Managing user acceptance testing of business applications

Abstract

User acceptance testing (UAT) events gather input from actual system users to determine where potential problems may exist in a new software system or major upgrade. Modern business systems are more complex and decentralized than ever before making UAT more complicated to perform. The collaborative nature of facilitated UAT events requires close interaction between the testers and the facilitation team, even when located in various locations worldwide. This study explores the best approaches for facilitating UAT remotely and globally in order to effectively facilitate geographically-dispersed actual system users in performing UAT exercises. While research suggests user involvement is important, there is a lack of understanding about the specifics of how to best engage users for maximizing the results, and our study addresses this gap. This study examines the following research questions: How should UAT facilitators (1) schedule user participation with a minimum impact to their regular work duties and maximum ability to be present when testing and not be distracted; (2) enable direct interactions with users including face-to-face conversations during the UAT event and access to user computer screens for configuration and validation; and (3) utilize quality management software that can be used seamlessly by all involved in UAT. To examine these questions, we utilize Social Presence Theory (SPT) to establish a conceptual lens for addressing these research questions. SPT supports that the communication environment must enable people to adopt the appropriate level of social presence required for that task. This study proposes a theoretically-derived examination based on SPT of facilitated UAT delineating when and how facilitators should involve actual system users in the UAT activities either through local facilitation or remote hosting of UAT exercises, among other options. © 2014 Springer International Publishing.

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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