인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.8 No.3
- 발행연도
- 2019.6
- 수록면
- 210 - 218 (9page)
- DOI
- 10.5573/IEIESPC.2019.8.3.210
이용수
초록· 키워드
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.
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목차
- Abstract
- 1. Introduction
- 2. Related Work
- 3. Experiment
- 4. Evaluation and Results
- 5. Threats to Validity
- 6. Visualization of Results
- 7. Conclusion and Future Work
- References
참고문헌
참고문헌 신청최근 본 자료
UCI(KEPA) : I410-ECN-0101-2019-569-000907014
