Program evolution: processes of software change
Program evolution: processes of software change
Cecil: A Sequencing Constraint Language for Automatic Static Analysis Generation
IEEE Transactions on Software Engineering
Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Model checking
Testing object-oriented systems: models, patterns, and tools
Testing object-oriented systems: models, patterns, and tools
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
LSCs: Breathing Life into Message Sequence Charts
Formal Methods in System Design
Software Engineering Economics
Software Engineering Economics
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Leveraging Legacy System Dollars for E-Business
IT Professional
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
Managing Interesting Rules in Sequence Mining
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
From run-time behavior to usage scenarios: an interaction-pattern mining approach
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Light-Weight Product-Lines for Evolution and Maintenance of Web Sites
CSMR '03 Proceedings of the Seventh European Conference on Software Maintenance and Reengineering
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Verifying safety policies with size properties and alias controls
Proceedings of the 27th international conference on Software engineering
Mining periodic patterns with gap requirement from sequences
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Perracotta: mining temporal API rules from imperfect traces
Proceedings of the 28th international conference on Software 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
Efficient mining of iterative patterns for software specification discovery
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient mining of recurrent rules from a sequence database
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Temporal logic for scenario-based specifications
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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
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Software specifications are often lacking, incomplete and outdated in the industry. Lack and incomplete specifications cause various software engineering problems. Studies have shown that program comprehension takes up to 45% of software development costs. One of the root causes of the high cost is the lack-of documented specification. Also, outdated and incomplete specification might potentially cause bugs and compatibility issues. In this paper, we describe novel data mining techniques to mine or reverse engineer these specifications from the pool of software engineering data. A large amount of software data is available for analysis. One form of software data is program execution traces. A program trace can be viewed as a sequence of events collected when a program is run. A set of program traces in turn can be viewed as a sequence database. In this paper, we present some novel work in mining software specifications by employing novel pattern mining and rule mining techniques. Performance studies show the scalability of our technique. Case studies on traces of a real industrial application show the utility of our technique in recovering program specifications from execution traces.