Automated Statistical Approach for Memory Leak Detection: Case Studies

被引:0
|
作者
Sor, Vladimir [1 ,2 ]
Salnikov-Tarnovski, Nikita [2 ]
Srirama, Satish Narayana [1 ]
机构
[1] Univ Tartu, Inst Comp Sci, J Liivi 2, Tartu, Estonia
[2] AS Webmedia R&D, Tartu, Estonia
关键词
Memory leak; troubleshooting; !text type='Java']Java[!/text] (TM); cloud computing;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Applications written in Java (TM) language, and in other programming languages running on Java (TM) 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 (TM) 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.
引用
收藏
页码:635 / +
页数:2
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