Advances in software inspections
IEEE Transactions on Software Engineering
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Multiple comparison procedures
Multiple comparison procedures
A Two-Person Inspection Method to Improve Programming Productivity
IEEE Transactions on Software Engineering
Prediction and control of ADA software defects
Journal of Systems and Software - An Oregon workshop on software metrics
The Detection of Fault-Prone Programs
IEEE Transactions on Software Engineering
The craft of software testing: subsystem testing including object-based and object-oriented testing
The craft of software testing: subsystem testing including object-based and object-oriented testing
Improvement of software process by process description and benefit estimation
Proceedings of the 17th international conference on Software engineering
Handbook of software reliability engineering
Handbook of software reliability engineering
Software cost and quality analysis by statistical approaches
Proceedings of the 20th international conference on Software engineering
Practical Guide to Software Quality Management
Practical Guide to Software Quality Management
Testing Very Big Systems
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Testing Enbredded Software
Capability Maturity Model, Version 1.1
IEEE Software
Tree-Based Software Quality Estimation Models For Fault Prediction
METRICS '02 Proceedings of the 8th International Symposium on Software Metrics
Software reliability models: an approach to early reliability prediction
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Residual fault density prediction using regression methods
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Software Metrics Model For Integrating Quality Control And Prediction
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
On Estimating Testing Effort Needed to Assure Field Quality in Software Development
ISSRE '02 Proceedings of the 13th International Symposium on Software Reliability Engineering
Using Machine Learning for Estimating the Defect Content After an Inspection
IEEE Transactions on Software Engineering
Software defect prediction based on source code metrics time series
Transactions on rough sets XIII
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In typical software development, a software reliability growth model (SRGM) is applied in each testing activity to determine the time to finish the testing. However, there are some cases in which the SRGM does not work correctly. That is, the SRGM sometimes mistakes quality for poor quality products. In order to tackle this problem, we focussed on the trend of time series data of software defects among successive testing phases and tried to estimate software quality using the trend. First, we investigate the characteristics of the time series data on the detected faults by observing the change of the number of detected faults. Using the rank correlation coefficient, the data are classified into four kinds of trends. Next, with the intention of estimating software quality, we investigate the relationship between the trends of the time series data and software quality. Here, software quality is defined by the number of faults detected during six months after shipment. Finally, we find a relationship between the trends and metrics data collected in the software design phase. Using logistic regression, we statistically show that two review metrics in the design and coding phase can determine the trend.