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Title
Assessing the Comprehension of UML Class Diagrams via Eye Tracking
Author
Yusuf Patel Dawoodi, Shehnaaz
Degree
MS, Kent State University, College of Arts and Sciences / Department of Computer Science, 2007.
Advisor
Jonathan I. Maletic
Pages
61p.
Abstract
In this thesis, eye-tracking equipment is used to assess how well a subject comprehends UML class diagrams. The goal of the study is to identify specific characteristics of UML class diagram, such as layout, color, and stereotype usage that are most effective for supporting a given task. Prior investigations in the software visualization and program comprehension communities have primarily focused on effective layout schemes and key aesthetics criteria with the goal of enhancing the cognitive process. A number of usability studies have been reported that evaluate UML class diagrams, including those with additional semantic information (e.g., class stereotypes), for an effective representation in addressing various software evolution tasks. These studies typically form conjectures and/or draw conclusions from the data explicitly collected from subjects’ via a combination of questionnaires, experience reports, and feedback comments after a designated task is completed. This raises a potential threat to the validity of the study namely: How well the subjects’ responses on completion of a task match the “reality” they observed while performing that task? That is, a subject may forget to report (or misreport) an observation after a lengthy task for example. Here we take a different approach to assess UML class diagrams. Results indicate subjects have a variation in the eye movements (i.e., how the subjects navigate the diagram) depending on their UML expertise and software-design ability to solve the given task. Layouts with additional semantic information about the design were found to be most effective and the use of class stereotypes seems to play a substantial role in comprehension of these diagrams.
Subject Headings
Computer Science
Keywords
UML; Class Diagrams; Eye Tracking; Program Comprehension

Document number: kent1194997886. Bookmark this page as
<http://rave.ohiolink.edu/etdc/view?acc_num=kent1194997886>.