Let's hear it from RETTA: A Requirements Elicitation Tool for TrAffic management systems

TL;DR

This paper introduces RETTA, an interactive tool that uses machine learning and crowd wisdom to facilitate requirements elicitation for traffic management systems, addressing domain complexity and stakeholder diversity.

Contribution

The paper presents the RETTA tool, integrating NLP and Naive Bayes to improve requirements elicitation in traffic management, bridging software engineering and transportation engineering.

Findings

RETTA effectively supports requirements classification in TM.

The tool leverages crowd input and machine learning for better elicitation.

RETTA is designed for Android devices, enhancing usability.

Abstract

The area of Traffic Management (TM) is characterized by uncertainty, complexity, and imprecision. The complexity of software systems in the TM domain which contributes to a more challenging Requirements Engineering (RE) job mainly stems from the diversity of stakeholders and complexity of requirements elicitation in this domain. This work brings an interactive solution for exploring functional and non-functional requirements of software-reliant systems in the area of traffic management. We prototyped the RETTA tool which leverages the wisdom of the crowd and combines it with machine learning approaches such as Natural Language Processing and Naive Bayes to help with the requirements elicitation and classification task in the TM domain. This bridges the gap among stakeholders from both areas of software development and transportation engineering. The RETTA prototype is mainly designed for requirements engineers and software developers in the area of TM and can be used on Android-based devices.