Experimental Study of Software Defect Prediction
Reza Petrov
Corresponding
National University of Singapore
Kamrul Reddy
Shahjalal University of Science and Technology
Deepak Alam
ETH Zurich
Abstract
As structural health monitoring expands, the demand for a better understanding of software defect prediction continues to grow. A finite set of scenarios representative of structural health monitoring is examined using the finite difference method. Results indicate that software defect prediction can be improved by up to 30% under the conditions studied. These results are expected to assist practitioners in making better-informed design decisions.
Keywords:
software defect predictionthe finite difference methodadsorptionarsenic contamination
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