Experiments of the effectiveness of dataflow- and controlflow-based test adequacy criteria
ICSE '94 Proceedings of the 16th international conference on Software engineering
Finding failures by cluster analysis of execution profiles
ICSE '01 Proceedings of the 23rd International Conference on Software Engineering
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Come, Let's Play: Scenario-Based Programming Using LSC's and the Play-Engine
Come, Let's Play: Scenario-Based Programming Using LSC's and the Play-Engine
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Active learning for automatic classification of software behavior
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
A study of the behavior of several methods for balancing machine learning training data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Frequent Substructure-Based Approaches for Classifying Chemical Compounds
IEEE Transactions on Knowledge and Data Engineering
QUARK: Empirical Assessment of Automaton-based Specification Miners
WCRE '06 Proceedings of the 13th Working Conference on Reverse Engineering
SMArTIC: towards building an accurate, robust and scalable specification miner
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Efficient mining of iterative patterns for software specification discovery
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning from mistakes: a comprehensive study on real world concurrency bug characteristics
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Mining significant graph patterns by leap search
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Mining temporal specifications for error detection
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Contrasting Sequence Groups by Emerging Sequences
DS '09 Proceedings of the 12th International Conference on Discovery Science
Malware detection based on mining API calls
Proceedings of the 2010 ACM Symposium on Applied Computing
A discriminative model approach for accurate duplicate bug report retrieval
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
Authorship classification: a syntactic tree mining approach
Proceedings of the ACM SIGKDD Workshop on Useful Patterns
An occurrence based approach to mine emerging sequences
DaWaK'10 Proceedings of the 12th international conference on Data warehousing and knowledge discovery
NDPMine: efficiently mining discriminative numerical features for pattern-based classification
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Mining closed discriminative dyadic sequential patterns
Proceedings of the 14th International Conference on Extending Database Technology
Scalable graph analyzing approach for software fault-localization
Proceedings of the 6th International Workshop on Automation of Software Test
Authorship classification: a discriminative syntactic tree mining approach
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Learning actions in complex software systems
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Mining significant time intervals for relationship detection
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
Mining emerging patterns by streaming feature selection
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Debugging embedded multimedia application traces through periodic pattern mining
Proceedings of the tenth ACM international conference on Embedded software
Mining explicit rules for software process evaluation
Proceedings of the 2013 International Conference on Software and System Process
Mining succinct predicated bug signatures
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
Empirical Software Engineering
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Software is a ubiquitous component of our daily life. We often depend on the correct working of software systems. Due to the difficulty and complexity of software systems, bugs and anomalies are prevalent. Bugs have caused billions of dollars loss, in addition to privacy and security threats. In this work, we address software reliability issues by proposing a novel method to classify software behaviors based on past history or runs. With the technique, it is possible to generalize past known errors and mistakes to capture failures and anomalies. Our technique first mines a set of discriminative features capturing repetitive series of events from program execution traces. It then performs feature selection to select the best features for classification. These features are then used to train a classifier to detect failures. Experiments and case studies on traces of several benchmark software systems and a real-life concurrency bug from MySQL server show the utility of the technique in capturing failures and anomalies. On average, our pattern-based classification technique outperforms the baseline approach by 24.68% in accuracy.