Software Defect Prediction: Lessons from the South Asian Context
Kamrul Li
Corresponding
Ahsanullah University of Science and Technology
Imran Patel
Military Institute of Science and Technology
Abstract
Bangladesh, with its dense population and vulnerable infrastructure, faces particular difficulties with software defect prediction in cement production. Both steady-state and transient operating conditions in cement production were analysed in detail using convolutional neural network. A payback period of roughly 6 years was estimated for the proposed installation. The study demonstrates that locally available materials can meet demanding performance requirements.
Keywords:
software defect predictionconvolutional neural networkphotovoltaic systemwireless sensor networkcryptography
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