Abstract
In cases where usability is a mission critical system quality it is becoming essential to know whether an evaluation study has identified the majority of existing defects. Previous work has shown that procedures for estimating the progress of evaluation studies have to account for variation in defect visibility; otherwise, harmful bias will happen. Here, a statistical model is introduced for estimating the number of not-yet-identified defects in a study. This approach also supports exact confidence intervals and can easily be adapted to estimate the required number of sessions. The method is evaluated and shown to, in most cases, provide accurate measures. A running example illustrates how practitioners may track the progress of their studies and make quantitatively informed decisions on when to finish.
| Original language | English |
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| Title of host publication | People and Computers XXIII Celebrating People and Technology |
| Subtitle of host publication | Proceedings of HCI 2009, Churchill College Cambridge, UK, 1-5 September 2009 |
| Editors | Alan F. Blackwell |
| Publisher | British Computer Society |
| Pages | 188-197 |
| ISBN (Print) | 978-1-906124-87-8 |
| Publication status | Published - 1 Sept 2009 |
| Event | 23rd BCS conference on Human Computer Interaction, HCI 2009: People and Computers XXIII Celebrating People and Technology - Cambridge, United Kingdom Duration: 1 Sept 2009 → 5 Sept 2009 Conference number: 23 |
Conference
| Conference | 23rd BCS conference on Human Computer Interaction, HCI 2009 |
|---|---|
| Abbreviated title | HCI |
| Country/Territory | United Kingdom |
| City | Cambridge |
| Period | 1/09/09 → 5/09/09 |
Keywords
- Maximum Likelihood
- IR-103799
- Count Data Models
- METIS-260211
- Usability Evaluation
- Process Control
- Reliability
- Usability Business