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Publication type: Conference paper
Type of review: Not specified
Title: Requirements-collector : automating requirements specification from elicitation sessions and user feedback
Authors: Panichella, Sebastiano
Ruiz, Marcela
et. al: No
DOI: 10.1109/RE48521.2020.00057
Proceedings: 2020 IEEE 28th International Requirements Engineering Conference (RE)
Pages: 404
Pages to: 407
Conference details: 28th IEEE International Requirements Engineering Conference (RE 2020), Zurich, Switzerland, 31 August - 4 September 2020
Issue Date: 2020
Publisher / Ed. Institution: IEEE
ISBN: 978-1-7281-7438-9
ISSN: 2332-6441
Language: English
Subject (DDC): 006: Special computer methods
Abstract: In the context of digital transformation, speeding up the time-to-market of high-quality software products is a big challenge. Software quality correlates with the success of requirements engineering (RE) sessions and the ability to collect feedback from end-users in an efficient, dynamic way. Thus, software analysts are tasked to collect all relevant material of RE sessions and user feedback, usually specified on written notes, flip charts, pictures, and user reviews. Afterward comprehensible requirements need to be specified for software implementation and testing. These activities are mostly performed manually, which causes process delays, with a negative effect on software quality attributes such as reliability, usability, comprehensibility. This paper presents Requirements-Collector, a tool for automating the tasks of requirements specification and user feedback analysis. Our tool involves machine learning (ML) and deep learning (DL) computational mechanisms enabling the automated classification of requirements discussed in RE meetings (stored in the form of audio recordings) and textual feedback in the form of user reviews. We use such techniques as they demonstrated to be quite effective in text classification problems. We argue that Requirements-Collector has the potential to renovate the role of software analysts, which can experience a substantial reduction of manual tasks, more efficient communication, dedication to more analytical tasks, and assurance of software quality from conception phases. The results of this work have shown that our tool is able to classify RE specifications and user review feedback with reliable accuracy.
Further description: ​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Fulltext version: Accepted version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in collections:Publikationen School of Engineering

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