Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Edge profiling versus path profiling: the showdown
POPL '98 Proceedings of the 25th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Basket Analysis for Graph Structured Data
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Object-Oriented Program Behavior Analysis Based on Control Patterns
APAQS '01 Proceedings of the Second Asia-Pacific Conference on Quality Software
A quickstart in frequent structure mining can make a difference
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
JavaTM just-in-time compiler and virtual machine improvements for server and middleware applications
VM'04 Proceedings of the 3rd conference on Virtual Machine Research And Technology Symposium - Volume 3
ORIGAMI: Mining Representative Orthogonal Graph Patterns
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
CCCM '08 Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 03
OptiScope: Performance Accountability for Optimizing Compilers
Proceedings of the 7th annual IEEE/ACM International Symposium on Code Generation and Optimization
Discovery of frequent graph patterns that consist of the vertices with the complex structures
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Transactions on Rough Sets III
Mining opportunities for code improvement in a just-in-time compiler
CC'10/ETAPS'10 Proceedings of the 19th joint European conference on Theory and Practice of Software, international conference on Compiler Construction
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This paper presents FlowGSP, a data-mining algorithm that discovers frequent sequences of attributes in subpaths of a flow graph. FlowGSP was evaluated using flow graphs derived from the execution of transactions in the IBM® WebSphere® Application Server, a large real-world enterprise application server. The vertices of this flow graph may represent single instructions, bytecodes, basic blocks, regions, or entire methods. These vertices are annotated with attributes that correspond to run-time characteristics of the execution of the program. FlowGSP successfully identified a number of existing characteristics of the Web-Sphere Application Server which had previously been discovered only through extensive manual examination. In addition, a multithreaded implementation of FlowGSP demonstrates the algorithm's suitability for exploiting the resources of modern multi-core computers.