Transaction mapping based approach for mining software specifications

Abstract

Specification mining is a machine learning approach for discovering specifications of the protocols that code must obey when interacting with an application program interface or abstract data type. Two major concerns in engineering software systems are high maintenance costs and reliability of systems. To reduce maintenance efforts, there is a need for automated tools to help software developers understand their existing code base. So, there is a need to extract specifications to aid program comprehension. In this paper a novel technique to efficiently mine software specifications, called TM_TraceMiner is proposed which mines software specifications from program execution traces. The Transaction Mapping algorithm is currently one of the fastest approaches. To address the limitations of Apriori-like methods and FP-growth methods, a mining paradigm has been proposed, which uses Transaction Mapping algorithm. Experimental data shows that this method outperforms the other two methods.