TY - GEN

T1 - Using eye tracking data to improve requirements specification use

AU - Ahrens, Maike

AU - Schneider, Kurt

N1 - Conference code: 26

PY - 2020/3/18

Y1 - 2020/3/18

N2 - [Context and motivation] 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. [Question/problem] 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. [Principal ideas/results] We used eye tracking data obtained from observing readers when using specifications to create three different attention transfer features to support them in this process. 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. 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. [Contribution] 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 improvement suggestions and ideas on where to focus follow-up research on.

AB - [Context and motivation] 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. [Question/problem] 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. [Principal ideas/results] We used eye tracking data obtained from observing readers when using specifications to create three different attention transfer features to support them in this process. 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. 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. [Contribution] 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 improvement suggestions and ideas on where to focus follow-up research on.

KW - Attention transfer

KW - Empirical study

KW - Eye tracking

KW - Requirements document

KW - Software requirements specification

KW - Visualization

UR - http://www.scopus.com/inward/record.url?scp=85083985954&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-44429-7_3

DO - 10.1007/978-3-030-44429-7_3

M3 - Conference contribution

SN - 9783030444280

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 36

EP - 51

BT - Requirements engineering

A2 - Madhavji, Nazim

A2 - Pasquale, Liliana

PB - Springer International Publishing AG

CY - Cham

T2 - 26th International Working Conference on Requirements Engineering

Y2 - 24 March 2020 through 27 March 2020

ER -