TY - JOUR
T1 - Metrics to predict future modifications and defects based on software requirements specifications
AU - Tsunoda, Taketo
AU - Washizaki, Hironori
AU - Fukazawa, Yosiaki
AU - Inoue, Sakae
AU - Hanai, Yoshiiku
AU - Kanazawa, Masanobu
N1 - Publisher Copyright:
© 2019 Institute of Electronics and Information Engineers. All rights reserved.
PY - 2019
Y1 - 2019
N2 - In software development, the quality of the upstream process greatly affects the quality of the downstream process. However, few studies have applied metrics to estimate quality, controlled the quality quantitatively, or have verified the relationship between specifications and software quality. One reason is that specifications are described in natural language, making it difficult to quantitatively evaluate software metrics, such as complexity. Although high-quality software requirements specifications (SRSs) lead to successful implementation, neither a simple quantitative evaluation nor an effective indicator to predict modification-prone SRSs exists. Herein, the effectiveness of two specification metrics is evaluated (the number of pages and the number of previous modifications) in order to predict software defects and future modifications of SRSs. We confirm that both specification quality measured by specification metrics and software quality measured by the number of defects are related. We also reveal that future modifications are correlated with the size of SRSs.
AB - In software development, the quality of the upstream process greatly affects the quality of the downstream process. However, few studies have applied metrics to estimate quality, controlled the quality quantitatively, or have verified the relationship between specifications and software quality. One reason is that specifications are described in natural language, making it difficult to quantitatively evaluate software metrics, such as complexity. Although high-quality software requirements specifications (SRSs) lead to successful implementation, neither a simple quantitative evaluation nor an effective indicator to predict modification-prone SRSs exists. Herein, the effectiveness of two specification metrics is evaluated (the number of pages and the number of previous modifications) in order to predict software defects and future modifications of SRSs. We confirm that both specification quality measured by specification metrics and software quality measured by the number of defects are related. We also reveal that future modifications are correlated with the size of SRSs.
KW - Empirical study
KW - Metrics
KW - Quality
KW - Software requirements specifications (SRSs)
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U2 - 10.5573/IEIESPC.2019.8.3.210
DO - 10.5573/IEIESPC.2019.8.3.210
M3 - Article
AN - SCOPUS:85068556066
SN - 2287-5255
VL - 8
SP - 210
EP - 218
JO - IEIE Transactions on Smart Processing and Computing
JF - IEIE Transactions on Smart Processing and Computing
IS - 3
ER -