Can a model estimate software effort from public data? A pre-registered blind test on nine open datasets — reproducible, and honest about the negative result.

This repository contains the code used for the paper: Liyan Song, Leandro Minku, and Xin Yao. "Software Effort Interval Prediction via Bayesian Inference and Synthetic Bootstrap Resampling", ACM Transactions on Software Engineering Methodology, 28(1):1–46, Februray 2019

Agile Software Effort Estimation System

Replication study of cognitive bias experiments in software effort estimation using five frontier LLMs as synthetic participants.

A hybrid model that combines fuzzy logic and a modified multi-layer perceptron (MLP) neural network to predict the effort required to complete software projects with different attributes (project size, team size, team experience, team growth, lines of code generated, project topic).