Software Engineering Research in the Neuroage Prof. Dr. Sven Apel Seminar/Proseminar — Summer Semester 2022



Further information regarding the first meeting (tomorrow)


Thank you for voting for presence/online and for your favourite topics.
We took it into account.

The topic assignment will be done tomorrow in the kick-off meeting.
The kick-off meeting will take place in presence (SR 206, E1 1) and online via MS Teams... Read more


Thank you for voting for presence/online and for your favourite topics.
We took it into account.

The topic assignment will be done tomorrow in the kick-off meeting.
The kick-off meeting will take place in presence (SR 206, E1 1) and online via MS Teams [1] at the same time.
For those who voted to joining in presence: we recommend to wear a face mask.

See you tomorrow!

[1] Visible on your personal status page on the CMS


Software Engineering Research in the Neuroage

The pivotal role of software in our modern world imposes strong requirements on quality, correctness, and reliability of software systems. The ability to understand program code plays a key role for programmers to fulfill these requirements. Despite significant progress, research on program comprehension has had a fundamental limitation: program comprehension is a cognitive process that cannot be directly observed, which leaves considerable room for (mis)interpretation, uncertainty, and confounding factors. Thus, central questions such as “What makes a good programmer?” and “How should we program?” are surprisingly difficult to answer based on the state of the art.
Recently, researchers began to lift research on program comprehension to a new level. The key idea is to leverage recent methods from cognitive neuroscience to obtain insights into the cognitive processes involved in program comprehension. Opening the “black box” of human cognition will lead to a breakthrough in understanding the why and how of program comprehension and to a completely new perspective and methodology of measuring program comprehension, with direct implications for programming methodology, language design, and education.
In this seminar, we will review and discuss the past, current, and future developments in this area.


Registration for the seminar is mandatory. To distribute students among the available seminars offered by the computer science department, you have to select your preferences for a seminar or a proseminar on the central registration platform for seminars and will be automatically assigned to a seminar according to your preferences.

If you are assigned to this seminar, for organizational reasons, you have to sign up both in the course registration form that will be given above and in the LSF (seminar, proseminar). Deadlines for the LSF (HISPOS) registration will be posted in the LSF (HISPOS) portal. Registration is possible up to three weeks after the topic assignment / kick-off.

In this seminar, each participant has to perform a literature search and propose an experiment for the given topic.
Subsequently, the topic, the results of the literature search, and the proposed experiment have to be incorporated into a presentation and a written thesis.
To aid the literature search, the experiment proposal, and the presentation, this seminar includes multiple preparatory sessions at the beginning of the semester.
The student presentations will be held in June and July 2022.
All sessions will take place on-site at the university (under the caveat that the pandemic situation admits in-person sessions) on Thursdays 12:15 PM - 2:00 PM.
Participation to all sessions is mandatory.
The topic assignment will take place on Thursday April 21, at 12:15 PM. Further information will be provided via e-mail after registration.


The following book is mandatory to read for this course:

  • R. Poldrack. The New Mind Readers: What Neuroimaging Can and Cannot Reveal about our Thoughts. Princeton University Press, 2018.

The following papers and topics are available in this course:

  Topic Paper
01 Seminal fMRI Study on Program Comprehension Understanding Understanding Source Code with Functional Magnetic Resonance Imaging
02 Top-Down Comprehension Measuring Neural Efficiency of Program Comprehension
03 Code Comprehension & Code Review Decoding the Representation of Code in the Brain: An fMRI Study of Code Review and Expertise
04 Data Structure Manipulation Distilling Neural Representations of Data Structure Manipulation Using fMRI and fNIRS
05 Bug Detection The Role of the Insula in Intuitive Expert Bug Detection in Computer Code: An fMRI Study
06 Writing Prose vs. Writing Code Neurological Divide: An fMRI Study of Prose and Code Writing
07 Expert Programmers Expert Programmers Have Fine-Tuned Cortical Representations of Source Code
08 Brain Areas & Code Comprehension Comprehension of Computer Code Relies Primarily on Domain-General Executive Resources
09 Brain Areas & Code Comprehension Computer Code Comprehension Shares Neural Resources with Formal Logical Inference in the Fronto- Parietal Network
10 Code Review Biases Biases and Differences in Code Review using Medical Imaging and Eye-Tracking: Genders, Humans, and Machines
11 Complexity Metrics Program Comprehension and Code Complexity Metrics: An fMRI Study
12 Combining fMRI & Eye Tracking Simultaneous Measurement of Program Comprehension with fMRI and Eye Tracking: A Case Study
13 Cognitive Load of Code Comprehension The Effect of Poor Source Code Lexicon and Readability on Developers’ Cognitive Load
14 Programmer Classification Mining Biometric Data to Predict Programmer Expertise and Task Difficulty. Cluster Computing
15 Replication Study without fMRI A Replication Study on Code Comprehension and Expertise using Lightweight Biometric Sensors
16 EEG Towards an Affordable Brain Computer Interface for the Assessment of Programmers’ Mental Workload

























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