Predicting User Actions in Software Processes

TL;DR

This paper presents a machine learning-based approach to predict user actions in software processes, aiding software architects by forecasting their next steps through sequence learning techniques.

Contribution

It adapts sequence learning methods for predicting user actions within software processes, a novel application in software engineering.

Findings

Effective prediction of user actions demonstrated

Improved assistance for software architects shown

Potential for enhancing software process automation

Abstract

This paper describes an approach for user (e.g. SW architect) assisting in software processes. The approach observes the user's action and tries to predict his next step. For this we use approaches in the area of machine learning (sequence learning) and adopt these for the use in software processes. Keywords: Software engineering, Software process description languages, Software processes, Machine learning, Sequence prediction