首页 | 本学科首页   官方微博 | 高级检索  
     


Application of fuzzy expert systems in assessing operational risk of software
Affiliation:1. Computer Engineering Department, Ankara University, Gölbaşı 50.yıl Yerleşkesi Bahçelievler Mh., 06830 Ankara, Turkey;2. Informatics Institute, Middle East Technical University, İnönü Bulvarı, 06531 Ankara, Turkey;1. VA Advanced Fellow for the Cpl. Michael Crescenz, VA Medical Center in Philadelphia, PA, United States;2. Department of Public Health, Philadelphia, PA, United States;3. Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, United States;4. Department of Pediatrics and Duke-Margolis Center for Health Policy, Duke University, Durham, NC, United States;5. Division of General Internal Medicine, University of Pennsylvania''s Perelman School of Medicine, Philadelphia, PA, United States;6. Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, United States
Abstract:Risk is the potential for realization of undesirable consequences of an event. Operational risk of software is the likelihood of untoward events occurring during operations due to software failures. NASA IV&V Facility is an independent institution which conducts Independent Assessments for various NASA projects. Its responsibilities, among others, include the assessments of operational risks of software. In this study, we investigate Independent Assessments that are conducted very early in the software development life cycle.Existing risk assessment methods are largely based on checklists and analysis of a risk matrix, in which risk factors are scored according to their influence on the potential operational risk. These scores are then arithmetically aggregated into an overall risk score. However, only incomplete project information is available during the very early phases of the software life cycle, and thus, a quantitative method, such as a risk matrix, must make arbitrary assumptions to assess operational risk.We have developed a fuzzy expert system, called the Research Prototype Early Assessment System, to support Independent Assessments of projects during the very early phases of the software life cycle. Fuzzy logic provides a convenient way to represent linguistic variables, subjective probability, and ordinal categories. To represent risk, subjective probability is a better way than quantitative objective probability of failure. Furthermore, fuzzy severity categories are more credible than numeric scores. We illustrated how fuzzy expert systems can infer useful results by using the limited facts about a current project, and rules about software development. This approach can be extended to add planned IV&V level, history of past NASA projects, and rules from NASA experts.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号