International Journal of System & Software Engineering

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Applications of Artificial Intelligence and Data Mining in Optimizing Software Engineering


Affiliations
1 VIT University, Vellore, Tamil Nadu, India
2 Department of Software Systems, VIT University, Vellore, Tamil Nadu, India
     

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Software engineering usually deals with a huge amount of data while attempting optimization, consistent cost estimation and other activities. Software engineering uses life cycle models with a number of phases that seem most suitable for development of a particular software. These phases have goals, which when carried out effectively and efficiently, can increase the success rate of the software. This paper focuses on two main ideas which involve the use of data mining and artificial intelligence techniques in software engineering respectively. Data mining techniques such as association, classification and clustering can be used to achieve development goals more efficiently by finding hidden patterns in data. As a result, selection of the appropriate data mining technique for each phase of the life cycle model optimizes the development process. Artificial Intelligence techniques like fuzzy logic, genetic algorithms, neural networks, knowledge bases and machine learning are being increasingly used to improve software development procedures and their functionality. Since a software evolves by exposure to varied environments and expertise of developers, there is a huge scope for applying artificial intelligence techniques to software development and engineering.

Keywords

Software Engineering, Data Mining, Fuzzy Logic, Genetic Algorithms, Artificial Neural Networks.
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  • Applications of Artificial Intelligence and Data Mining in Optimizing Software Engineering

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Authors

Upamanyu Chakravarty
VIT University, Vellore, Tamil Nadu, India
Rajit Pimpale
VIT University, Vellore, Tamil Nadu, India
Raghav Sharma
VIT University, Vellore, Tamil Nadu, India
L. Ramanathan
Department of Software Systems, VIT University, Vellore, Tamil Nadu, India

Abstract


Software engineering usually deals with a huge amount of data while attempting optimization, consistent cost estimation and other activities. Software engineering uses life cycle models with a number of phases that seem most suitable for development of a particular software. These phases have goals, which when carried out effectively and efficiently, can increase the success rate of the software. This paper focuses on two main ideas which involve the use of data mining and artificial intelligence techniques in software engineering respectively. Data mining techniques such as association, classification and clustering can be used to achieve development goals more efficiently by finding hidden patterns in data. As a result, selection of the appropriate data mining technique for each phase of the life cycle model optimizes the development process. Artificial Intelligence techniques like fuzzy logic, genetic algorithms, neural networks, knowledge bases and machine learning are being increasingly used to improve software development procedures and their functionality. Since a software evolves by exposure to varied environments and expertise of developers, there is a huge scope for applying artificial intelligence techniques to software development and engineering.

Keywords


Software Engineering, Data Mining, Fuzzy Logic, Genetic Algorithms, Artificial Neural Networks.

References