The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Propomos um novo sistema de inferência de intenções dos programadores, COSMO, baseado em uma classificação de declarações de atribuição. COSMO é um subsistema do nosso ambiente de programação inteligente para educação em programação. O ambiente de programação consiste em um sistema de compreensão de programas projetado para programadores novatos e um sistema de apoio à avaliação de programas novatos projetado para professores, sendo que ambos utilizam a técnica de fatiamento de programas. Normalmente, o método de fatiamento do programa requer a seleção de critérios de fatiamento. No entanto, a seleção automática de critérios de fatiamento eficazes é difícil. Aqui propomos um novo sistema de inferência de intenções dos programadores COSMO com seleção automática de critérios de fatiamento eficazes. Em nosso sistema, os critérios de fatiamento são inferidos utilizando o modelo de estrutura de contexto dos programas. Os programas são considerados textos em linguagem natural no modelo e analisados usando um pensamento semelhante em análises de estrutura de contexto de textos em linguagem natural. O modelo é baseado em uma classificação de instruções de atribuição utilizando análise de dependência de programas. Além disso, o COSMO obtém redes com informações sobre a decomposição top-down de problemas como resultado da inferência da intenção dos programadores. Portanto, o COSMO é útil para compreender programas sem conhecimento pressuposto.
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Haruo KAWASAKI, "Inferring Programmers' Intention by the Use of Context Structure Model of Programs" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 4, pp. 835-844, April 2000, doi: .
Abstract: We propose a new inferring programmers' intention system COSMO based on a classification of assignment statements. COSMO is a subsystem of our intelligent programming environment for programming education. The programming environment consists of a program understanding system designed for novice programmers and a novice program evaluation support system designed for teachers, both of which use the technique of the program slicing. Usually, the method of program slicing requires selection of slicing criteria. However, automatic selection of effective slicing criteria is difficult. Here we propose a new inferring programmers' intention system COSMO with automatic selection of effective slicing criteria. In our system, the slicing criteria are inferred using the context structure model of programs. Programs are regarded as natural language texts in the model and analyzed using a similar thinking in context structure analyses of natural language texts. The model is based on a classification of assignment statements using dependence analysis of programs. Furthermore, COSMO obtains networks with information on top-down decomposition of problems as a result of inferring programmers' intention. Therefore, COSMO is useful for understanding programs without presupposed knowledge.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_4_835/_p
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@ARTICLE{e83-d_4_835,
author={Haruo KAWASAKI, },
journal={IEICE TRANSACTIONS on Information},
title={Inferring Programmers' Intention by the Use of Context Structure Model of Programs},
year={2000},
volume={E83-D},
number={4},
pages={835-844},
abstract={We propose a new inferring programmers' intention system COSMO based on a classification of assignment statements. COSMO is a subsystem of our intelligent programming environment for programming education. The programming environment consists of a program understanding system designed for novice programmers and a novice program evaluation support system designed for teachers, both of which use the technique of the program slicing. Usually, the method of program slicing requires selection of slicing criteria. However, automatic selection of effective slicing criteria is difficult. Here we propose a new inferring programmers' intention system COSMO with automatic selection of effective slicing criteria. In our system, the slicing criteria are inferred using the context structure model of programs. Programs are regarded as natural language texts in the model and analyzed using a similar thinking in context structure analyses of natural language texts. The model is based on a classification of assignment statements using dependence analysis of programs. Furthermore, COSMO obtains networks with information on top-down decomposition of problems as a result of inferring programmers' intention. Therefore, COSMO is useful for understanding programs without presupposed knowledge.},
keywords={},
doi={},
ISSN={},
month={April},}
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TY - JOUR
TI - Inferring Programmers' Intention by the Use of Context Structure Model of Programs
T2 - IEICE TRANSACTIONS on Information
SP - 835
EP - 844
AU - Haruo KAWASAKI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2000
AB - We propose a new inferring programmers' intention system COSMO based on a classification of assignment statements. COSMO is a subsystem of our intelligent programming environment for programming education. The programming environment consists of a program understanding system designed for novice programmers and a novice program evaluation support system designed for teachers, both of which use the technique of the program slicing. Usually, the method of program slicing requires selection of slicing criteria. However, automatic selection of effective slicing criteria is difficult. Here we propose a new inferring programmers' intention system COSMO with automatic selection of effective slicing criteria. In our system, the slicing criteria are inferred using the context structure model of programs. Programs are regarded as natural language texts in the model and analyzed using a similar thinking in context structure analyses of natural language texts. The model is based on a classification of assignment statements using dependence analysis of programs. Furthermore, COSMO obtains networks with information on top-down decomposition of problems as a result of inferring programmers' intention. Therefore, COSMO is useful for understanding programs without presupposed knowledge.
ER -