The Detection of Fault-Prone Programs
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering - Special issue on software reliability
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
Models and Measurements for Quality Assessment of Software
ACM Computing Surveys (CSUR)
Predicting Fault-Prone Software Modules in Embedded Systems with Classification Trees
HASE '99 The 4th IEEE International Symposium on High-Assurance Systems Engineering
Predicting Fault-Proneness using OO Metrics: An Industrial Case Study
CSMR '02 Proceedings of the 6th European Conference on Software Maintenance and Reengineering
Software Quality Prediction Using Mixture Models with EM Algorithm
APAQS '00 Proceedings of the The First Asia-Pacific Conference on Quality Software (APAQS'00)
An Application of Fuzzy Clustering to Software Quality Prediction
ASSET '00 Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology (ASSET'00)
Some experimental estimators for developmental and delivered errors in software development projects
Proceedings of the 1981 ACM workshop/symposium on Measurement and evaluation of software quality
An Empirical Study on Object-Oriented Metrics
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Extract Rules from Software Quality Prediction Model Based on Neural Network
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Predictors of customer perceived software quality
Proceedings of the 27th international conference on Software engineering
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
An investigation of the effect of module size on defect prediction using static measures
PROMISE '05 Proceedings of the 2005 workshop on Predictor models in software engineering
A Novel Method for Early Software Quality Prediction Based on Support Vector Machine
ISSRE '05 Proceedings of the 16th IEEE International Symposium on Software Reliability Engineering
Proceedings of the 28th international conference on Software engineering
Mining metrics to predict component failures
Proceedings of the 28th international conference on Software engineering
Estimation of project success using Bayesian classifier
Proceedings of the 28th international conference on Software engineering
Global Sensitivity Analysis of Predictor Models in Software Engineering
PROMISE '07 Proceedings of the Third International Workshop on Predictor Models in Software Engineering
An Integrated Approach to Quality Modelling
WoSQ '07 Proceedings of the 5th International Workshop on Software Quality
An Experimental Study of Software Metrics for Real-Time Software
IEEE Transactions on Software Engineering
Quantitative Estimates of Debugging Requirements
IEEE Transactions on Software Engineering
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Various models and techniques have been proposed and applied in literature for software quality prediction. Specificity of each suggested model is one of the impediments in development of a generic model. A few models have been quality factor specific whereas others are software development paradigm specific. The models can even be company specific or domain specific. The amount of work done for software quality prediction compels the researchers to get benefit from the existing models and develop a relatively generic model. Development of a generic model will facilitate the quality managers by letting them focus on how to improve the quality instead of employing time on deciding which technique best suites their scenario. This paper suggests a generic model which takes software as input and predicts a quality factor value using existing models. This approach captures the specificity of existing models in various dimensions (like quality factor, software development paradigm, and software development life cycle phase etc.), and calculates quality factor value based on the model with higher accuracy. Application of the model has been discussed with the help of an example.