Data-driven and tool-supported elicitation of quality requirements in agile companies

• Published in: Software quality journal Vol. 28; no. 3; pp. 931 - 963
• Main Authors: Oriol, Marc, Martínez-Fernández, Silverio, Behutiye, Woubshet, Farré, Carles, Kozik, Rafał, Seppänen, Pertti, Vollmer, Anna Maria, Rodríguez, Pilar, Franch, Xavier, Aaramaa, Sanja, Abhervé, Antonin, Choraś, Michał, Partanen, Jari
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2020; Springer Nature B.V
• Subjects: Compilers; Computer Science; Dashboards; Data Structures and Information Theory; Interpreters; Measuring instruments; Operating Systems; Perception; Programming Languages; Qualitative analysis; Software; Software development; Software Engineering/Programming and Operating Systems; Non-functional requirements; Data-driven software engineering; Agile software development; Software quality; Quality requirements; Quality attributes; Requirements engineering
• ISSN: 0963-9314; 1573-1367
• DOI: 10.1007/s11219-020-09509-y

Quality requirements (QRs) are a key artifact needed to ensure the quality and success of a software system. Despite their importance, QRs rarely get the same degree of attention as their functional counterpart in agile software development (ASD) projects. Moreover, crucial information that can be obtained from software development repositories (e.g., JIRA, GitHub) is not fully exploited, or is even neglected, in QR elicitation activities. In this work, we present a data-driven tooled approach for the semi-automatic generation and documentation of QRs in the context of ASD. The approach is based on the declaration of thresholds over quality-related issues, whose violation triggers user-defined alerts. These alerts are used to browse a catalog of QR patterns that are presented to the ASD team by means of a dashboard that implements several analysis techniques. Once selected, the patterns generate the QRs, which are documented and stored in the product backlog. The full approach is implemented via a configurable platform. Over the course of 1 year, four companies differing in size and profile followed this approach and deployed the platform in their premises to semi-automatically generate QRs in several projects. We used standardized measurement instruments to elicit the perception of 22 practitioners regarding their use of the tool. The quantitative and qualitative analyses yielded positive results; i.e., the practitioners’ perception with regard to the tool’s understandability, reliability, usefulness, and relevance was positive. We conclude that the results show potential for future adoption of data-driven elicitation of QRs in agile companies and encourage other practitioners to use the presented tool and adopt it in their companies.