Automated statistical approach for memory leak detection: Case studies

dc.contributor.author Šor, Vladimir
dc.contributor.author Salnikov-Tarnovski, Nikita
dc.contributor.author Srirama, Satish Narayana
dc.date.accessioned 2022-03-27T06:06:23Z
dc.date.available 2022-03-27T06:06:23Z
dc.date.issued 2011-11-21
dc.description.abstract Applications written in Java™ language, and in other programming languages running on Java™ Virtual Machine (JVM) are widely used in cloud environments. Although JVM features garbage collection, memory leaks can still happen in these applications. Current solutions for finding memory leaks have several drawbacks which become critical when deployed in distributed and dynamic environments like cloud. Statistical approach for memory leak detection gives good results in terms of false positives and we have implemented automatic statistical approach for memory leak detection in Java™ applications. To test its correctness and performance we have conducted several experiments by finding memory leaks in a large web-application and searching for related bugs in open source projects from Apache Software Foundation. This paper presents the results of these experiments and concludes that automated statistical method for memory leak detection is efficient and can be used also in production systems to find hardly reproducible leaks. © 2011 Springer-Verlag.
dc.identifier.citation Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). v.7045 LNCS(PART 2)
dc.identifier.issn 03029743
dc.identifier.uri 10.1007/978-3-642-25106-1_16
dc.identifier.uri http://link.springer.com/10.1007/978-3-642-25106-1_16
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9343
dc.subject cloud computing
dc.subject Java™
dc.subject Memory leak
dc.subject troubleshooting
dc.title Automated statistical approach for memory leak detection: Case studies
dc.type Book Series. Conference Paper
dspace.entity.type
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