•   When: Monday, February 21, 2022 from 02:00 PM to 03:00 PM
•   Speakers: Souti Chattopadhyay
•   Location: ZOOM only
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Abstract:

86 billion neurons make up our brains! Naturally, these 100 trillion neural connections give rise to a complex process of making decisions, interpreting information, and taking intended actions. This is especially true when programming, whether to build software systems or analyze data. Cognitive processes like selective interpretation and biases affect these programming decisions and actions frequently and significantly. In a recent study, we found that biases are associated with 45.7% of actions that developers take (like editing a line or navigating to a part of code). Eventually, developers reversed or undid 70% of the actions associated with biases which made up 25% of their entire worktime [1]. Similarly, data scientists report spending a lot of time in a “tortuous, multi-step adventure” for getting the data set up for analysis based on familiarity and preferences [2]. Programmers pay the necessary price of being human when working with tools without support for the negative impacts of cognitive processes. In this talk, I will present findings on how some cognitive processes affect programming. To reduce the friction between software and cognition, we will discuss designing tools to be vigilant and provide desired support using automated and empirical approaches.

 Bio:

Souti Chattopadhyay (Rini) is a Ph.D. candidate at Oregon State University in the Department of EECS. She works at the intersection of Human-Computer Interaction, Software Engineering, and Cognitive Science, focusing on assisting software engineers and data scientists.

 Her research is on human-centered tools and interfaces that align with the human cognitive processes when solving problems. Her work is focused on understanding how humans make decisions when interacting with interfaces, specifically programming interfaces. She studies developers, data scientists, and end-user programmers to identify the process behind their technical decisions and social interactions.

 During her internship at Microsoft Research, she worked on a project related to the next generation of developers, specifically how they express their identity on social media platforms like YouTube. Some of her works were awarded best papers and honorable mentions by ACM and IEEE, including understanding cognitive biases in programmers and exploring a plethora of challenges data scientists face. Her work on cognitive biases was also recognized as research highlights by CACM and that on data scientists was featured on Nature articles.

 References:

[1] Souti Chattopadhyay, Nicholas Nelson, Audrey Au, Natalia Morales, Christopher Sanchez, Rahul Pandita, and Anita Sarma. 2020. A tale from the trenches: cognitive biases and software development. In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering (ICSE '20). Association for Computing Machinery, New York, NY, USA, 654–665. DOI:https://doi.org/10.1145/3377811.3380330

[2] Souti Chattopadhyay, Ishita Prasad, Austin Z. Henley, Anita Sarma, and Titus Barik. 2020. What's Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 1–12. DOI:https://doi.org/10.1145/3313831.3376729