Artificial Neural Network-based Approaches For Predicting Software Development

Abstract

To Get Reliable Software On Time And Under Budget, You Need To Be Able To Accurately Forecast How Much Work Will Go Into Developing It. There Have Been A Number Of Software Effort Estimating Models Made In The Last Few Years, But It's Still Hard To Get Reliable Estimates For Software Projects. Software Failures Are Primarily Attributed To Inaccurate Effort Estimation During Initial Phases. So, A Lot Of Researchers Are Utilizing AI To Make New Models And Make The Ones That Already Exist Better. Dynamic Circumstances In Software Development Technology Complicate The Predictability Of Work Estimation. This Article Talks About The Most Popular Ways To Estimate How Much Work Software Will Take. ANN (Artificial Neural Network) Can Simulate A Complicated Set Of Relationships Between The Dependent Variable (effort) And The Independent Factors (cost Drivers), Which Makes It A Promising Tool For Estimate. This Study Provides A Review Grounded In The Performance Analysis Of Artificial Neural Networks (ANN) And Juxtaposes The Outcomes Of Linear Regression Models In Effort Estimation.

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