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Software quality assessment model: a systematic mapping study

delete2019-07-26
delete17
PRE
AI
鄢萌 (Meng Yan)
X
Xin Xia *
张小洪 (Xiaohong Zhang)
徐玲 封面图
徐玲 (Ling Xu)
杨丹 封面图
杨丹 (Dan Yang)
S
Shanping Li
DOI:10.1007/s11432-018-9608-3delete
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摘要

摘要

En 中文
Quality model is regarded as a well-accepted approach for assessing, managing and improving software product quality. There are three categories of quality models for software products, i.e., definition model, assessment model, and prediction model. Quality assessment model (QAM) is a metric-based approach to assess the software quality. It is typically regarded as of high importance for its clear method on how to assess a system. However, the current state-of-the-art in QAM research is under limited investigation. To address this gap, the paper provides an organized and synthesized summary of the current QAMs. In detail, we conduct a systematic mapping study (SMS) for structuring the relevant articles. We obtain a total of 716 papers from the five databases, and 31 papers are selected as relevant studies at last. In summary, our work focuses on QAMs from the following aspects: software metrics, quality factors, aggregation methods, evaluation methods and tool support. According to the analysis results, our work discovers five needs that researchers in this area should continue to address: (1) new method and criteria to tailor a quality framework (i.e., structure of software metrics and quality factors) according to different specifics, (2) systematic investigations on the effectiveness, strength and weakness of different aggregation methods to guide the method selection in different context, (3) more investigations on evaluating QAMs in the context of industrial cases, (4) further investigations or real-world case studies on the QAMs related tools, and (5) building a public and diverse software benchmark which can be adopted in different application context.
Keyword:
software quality
systematic mapping study
quality assessment model
aggregation method
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期刊

Science China Information Sciences 封面图
Science China Information Sciences
IF:
7.6
论文数:
4.9K
被引数:
8.9K

机构

M
Monash University
学者数:
5.4W
论文数: 5.4W
被引数: 79
C
Chongqing University
学者数:
5.1W
论文数: 4.1W
被引数: 6.0W
Z
zhejiang university
学者数:
17.7W
论文数: 12.1W
被引数: 152
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