Software Engineering Research in the Neuroage Prof. Dr. Sven Apel Seminar — Winter Semester 2019


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About the Seminar

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 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.
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.

Kick-off and topic assignment will take place on October 24, at 12:15 in E1 1 room 206.



  • R. Poldrack. New Mind Readers: What Neuroimaging Can and Cannot Reveal about our Thoughts. Princeton University Press, 2018.
  • J. Siegmund, C. Kästner, S. Apel, C. Parnin, A. Bethmann, T. Leich, G. Saake, and A. Brechmann. Understanding Understanding Source Code with Functional Magnetic Resonance Imaging. In Proc. Int. Conf. Software Engineering (ICSE), pages 378–389. ACM, 2014.
  • J. Siegmund, N. Peitek, C. Parnin, S. Apel, J. Hofmeister, C. Kästner, A. Begel, A. Bethmann, and A. Brechmann. Measuring Neural Effi-
    ciency of Program Comprehension. In Proc. Europ. Software Engineering Conf./Foundations of Software Engineering (ESEC/FSE), pages 140–150. ACM, 2017.
  • N. Peitek, J. Siegmund, S. Apel, C. Kästner, C. Parnin, A. Bethmann, T. Leich, G. Saake, and A. Brechmann. A Look into Programmers’ Heads. IEEE Transactions on Software Engineering, 2018. Online first.
  • N. Peitek, J. Siegmund, C. Parnin, S. Apel, J. Hofmeister, and A. Brechmann. Simultaneous Measurement of Program Comprehension with
    fMRI and Eye Tracking: A Case Study. In Proc. Int. Symp. Empirical Software Engineering and Measurement (ESEM), page 24:1–24:10. ACM, 2018.
  • J. Duraes, H. Madeira, J. Castelhano, C. Duarte, and M. C. Branco. WAP: Understanding the Brain at Software Debugging. In Proc. Int. Symposium Software Reliability Engineering (ISSRE), pages 87–92. IEEE, 2016.
  • B. Floyd, T. Santander, and W. Weimer. Decoding the Representation of Code in the Brain: An fMRI Study of Code Review and Expertise. In Proc. Int. Conf. Software Engineering (ICSE), pages 175–186. IEEE, 2017.
  • Y. Huang, X. Liu, R. Krueger, T. Santander, X. Hu, K. Leach, T. Santander, and W. Weimer. Distilling Neural Representations of Data Structure Manipulation using fMRI and fNIRS. In Proc. Int. Conf. Software Engineering (ICSE). IEEE, 2019.
  • S. Fakhoury, Y. Ma, V. Arnaoudova, and O. Adesope. The Effect of Poor Source Code Lexicon and Readability on Developers’ Cognitive Load. In Proc. Int. Conf. Program Comprehension (ICPC), pages 286–296. ACM, 2018.
  • T. Nakagawa, Y. Kamei, H. Uwano, A. Monden, K. Matsumoto, and D. M. German. Quantifying Programmers’ Mental Workload During Program Comprehension Based on Cerebral Blood Flow Measurement: A Controlled Experiment. In Proc. Int. Conf. Software Engineering (ICSE), pages 448–451. ACM, 2014.
  • Y. Ikutani and H. Uwano. Brain Activity Measurement during Program Comprehension with NIRS. In Proc. Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), pages 1–6. IEEE, 2014.
  • M. Kosti, K. Georgiadis, D. Adamos, N. Laskaris, D. Spinellis, and L. Angelis. Towards an Affordable Brain Computer Interface for the Assessment of Programmers’ Mental Workload. J. Human–Computer Studies, 115:52–66, 2018.
  • S. Lee, D. Hooshyar, H. Ji, K. Nam, and H. Lim. Mining Biometric Data to Predict Programmer Expertise and Task Difficulty. Cluster Computing, 21(1):1097–1107, 2018.
  • M. Yeh, D. Gopstein, Y. Yan, and Y. Zhuang. Detecting and Comparing Brain Activity in Short Program Comprehension Using EEG. In Proc. Frontiers in Education Conference, pages 1–5. IEEE, 2017.
  • T. Ishida, and H. Uwano. Synchronized Analysis of Eye Movement and EEG During Program Comprehension. In Proc. Int. Workshop on Eye Movements in Programming (EMIP), pages 26–32, IEEE, 2019.

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