Feature-oriented software requirements specification

ZHANG Guo-sheng

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Feature-oriented software requirements specification

更新时间：2026-09-04

- Feature-oriented software requirements specification
- Vol. 36, Issue 11, Pages: 20-23(2019)
- 作者机构：
  
  云南大学信息学院,云南,昆明,650091
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2019
- 稿件说明：
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张国生. 面向特征的软件需求规约[J]. 微电子学与计算机, 2019, 36(11): 20-23.

ZHANG Guo-sheng. Feature-oriented software requirements specification[J]. 2019, 36(11): 20-23.
张国生. 面向特征的软件需求规约[J]. 微电子学与计算机, 2019, 36(11): 20-23. DOI：

ZHANG Guo-sheng. Feature-oriented software requirements specification[J]. 2019, 36(11): 20-23. DOI：

摘要

基于大数据方法对自然语言用户需求文本进行分析

用TF-IDF方法计算特征词在需求文本中的出现频率

归一化后求得特征词在文本中的权重

用卡方统计量衡量特征词和簇之间的相关性

用k-均值算法和二分k-均值算法对特征集聚类

生成用户需求文本特征树

并映射为需求功能分解树中对应的需求功能

使需求特征语义、结构更加清晰

增强了自动需求规约能力

提高了需求分析效率

使需求规约更加科学、合理、准确.

Abstract

Based on big data method

the text of natural language user requirement is analyzed. TF-IDF method is used to calculate the frequency of feature words appearing in the requirement text. After normalization

the weight of feature words in the text is obtained. Chi-square statistics is used to measure the correlation between feature words and clusters. The feature set is clustered by k-means algorithm and bisecting k-means algorithm

and the user requirement text feature tree is generated

which is mapped to the corresponding requirement function in the requirement function decomposition tree. The semantics and structure of requirement feature are clearer. The ability of automatic requirement specification is enhanced. The efficiency of requirement analysis is improved

and the requirement specification is more scientific

reasonable and accurate.

关键词

Keywords

references

DAVIS A M. The design of a family of application- oriented requirements languages[J]. Computer, 1982, 15(5):21-28. DOI: 21

SALTON G, WONG A, YANG C S. A vector space model for automatic indexing[J].Communications of the ACM, 1975.18(11): 613-620. DOI: 613

Washington WIEGERS K E. Software requirements[M]. Washington:Microsoft Press, 1999.

SAVARESI S M, BOLEY D. On the performance of bisecting k-meansand PDDP[C]//Proc. of the 1st SIAM International Conference onData Mining.Chicago, USA: [s.n.], 2001: 1-14.

MACQUEEN J. Some methods for classification and analysis of multivariate observations[C]//Proc. of the 5th Berkeley Symposium on Mathematical Statistics and Probability. Los Angeles: University of California Press, 1967: 281-297.

TURNER C R, FUGGETTA A, LAVAZZA L, et al. A conceptual basis for feature engineering[J]. Journal of Systems and Software, 1999, 49(1):3-15. DOI: 3

张国生.需求演化过程建模[J].微电子学与计算机, 2012, 29(5):54-57. DOI: 54

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