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Dissertation_Naser-Al-Madi-2020.pdf (2.07 MB)

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Modeling Eye Movement for the Assessment of Programming Proficiency

Al Madi, Naser S
http://rave.ohiolink.edu/etdc/view?acc_num=kent1595429905152276

Abstract Details

2020, PHD, Kent State University, College of Arts and Sciences / Department of Computer Science.
The overwhelming majority of software development time is spent reading source code in a process known formally as Program Comprehension. Studies have found that programmers spend more than 50% of their time on activities that reflect searching for information. Program Comprehension is defined as the process of understanding how a software system or part of it work. Without understanding existing source code fixing, debugging, modifying, reusing, and maintaining software become impossible. On the economic side, software maintenance is the biggest cost in creating software systems. Among the modern observation tools for studying program comprehension comes Eye Tracking. The use of eye tracking in the study of human-oriented Software Engineering allowed researchers to gain a better understanding of the strategies and processes applied by programmers. This dissertation presents an investigation of source code reading on the token level, this includes the influence of token frequency, length, and predictability on eye movement. The focus of the investigation is on two central aspects: First, the differences in eye movement during reading source code and during reading natural language text. Second, the differences between novices and experts in the magnitude and influence of linguistic factors that affect eye movement. The results provide evidence that on the token level source code is influenced by the same factors as natural text, yet the magnitude of these effects is different from natural text. In addition, the results suggest that the magnitude of the linguistic effects on eye movement is a proxy indicator of skilled source code reading behavior. Based on these results, a model of eye-movement control is used to simulate eye movement over source code. The model predicts and explains when and where eyes move over source code accounting for cognitive processing time. Such models can be used in various areas of Software Engineering, and the use of the model is demonstrated in two applications: First, in estimating programming language reading proficiency based solely on eye movement. Second, in an automated technique for correcting erroneous eye tracking recordings over source code.
Jonathan Maletic, Dr. (Advisor)
Feodor Dragan, Dr. (Committee Member)
Gwenn Volkert, Dr. (Committee Member)
Bonita Sharif, Dr. (Committee Member)
Jocelyn Folk, Dr. (Committee Member)
Michael Carl, Dr. (Committee Member)
114 p.
Computer Science
Eye tracking; eye movement; n-gram; modeling; source code; natural text; frequency; predictability; language; novice; expert; reading; classification; fixation; correction; awesomology; token; E-Z reader; Programming; Proficiency; Assessment;

Recommended Citations

Citations

  • Al Madi, N. S. (2020). Modeling Eye Movement for the Assessment of Programming Proficiency [Doctoral dissertation, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1595429905152276

    APA Style (7th edition)

  • Al Madi, Naser. Modeling Eye Movement for the Assessment of Programming Proficiency. 2020. Kent State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1595429905152276.

    MLA Style (8th edition)

  • Al Madi, Naser. "Modeling Eye Movement for the Assessment of Programming Proficiency." Doctoral dissertation, Kent State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=kent1595429905152276

    Chicago Manual of Style (17th edition)

kent1595429905152276
417
© 2020, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.