Estimating Residual Faults from Code Coverage
SAFECOMP '02 Proceedings of the 21st International Conference on Computer Safety, Reliability and Security
SREPT: Software Reliability Estimation and Prediction Tool
TOOLS '98 Proceedings of the 10th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
SREPT: Software Reliability Estimation and Prediction Tool
TOOLS '00 Proceedings of the 11th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
A conservative theory for long term reliability growth prediction
ISSRE '96 Proceedings of the The Seventh International Symposium on Software Reliability Engineering
Architecture-Based Software Reliability Analysis: Overview and Limitations
IEEE Transactions on Dependable and Secure Computing
Regression via Classification applied on software defect estimation
Expert Systems with Applications: An International Journal
On the effectiveness of early life cycle defect prediction with Bayesian Nets
Empirical Software Engineering
Theory of relative defect proneness
Empirical Software Engineering
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
Testing the theory of relative defect proneness for closed-source software
Empirical Software Engineering
Expert Systems with Applications: An International Journal
Assessing programming language impact on development and maintenance: a study on c and c++
Proceedings of the 33rd International Conference on Software Engineering
Taxonomy of quality metrics for assessing assurance of security correctness
Software Quality Control
Operating system reliability from the quality of experience viewpoint: an exploratory study
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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In this note, the number of faults or "bugs" per line of code is estimated based upon Halstead's software science relationships. This number is shown to be an increasing function of the number of lines of code in a program, a result in agreement with intuition and some current theories of complexity. The form of this function is investigated and an easy-to-use approximation is developed. An application to a moderately large software project is shown in which the predicted number of faults for program modules of various sizes agrees fairly well with the actual numbers of faults discovered.