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A systematic mapping study on text analysis techniques in software architecture

delete2018-10-01
delete15
PRE
AI
T
Tingting Bi
P
Peng Liang *
A
Antony Tang
C
Chen Yang
DOI:10.1016/j.jss.2018.07.055delete
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Abstract

Abstract

En 中文
Context Information from artifacts in each phase of the software development life cycle can potentially be mined to enhance architectural knowledge. Many text analysis techniques have been proposed for mining such artifacts. However, there is no comprehensive understanding of what artifacts these text analysis techniques analyze, what information they are able to extract or how they enhance architecting activities. Objective: This systematic mapping study aims to study text analysis techniques for mining architecture-related artifacts and how these techniques have been used, and to identify the benefits and limitations of these techniques and tools with respect to enhancing architecting activities. Method: We conducted a systematic mapping study and defined five research questions. We analyzed the results using descriptive statistics and qualitative analysis methods. Results: Fifty-five studies were finally selected with the following results: (1) Current text analysis research emphasizes on architectural understanding and recovery. (2) A spectrum of text analysis techniques have been used in textual architecture information analysis. (3) Five categories of benefits and three categories of limitations were identified. Conclusions: This study shows a steady interest in textual architecture information analysis. The results give clues for future research directions on improving architecture practice through using these text analysis techniques.
Keywords:
Software architecture
Text analysis technique
Systematic mapping study
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Journal

Journal of Systems and Software cover
Journal of Systems and Software
IF:
4.1
Papers:
5.4K
Citations:
8.4K

Organization

S
Swinburne University of Technology
Scholars:
9.3K
Papers: 1.2W
Citations: 2.0W
W
wuhan university
Scholars:
8.0W
Papers: 5.8W
Citations: 70