CodersMUSE: Multi-Modal Data Exploration of Program-Comprehension Experiments

Program comprehension is a central cognitive process in programming. It has been in the focus of researchers for decades, but is still not thoroughly unraveled. Multi-modal psycho-physiological and neurobiological measurement methods have proved successful to gain a more holistic understanding of program comprehension. However, there is no proper tool support that lets researchers explore synchronized, conjoint multi-modal data, specifically designed for the needs in program-comprehension research. In this paper, we present CodersMUSE, a prototype implementation that aims to satisfy this crucial need.

[1]  Andrew Begel,et al.  Using psycho-physiological measures to assess task difficulty in software development , 2014, ICSE.

[2]  Sascha Meudt,et al.  Atlas - Annotation tool using partially supervised learning and multi-view co-learning in human-computer-interaction scenarios , 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).

[3]  Westley Weimer,et al.  Decoding the Representation of Code in the Brain: An fMRI Study of Code Review and Expertise , 2017, 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE).

[4]  Sven Apel,et al.  Toward conjoint analysis of simultaneous eye-tracking and fMRI data for program-comprehension studies , 2018, EMIP@ETRA.

[5]  B. Chance,et al.  Cognition-activated low-frequency modulation of light absorption in human brain. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[6]  W. Marsden I and J , 2012 .

[7]  Sven Apel,et al.  Measuring neural efficiency of program comprehension , 2017, ESEC/SIGSOFT FSE.

[8]  Sven Apel,et al.  Simultaneous measurement of program comprehension with fMRI and eye tracking: a case study , 2018, ESEM.

[9]  Janet Siegmund,et al.  Program Comprehension: Past, Present, and Future , 2016, 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER).

[10]  W. Boucsein Electrodermal activity, 2nd ed. , 2012 .

[11]  Rebecca Tiarks What Programmers Really Do - An Observational Study , 2011, Softwaretechnik-Trends.

[12]  Venera Arnaoudova,et al.  The Effect of Poor Source Code Lexicon and Readability on Developers' Cognitive Load , 2018, 2018 IEEE/ACM 26th International Conference on Program Comprehension (ICPC).

[13]  Henrique Madeira,et al.  The role of the insula in intuitive expert bug detection in computer code: an fMRI study , 2018, Brain Imaging and Behavior.

[14]  Arthur M. Jacobs,et al.  OGAMA (Open Gaze and Mouse Analyzer): Open-source software designed to analyze eye and mouse movements in slideshow study designs , 2008, Behavior research methods.

[15]  Andreas Stefik,et al.  Understanding Programming Expertise , 2015, ACM Trans. Comput. Hum. Interact..

[16]  Thomas Leich,et al.  Understanding understanding source code with functional magnetic resonance imaging , 2014, ICSE.