Details
| Original language | English |
|---|---|
| Title of host publication | 2020 IEEE 28th International Requirements Engineering Conference (RE) |
| Editors | Travis Breaux, Andrea Zisman, Samuel Fricker, Martin Glinz |
| Pages | 434-439 |
| Number of pages | 6 |
| ISBN (electronic) | 9781728174389 |
| Publication status | Published - 2020 |
Publication series
| Name | Proceedings of the IEEE International Conference on Requirements Engineering |
|---|---|
| Volume | 2020-August |
| ISSN (Print) | 1090-705X |
| ISSN (electronic) | 2332-6441 |
Abstract
Keywords
- Gaze tracking, Task analysis, Software, Tools, Stakeholders, Switches, Data visualization, software traceability, eye tracking, interaction data, trace links
ASJC Scopus subject areas
- Engineering(all)
- Computer Science(all)
- Business, Management and Accounting(all)
- Strategy and Management
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
2020 IEEE 28th International Requirements Engineering Conference (RE). ed. / Travis Breaux; Andrea Zisman; Samuel Fricker; Martin Glinz. 2020. p. 434-439 9218195 (Proceedings of the IEEE International Conference on Requirements Engineering; Vol. 2020-August).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Towards Automatic Capturing of Traceability Links by Combining Eye Tracking and Interaction Data
AU - Ahrens, M.
PY - 2020
Y1 - 2020
N2 - Despite its numerous scientifically cited benefits, traceability is still rarely established in industrial settings. Years of research in the area have brought several different approaches to create traceability links including Information Retrieval (IR) and Machine Learning approaches. However, their accuracy and overall traceability support is not sufficient yet to be properly applied in practice. In my research, I want to investigate the usage of eye tracking and interaction data in the field of traceability. By tracking how software engineers interact with documents, where they focus on and recording gaze links between those documents, an algorithm is designed to obtain trace links between artifacts from these data. Eye tracking and interaction data have the advantage that they can be recorded in an automatic, non-intrusive way without requiring manual effort. They give detailed insight about where people focus on when working on tasks. However, software support of eye tracking is still limited, especially in the context of dynamic content such as switching between, scrolling or editing documents. Therefore, one essential step of my research is to provide software support for recording eye tracking data in dynamic document environments. By combining eye tracking data with additionally recorded metadata such as interactions, this eye tracking framework shall enable the automatic capturing of gaze links and gaze durations during software engineering tasks. The approach of using eye tracking in the context of traceability will be evaluated in several usage scenarios such as requirements coverage assessment.
AB - Despite its numerous scientifically cited benefits, traceability is still rarely established in industrial settings. Years of research in the area have brought several different approaches to create traceability links including Information Retrieval (IR) and Machine Learning approaches. However, their accuracy and overall traceability support is not sufficient yet to be properly applied in practice. In my research, I want to investigate the usage of eye tracking and interaction data in the field of traceability. By tracking how software engineers interact with documents, where they focus on and recording gaze links between those documents, an algorithm is designed to obtain trace links between artifacts from these data. Eye tracking and interaction data have the advantage that they can be recorded in an automatic, non-intrusive way without requiring manual effort. They give detailed insight about where people focus on when working on tasks. However, software support of eye tracking is still limited, especially in the context of dynamic content such as switching between, scrolling or editing documents. Therefore, one essential step of my research is to provide software support for recording eye tracking data in dynamic document environments. By combining eye tracking data with additionally recorded metadata such as interactions, this eye tracking framework shall enable the automatic capturing of gaze links and gaze durations during software engineering tasks. The approach of using eye tracking in the context of traceability will be evaluated in several usage scenarios such as requirements coverage assessment.
KW - Gaze tracking
KW - Task analysis
KW - Software
KW - Tools
KW - Stakeholders
KW - Switches
KW - Data visualization
KW - software traceability
KW - eye tracking
KW - interaction data
KW - trace links
UR - http://www.scopus.com/inward/record.url?scp=85093931100&partnerID=8YFLogxK
U2 - 10.1109/re48521.2020.00064
DO - 10.1109/re48521.2020.00064
M3 - Conference contribution
SN - 978-1-7281-7439-6
T3 - Proceedings of the IEEE International Conference on Requirements Engineering
SP - 434
EP - 439
BT - 2020 IEEE 28th International Requirements Engineering Conference (RE)
A2 - Breaux, Travis
A2 - Zisman, Andrea
A2 - Fricker, Samuel
A2 - Glinz, Martin
ER -