Using data mining and recommender systems to scale up the requirements process
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 requirement...
Saved in:
| Published in | International Conference on Software Engineering 2008 Vol. 2008; no. 4 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
11.05.2008
|
| Online Access | Get full text |
| ISBN | 1605580260 9781605580265 |
| ISSN | 0270-5257 |
| DOI | 10.1145/1370700.1370702 |
Cover
| Summary: | 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. |
|---|---|
| Bibliography: | SourceType-Scholarly Journals-2 ObjectType-Feature-2 ObjectType-Conference Paper-1 content type line 23 SourceType-Conference Papers & Proceedings-1 ObjectType-Article-3 |
| ISBN: | 1605580260 9781605580265 |
| ISSN: | 0270-5257 |
| DOI: | 10.1145/1370700.1370702 |