Automatic Test Generation on the Basis of a Semantic Network

被引：0

作者：

Dolgova, Elena ^{[1
]}

Eriskina, E., V ^{[1
]}

Faizrakhmanov, Rustam ^{[1
]}

Kasyanova, E. A. ^{[1
]}

Kurushin, D. S. ^{[1
]}

Nesterova, N. M. ^{[1
]}

Soboleva, O., V ^{[1
]}

机构：

[1] State Natl Res Politech Univ, Komsomolsky Av 29, Perm 614000, Russia

来源：

DIGITAL SCIENCE | 2019年 / 850卷

关键词：

Test generation; Automatic test generation; Natural-language text; Domain model; Denotative graph; Generation of test templates; Trees AND/OR; n-grams; Associative links; !text type='Python']Python[!/text; Pymystem; Rutermextract;

D O I：

10.1007/978-3-030-02351-5_20

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper is devoted to the problem of automatic generating of tests based on the natural language texts. The methods of generating natural language questions are considered. The domain model presented in the form of a denotatum graph and the experiments verifying the model are described. The program algorithm for generating tests based on the texts in natural language and pseudocode are given. The analysis of the results of this program and the main shortcomings are demonstrated. The algorithm of the program "finalization" using n-grams and the search of associative connections and its pseudocode are shown. The test generated as a result of the algorithm usage is presented.

引用

页码：159 / 165

页数：7

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