학술논문

Metrics based classification trees for software test monitoring and management
Document Type
Conference
Author
Source
Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94 Tools with artificial intelligence Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on. :534-540 1994
Subject
Computing and Processing
Classification tree analysis
Software testing
Monitoring
Software measurement
Programming
Software metrics
Application software
Risk management
Job shop scheduling
Processor scheduling
Language
Abstract
An important objective of software test programs is to identity, "high-risk" components. This paper focuses on one method which can be applied to identify high-risk software components, the use of a classification tree with an established software metrics set. The selected examples of high-risk software components are those modules which are most likely to induce errors in the target operational system, and those software components which will require the most effort in the development process. The associated metrics are software reliability and productivity. This paper describes the methodology utilized by the US Army in the application of classification trees for analysis of software metrics data. A detailed example is provided with a step-by-step procedure for construction of a classification tree for software metrics analysis.ETX