- 요약
- Abstract
- 1. 서론
- 2. 관련 연구
- 3. 베이지안 네트워크 기반 소프트웨어 메트릭 관리 모델
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https://www.riss.kr/link?id=A102593002
2016
Korean
569
KCI우수등재
학술저널
1334-1341(8쪽)
1
0
상세조회0
다운로드목차 (Table of Contents)
참고문헌 (Reference)
1 김태연, "교차 프로젝트 결함 예측 모형의 성능 비교" 한국정보과학회 40 (40): 774-783, 2013
2 김태연, "객체지향 메트릭 기반인 결함 예측 모형의 범용성에 관한 실험적 연구" 한국정보처리학회 16 (16): 407-416, 2009
3 N. Fenton, "Using Bayesian Networks to Predict Software Defects and Reliability" 222 (222): 701-712, 2008
4 A. B. Downey, "Think Bayes" Hanbit Media 23-24, 2014
5 J. S. Shirabad, "The PROMISE Repository of Software Engineering Databases" School of Information Technology and Engineering, University of Ottawa
6 A. Okutan, "Software defect prediction using Bayesian networks" 19 (19): 154-181, 2014
7 I. Sommerville, "Software Engineering" Pearson Education Korea, Ltd. 2008
8 Y. Chen, "Research on software defect prediction based on data mining" 1 : 563-567, 2010
9 L. Li, "Research on Machining Defect Diagnosis Method Based on Bayesian Networks" 1-4, 2009
10 M. Fowler, "Refactoring" Daechung Media 73-74, 2003
1 김태연, "교차 프로젝트 결함 예측 모형의 성능 비교" 한국정보과학회 40 (40): 774-783, 2013
2 김태연, "객체지향 메트릭 기반인 결함 예측 모형의 범용성에 관한 실험적 연구" 한국정보처리학회 16 (16): 407-416, 2009
3 N. Fenton, "Using Bayesian Networks to Predict Software Defects and Reliability" 222 (222): 701-712, 2008
4 A. B. Downey, "Think Bayes" Hanbit Media 23-24, 2014
5 J. S. Shirabad, "The PROMISE Repository of Software Engineering Databases" School of Information Technology and Engineering, University of Ottawa
6 A. Okutan, "Software defect prediction using Bayesian networks" 19 (19): 154-181, 2014
7 I. Sommerville, "Software Engineering" Pearson Education Korea, Ltd. 2008
8 Y. Chen, "Research on software defect prediction based on data mining" 1 : 563-567, 2010
9 L. Li, "Research on Machining Defect Diagnosis Method Based on Bayesian Networks" 1-4, 2009
10 M. Fowler, "Refactoring" Daechung Media 73-74, 2003
11 Jie Ba, "ProPRED: A Probabilistic Model for the Prediction of Residual Defects" 247-251, 2012
12 N. Fenton, "Predicting software defects in varying development lifecycles using Bayesian nets" 49 (49): 32-43, 2007
13 I. Arora, "Open Issues in Software Defect Prediction" 46 : 906-912, 2015
14 N. Fenton, "On the effectiveness of early life cycle defect prediction with Bayesian Nets" 13 : 499-537, 2008
15 E. Choi, "New Software Engineering" Jungik Publishing 448-449, 2014
16 V. U. B. Challagulla, "Empirical assessment of machine learning based software defect prediction techniques" 263-270, 2005
17 G. J. Pai, "Empirical Analysis of Software Fault Content and Fault Proneness Using Bayesian Methods" 33 (33): 675-686, 2007
18 A. T. Misirli, "Bayesian Networks For Evidence-Based Decision-Making in Software Engineering" 40 (40): 533-554, 2014
19 S. Shin, "Basic Principles of Probabilistic Program-ming" Acorn publishing 2015
20 R. Rana, "Analyzing defect inflow distribution and applying Bayesian inference method for software defect prediction in large software projects" 117 : 229-244, 2016
21 J. Lin, "An Integrated Procedure for Bayesian Reliability Inference Using MCMC" 2014 : 2014
22 M. D'Ambros, "An Extensive Comparison of Bug Prediction Approaches" 31-41, 2010
23 K. Jeet, "A Bayesian Network based Approach for Software Defects Prediction" 36 (36): 1-5, 2011
24 S. Wagner, "A Bayesian Network Approach to Assess and Predict Software Quality Using Activity-Based Quality Models" 2009
Local Grid-based Multipath Routing Protocol for Mobile Sink in Wireless Sensor Networks
kNN Query Processing Algorithm based on the Encrypted Index for Hiding Data Access Patterns
The Design of Object-of-Interest Extraction System Utilizing Metadata Filtering from Moving Object
Outdoor Swarm Flight System Based on RTK-GPS
학술지 이력
연월일 | 이력구분 | 이력상세 | 등재구분 |
---|---|---|---|
2021 | 평가예정 | 계속평가 신청대상 (등재유지) | |
2016-01-01 | 평가 | 우수등재학술지 선정 (계속평가) | |
2015-01-01 | 평가 | 등재학술지 유지 (등재유지) | |
2002-01-01 | 평가 | 학술지 통합 (등재유지) |
학술지 인용정보
기준연도 | WOS-KCI 통합IF(2년) | KCIF(2년) | KCIF(3년) |
---|---|---|---|
2016 | 0.19 | 0.19 | 0.19 |
KCIF(4년) | KCIF(5년) | 중심성지수(3년) | 즉시성지수 |
0.2 | 0.18 | 0.373 | 0.07 |