Presentation
Time:
M.S. Thesis Defense: Jigyasa Chauhan
Date:
12:00 pm –
1:00 pm
Avery Hall
Room: 347
1144 T St
Lincoln NE 68508
Lincoln NE 68508
Additional Info: AVH
M.S. Thesis Defense: Jigyasa Chauhan
Monday, November 28, 2022
12:00 PM (Noon)
347 Avery Hall
“AN EMPIRICAL STUDY ON THE CLASSIFICATION OF PYTHON LANGUAGE FEATURES USING EYE-TRACKING”
Eye tracking has been an evolutionary technology in the field of software engineering. We aim to utilize this technology to understand the behavior of programmers comprehending python code. Python has been constantly evolving with time. The addition of various features and functionalities has made python flexible, more-readable and easier to adapt for multi-disciplinary software programmers. But despite of new advancements to the language, we are trying to understand whether it is being used in an efficient way. Depending on how python has been utilised in the industry, it would be helpful to understand how programmers use and classify python code. The language features help us classify how programmers are using the code. Do they understand the different paradigms of python? What is their approach to debug a certain paradigm? This paper presents the first study on how programmers analyse python code using it’s features based on an eye-tracking study. To conduct this study we collected our data samples from 30 python programmers. [Results yet to be mentioned]
Committee:
Dr. Robert Dyer, Advisor
Dr. Bonita Sharif
Dr. Rahul Purandar
Monday, November 28, 2022
12:00 PM (Noon)
347 Avery Hall
“AN EMPIRICAL STUDY ON THE CLASSIFICATION OF PYTHON LANGUAGE FEATURES USING EYE-TRACKING”
Eye tracking has been an evolutionary technology in the field of software engineering. We aim to utilize this technology to understand the behavior of programmers comprehending python code. Python has been constantly evolving with time. The addition of various features and functionalities has made python flexible, more-readable and easier to adapt for multi-disciplinary software programmers. But despite of new advancements to the language, we are trying to understand whether it is being used in an efficient way. Depending on how python has been utilised in the industry, it would be helpful to understand how programmers use and classify python code. The language features help us classify how programmers are using the code. Do they understand the different paradigms of python? What is their approach to debug a certain paradigm? This paper presents the first study on how programmers analyse python code using it’s features based on an eye-tracking study. To conduct this study we collected our data samples from 30 python programmers. [Results yet to be mentioned]
Committee:
Dr. Robert Dyer, Advisor
Dr. Bonita Sharif
Dr. Rahul Purandar