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Using data mining and recommender systems to scale up the requirements process

Published:10 May 2008Publication History

ABSTRACT

Ultra-Large-Scale (ULS) software projects are anticipated to be highly complex and to involve thousands, or even hundreds of thousands of stakeholders. Unfortunately numerous accounts of recent failures and challenges in industrial and governmental projects have demonstrated that current requirements elicitation and prioritization practices do not scale adequately to address the needs of large projects. This position paper directly addresses this problem through proposing an open, inclusive, and robust elicitation and prioritization process that utilizes data-mining and recommender technologies to facilitate the active involvement of many thousands of stakeholders. We believe that the approach described in this paper is a fundamental building block towards addressing higher level requirements problems facing ULS Systems.

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            • Published in

              cover image ACM Conferences
              ULSSIS '08: Proceedings of the 2nd international workshop on Ultra-large-scale software-intensive systems
              May 2008
              80 pages
              ISBN:9781605580265
              DOI:10.1145/1370700
              • General Chairs:
              • Kevin Sullivan,
              • Rick Kazman

              Copyright © 2008 ACM

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              Publication History

              • Published: 10 May 2008

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              ULSSIS '08 Paper Acceptance Rate19of19submissions,100%Overall Acceptance Rate19of19submissions,100%

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