Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 106483 |
Fachzeitschrift | Information and Software Technology |
Jahrgang | 131 |
Frühes Online-Datum | 12 Nov. 2020 |
Publikationsstatus | Veröffentlicht - März 2021 |
Abstract
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Software
- Informatik (insg.)
- Information systems
- Informatik (insg.)
- Angewandte Informatik
Zitieren
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- Harvard
- Apa
- Vancouver
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- RIS
in: Information and Software Technology, Jahrgang 131, 106483, 03.2021.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Improving Requirements Specification Use by Transferring Attention with Eye Tracking Data
AU - Ahrens, Maike
AU - Schneider, Kurt
PY - 2021/3
Y1 - 2021/3
N2 - [Context] Software requirements specifications are the main point of reference in traditional software projects. Especially in large projects, these documents get read by multiple people, multiple times. Several guidelines and templates already exist to support writing a good specification. However, not much research has been done in investigating how to support the use of specifications and help readers to find relevant information and navigate in the document more efficiently. [Objective] We aim to ease the reading process of requirements specifications by making use of previously recorded attention data. Therefore, we created three different attention transfer features based on eye tracking data obtained from observing readers when using specifications. [Method] In a student experiment, we evaluated if these attention visualizations positively affect the roles software architect, UI-designer and tester when reading a specification for the first time. [Results] The results show that the attention visualizations did not decrease navigation effort, but helped to draw the readers’ attention towards highlighted parts and decreased the average time spent on pages. They were mostly perceived as valuable by the readers. [Conclusions] We explored and evaluated the approach of visualizing other readers’ attention focus to help support new readers. Our results include interesting findings on what works well, what does not and what could be enhanced. We present several suggestions on how attention data could be used to fasten document navigation, direct reading and facilitate user-specific reading.
AB - [Context] Software requirements specifications are the main point of reference in traditional software projects. Especially in large projects, these documents get read by multiple people, multiple times. Several guidelines and templates already exist to support writing a good specification. However, not much research has been done in investigating how to support the use of specifications and help readers to find relevant information and navigate in the document more efficiently. [Objective] We aim to ease the reading process of requirements specifications by making use of previously recorded attention data. Therefore, we created three different attention transfer features based on eye tracking data obtained from observing readers when using specifications. [Method] In a student experiment, we evaluated if these attention visualizations positively affect the roles software architect, UI-designer and tester when reading a specification for the first time. [Results] The results show that the attention visualizations did not decrease navigation effort, but helped to draw the readers’ attention towards highlighted parts and decreased the average time spent on pages. They were mostly perceived as valuable by the readers. [Conclusions] We explored and evaluated the approach of visualizing other readers’ attention focus to help support new readers. Our results include interesting findings on what works well, what does not and what could be enhanced. We present several suggestions on how attention data could be used to fasten document navigation, direct reading and facilitate user-specific reading.
KW - Attention transfer
KW - Software requirements specification
KW - Requirements document
KW - Eye tracking
KW - Visualization
KW - Empirical study
UR - http://www.scopus.com/inward/record.url?scp=85097576099&partnerID=8YFLogxK
U2 - 10.1016/j.infsof.2020.106483
DO - 10.1016/j.infsof.2020.106483
M3 - Article
VL - 131
JO - Information and Software Technology
JF - Information and Software Technology
SN - 0950-5849
M1 - 106483
ER -