Validating Feature Models With Respect to Textual Product Line Specifications

被引:7
作者
Sree-Kumar, Anjali [1 ]
Planas, Elena [1 ]
Clariso, Robert [1 ]
机构
[1] Univ Oberta Catalunya UOC, Barcelona, Spain
来源
PROCEEDINGS OF 15TH INTERNATIONAL WORKING CONFERENCE ON VARIABILITY MODELLING OF SOFTWARE-INTENSIVE SYSTEMS, VAMOS 2021 | 2021年
基金
欧盟地平线“2020”;
关键词
Software Product Line; Natural Language Processing; Feature Model Validation; Machine Learning; Requirements Engineering; AUTOMATED EXTRACTION; REQUIREMENTS;
D O I
10.1145/3442391.3442407
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Feature models (FM) are a valuable resource in the analysis of software product lines (SPL). They provide a visual abstraction of the variation points in a family of related software products. FMs can be manually created by domain experts or extracted (semi-) automatically from textual documents such as product descriptions or requirements specifications. Nevertheless, there is no way to measure the accuracy of a FM with respect to the information described in the source documents. This paper proposes a method to quantify and visualize whether the elements in a FM (features and relationships) conform to the information available in a set of specification documents. Both the correctness (choice of representative elements) and completeness (no missing elements) of the FM are considered. Designers can use this feedback to fix defects in the FM or to detect incomplete or inconsistent information in the source documents.
引用
收藏
页数:10
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