Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation

Object-oriented application framework is one of the most important implementations of object-oriented software engineering. Normally, a user takes several months of learning in order to become highly productive in using a specific object-oriented application framework. Without proper documentation,...

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Main Authors: Mat Jani H., Lee S.P.
Other Authors: 13609136000
Format: Conference paper
Published: Springer Verlag 2023
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id my.uniten.dspace-30891
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spelling my.uniten.dspace-308912023-12-29T15:55:21Z Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation Mat Jani H. Lee S.P. 13609136000 55664303000 Framework documentation Genetic algorithm (GA) Knuth-Morris-Pratt (KMP) pattern matching algorithm Applications Education Genetic algorithms Information systems Learning systems Object oriented programming Pattern matching Software engineering Application frameworks Case base Case-based learning Framework documentation Knuth-Morris-Pratt (KMP) pattern matching algorithm Machine-learning Nearest neighbor algorithms Object-oriented Object-oriented software engineerings Search process Learning algorithms Object-oriented application framework is one of the most important implementations of object-oriented software engineering. Normally, a user takes several months of learning in order to become highly productive in using a specific object-oriented application framework. Without proper documentation, frameworks are not very usable to framework users. Currently available framework documentation approaches are not very effective for new framework users, and this scenario tends to discourage new users in using frameworks. The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. GA assists in optimizing the search process and performs machine learning. Within the GA, nearest neighbor algorithm is used in determining the most similar recorded case that can be used in solving the new case. A new case is retained in the case base for future retrievals. A framework user is allowed to select from a list of features provided by the framework that he or she is interested in learning, and the system will give an example of application related to the selected features. This paper concludes with a prototype that implements the intelligent framework documentation approach. � 2009 Springer Berlin Heidelberg. Final 2023-12-29T07:55:21Z 2023-12-29T07:55:21Z 2009 Conference paper 10.1007/978-3-642-01112-2_21 2-s2.0-65449152946 https://www.scopus.com/inward/record.uri?eid=2-s2.0-65449152946&doi=10.1007%2f978-3-642-01112-2_21&partnerID=40&md5=f38fceb4cc60259c194a70abc2951e83 https://irepository.uniten.edu.my/handle/123456789/30891 20 LNBIP 202 213 Springer Verlag Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Framework documentation
Genetic algorithm (GA)
Knuth-Morris-Pratt (KMP) pattern matching algorithm
Applications
Education
Genetic algorithms
Information systems
Learning systems
Object oriented programming
Pattern matching
Software engineering
Application frameworks
Case base
Case-based learning
Framework documentation
Knuth-Morris-Pratt (KMP) pattern matching algorithm
Machine-learning
Nearest neighbor algorithms
Object-oriented
Object-oriented software engineerings
Search process
Learning algorithms
spellingShingle Framework documentation
Genetic algorithm (GA)
Knuth-Morris-Pratt (KMP) pattern matching algorithm
Applications
Education
Genetic algorithms
Information systems
Learning systems
Object oriented programming
Pattern matching
Software engineering
Application frameworks
Case base
Case-based learning
Framework documentation
Knuth-Morris-Pratt (KMP) pattern matching algorithm
Machine-learning
Nearest neighbor algorithms
Object-oriented
Object-oriented software engineerings
Search process
Learning algorithms
Mat Jani H.
Lee S.P.
Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
description Object-oriented application framework is one of the most important implementations of object-oriented software engineering. Normally, a user takes several months of learning in order to become highly productive in using a specific object-oriented application framework. Without proper documentation, frameworks are not very usable to framework users. Currently available framework documentation approaches are not very effective for new framework users, and this scenario tends to discourage new users in using frameworks. The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. GA assists in optimizing the search process and performs machine learning. Within the GA, nearest neighbor algorithm is used in determining the most similar recorded case that can be used in solving the new case. A new case is retained in the case base for future retrievals. A framework user is allowed to select from a list of features provided by the framework that he or she is interested in learning, and the system will give an example of application related to the selected features. This paper concludes with a prototype that implements the intelligent framework documentation approach. � 2009 Springer Berlin Heidelberg.
author2 13609136000
author_facet 13609136000
Mat Jani H.
Lee S.P.
format Conference paper
author Mat Jani H.
Lee S.P.
author_sort Mat Jani H.
title Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
title_short Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
title_full Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
title_fullStr Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
title_full_unstemmed Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
title_sort using ga and kmp algorithm to implement an approach to learning through intelligent framework documentation
publisher Springer Verlag
publishDate 2023
_version_ 1806428038083117056
score 13.188404