The Experts below are selected from a list of 18 Experts worldwide ranked by ideXlab platform
Chin Kuan Ho - One of the best experts on this subject based on the ideXlab platform.
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An Interactive Method for Validating Stage Configuration
Journal of Software Engineering and Applications, 2020Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Chin Kuan HoAbstract:Software product Line (SPL) is an emerging methodology for developing software products. Stage-configuration is one the important processes applying to the SPL. In stage-configuration, different groups and different people make configuration choices in different stages. Therefore, a successful software product is highly dependent on the validity of stage-configuration process. In this paper, a rule-based method is proposed for validating stage-configuration in SPL. A logical representation of variability using First Order Logic (FOL) is provided. Five operations: validation rules, explanation and corrective explanation, propagation and Delete-Cascade, filtering and cardinality test are studied as proposed operations for validating stage-configuration. The relevant contributions of this paper are: implementing automated consistency checking among constraints during stage-configuration process based on three levels (Variant- to-variant, variant-to-variation point, and variation point-to-variation point), define interactive explanation and corrective explanation, define a filtering operation to guide the user within stage-configuration, and define (explicitly) Delete-Cascade validation
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HICSS - Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer:1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
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Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer: 1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
Abdelrahman Osman Elfaki - One of the best experts on this subject based on the ideXlab platform.
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An Interactive Method for Validating Stage Configuration
Journal of Software Engineering and Applications, 2020Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Chin Kuan HoAbstract:Software product Line (SPL) is an emerging methodology for developing software products. Stage-configuration is one the important processes applying to the SPL. In stage-configuration, different groups and different people make configuration choices in different stages. Therefore, a successful software product is highly dependent on the validity of stage-configuration process. In this paper, a rule-based method is proposed for validating stage-configuration in SPL. A logical representation of variability using First Order Logic (FOL) is provided. Five operations: validation rules, explanation and corrective explanation, propagation and Delete-Cascade, filtering and cardinality test are studied as proposed operations for validating stage-configuration. The relevant contributions of this paper are: implementing automated consistency checking among constraints during stage-configuration process based on three levels (Variant- to-variant, variant-to-variation point, and variation point-to-variation point), define interactive explanation and corrective explanation, define a filtering operation to guide the user within stage-configuration, and define (explicitly) Delete-Cascade validation
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Software Product Line- A Ruled-Based Approach
2012Co-Authors: Abdelrahman Osman ElfakiAbstract:The operations that are discussed and solved in this book consist of 12 operations. There are six operations for validating domain engineering (determine SPL validity, inconsistency detection, dead feature detection, false option detection, wrong cardinality detection, and redundancy detection) and six operations for validating the configuration process (constraint consistency checking, propagation and Delete Cascade, interactive explanation, corrective explanation, optimization, and deadlock detection).
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HICSS - Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer:1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
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Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer: 1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
Somnuk Phon-amnuaisuk - One of the best experts on this subject based on the ideXlab platform.
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An Interactive Method for Validating Stage Configuration
Journal of Software Engineering and Applications, 2020Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Chin Kuan HoAbstract:Software product Line (SPL) is an emerging methodology for developing software products. Stage-configuration is one the important processes applying to the SPL. In stage-configuration, different groups and different people make configuration choices in different stages. Therefore, a successful software product is highly dependent on the validity of stage-configuration process. In this paper, a rule-based method is proposed for validating stage-configuration in SPL. A logical representation of variability using First Order Logic (FOL) is provided. Five operations: validation rules, explanation and corrective explanation, propagation and Delete-Cascade, filtering and cardinality test are studied as proposed operations for validating stage-configuration. The relevant contributions of this paper are: implementing automated consistency checking among constraints during stage-configuration process based on three levels (Variant- to-variant, variant-to-variation point, and variation point-to-variation point), define interactive explanation and corrective explanation, define a filtering operation to guide the user within stage-configuration, and define (explicitly) Delete-Cascade validation
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HICSS - Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer:1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
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Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer: 1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
Saravanan Muthaiyah - One of the best experts on this subject based on the ideXlab platform.
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HICSS - Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer:1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
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Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer: 1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
Ibrahim H. M. Magboul - One of the best experts on this subject based on the ideXlab platform.
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HICSS - Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer:1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.
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Defining Variability in DSS: An Intelligent Method for Knowledge Representation and Validation
2010 43rd Hawaii International Conference on System Sciences, 2010Co-Authors: Abdelrahman Osman Elfaki, Somnuk Phon-amnuaisuk, Saravanan Muthaiyah, Ibrahim H. M. Magboul, Chin Kuan HoAbstract:Managing knowledge is both a challenging and complex task. There is a number techniques for making decisions in today's knowledge-based economies. Decision support systems (DSS) have been developed to aid the decision-making process to find solutions for multiple problems. One aspect that hinders successful decision making is the issue of variability definition. The aim of this paper is to define variability by proposing an intelligent method. Knowledge representation is based in two layer: 1) the upper layer i.e. graphical representation and 2) the lower layer i.e. a mathematical algorithm. We present a method that defines and provides auto-support for five operations in knowledge validation particularly dependency constraint rules, propagation, Delete-Cascade, logical inconsistency and dead choice detection.