performance. This is because the non-deterministic nature of GC makes very complex to properly model it and evaluate its performance impacts. To help tackling these problems, we present an engine to generate realistic GC benchmarks by enabling to effectively capture the GC/memory behaviours experienced by real-world Java applications. We also demonstrate, through a comprehensive experimental evaluation, how such benchmarks can be useful to strengthen the evaluation of GC-related advancements.
Funding Details: European Commission - European Regional Development Fund
Science Foundation Ireland
metadata.dc.description.othersponsorship: Southern & Eastern Regional Operational Programme to Lero - the Irish Software Research Centre (www.lero.ie)
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2018 IEEE
Keywords: Software testingObject-oriented systemsJavaGarbage collectionBenchmark generationPerformance
DOI: 10.1109/conisoft.2018.8645889
Language: en
Status of Item: Not peer reviewed
Is part of: Kellenberger, P. (ed.). Proceedings: the 2018 6th International Conference in Software Engineering Research and Innovation (CONISOFT 2018)
Conference Details: CONISOFT 2018: 6th International Conference in Software Engineering Research and Innovation, San Luis Potosí, Mexico, 24-26 October 2018
ISBN: 978-1-5386-6577-0
Appears in Collections:Computer Science Research Collection

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This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.