A Two-Person Inspection Method to Improve Programming Productivity
IEEE Transactions on Software Engineering
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Estimating software fault content before coding
ICSE '92 Proceedings of the 14th international conference on Software engineering
Assessing Software Designs Using Capture-Recapture Methods
IEEE Transactions on Software Engineering - Special issue on software reliability
An Experiment to Assess the Cost-Benefits of Code Inspections in Large Scale Software Development
IEEE Transactions on Software Engineering
A promising approach to two-person software review in educational environment
Journal of Systems and Software
A criticsm on the capture-and-recapture method for software reliability assurance
Journal of Systems and Software
Using simulation to build inspection efficiency benchmarks for development projects
Proceedings of the 20th international conference on Software engineering
Defect content estimations from review data
Proceedings of the 20th international conference on Software engineering
An encompassing life cycle centric survey of software inspection
Journal of Systems and Software
A Comprehensive Evaluation of Capture-Recapture Models for Estimating Software Defect Content
IEEE Transactions on Software Engineering
An experimental comparison of reading techniques for defect detection in UML design documents
Journal of Systems and Software
The application of subjective estimates of effectiveness to controlling software inspections
Journal of Systems and Software - Special issue on software maintenance
IEEE Transactions on Software Engineering
Empirical Software Engineering
Comparing Detection Methods for Software Requirements Inspections: A Replicated Experiment
IEEE Transactions on Software Engineering
Software quality &equil; test accuracy × test coverage
ICSE '82 Proceedings of the 6th international conference on Software engineering
Quantitative Evaluation of Capture-Recapture Models to Control Software Inspections
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
A Comparison and Integration of Capture-Recapture Models and the Detection Profile Method
ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
Estimating the Number of Undetected Errors: Bayesian Model Selection
ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
Towards an inspection technique for use case models
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Use of software inspection inputs in practice
Proceedings of the 24th International Conference on Software Engineering
Applying sampling to improve software inspections
Journal of Systems and Software - Special issue: Applications of statistics in software engineering
Software Defect Association Mining and Defect Correction Effort Prediction
IEEE Transactions on Software Engineering
The effect of the number of inspectors on the defect estimates produced by capture-recapture models
Proceedings of the 30th international conference on Software engineering
Evaluation of capture-recapture models for estimating the abundance of naturally-occurring defects
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Integrating in-process software defect prediction with association mining to discover defect pattern
Information and Software Technology
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Capture-recapture (CR) models have been proposed as an objective method for controlling software inspections. CR models were originally developed to estimate the size of animal populations. In software, they have been used to estimate the number of defects in an inspected artifact. This estimate can be another source of information for deciding whether the artifact requires a reinspection to ensure that a minimal inspection effectiveness level has been attained. Little evaluative research has been performed thus far on the utility of CR models for inspections with two inspectors. In this paper, we report on an extensive Monte Carlo simulation that evaluated capture-recapture models suitable for two inspectors assuming a code inspections context. We evaluate the relative error of the CR estimates as well as the accuracy of the reinspection decision made using the CR model. Our results indicate that the most appropriate capture-recapture model for two inspectors is an estimator that allows for inspectors with different capabilities. This model always produces an estimate (i.e., does not fail), has a predictable behavior (i.e., works well when its assumptions are met), will have a relatively high decision accuracy, and will perform better than the default decision of no reinspections. Furthermore, we identify the conditions under which this estimator will perform best.