An approach to software development effort estimation using machine learning

We introduce a machine learning approach for real life software development effort estimation. Our method uses state of the art developments such as distributed word embeddings in order to create a system that can estimate effort given only basic project management metrics and, most importantly, textual descriptions of tasks. We use an artificial neural network for automating the effort estimation task. We evaluate our method on genuine software project data from a software company, obtaining results that surpass some of the related literature and a system that promises much easier integration into any software management tool that stores textual descriptions of tasks.