Abstract
As shown by several studies, programmers’ readability of source code is influenced by its structural and the textual features. In order to assess the importance of these features, we conducted an eye-tracking experiment with programming students. To assess the readability and comprehensibility of code snippets, the test subjects were exposed to four different snippets containing or missing structural and/or textual elements. To assure that all subjects were at an equivalent level of expertise, their programming skills were also evaluated. During the eye-tracking experiment, the subjects were also asked to give a readability and comprehensibility score to each snippet. The absence of textual features showed to increase the average fixation duration. This indicates that for the test subjects the textual features were more essential for the comprehension of the code. Gaze pattern analysis revealed less ordered patterns in the absence of structural features compared to the absence of textual features.
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Notes
- 1.
Source codes are written in a programming language, which a human can easily read. A large program may contain many different source code files within its architecture. Compilers translate source codes into machine language, which is processed faster by the digital machine but it is harder for a human to deal with.
References
Kuhn, A., Ducasse, S., Gîrba, T.: Semantic clustering: identifying topics in source code. Inf. Softw. Technol. 49, 230–243 (2007). https://doi.org/10.1016/j.infsof.2006.10.017
Busjahn, T., Bednarik, R., Begel, A., Crosby, M., Paterson, J.H., Schulte, C., Sharif, B., Tamm, S.: Eye movements in code reading: relaxing the linear order. In: IEEE International Conference on Program Comprehension August 2015, pp. 255–265 (2015). https://doi.org/10.1109/icpc.2015.36
Schulte, C., Clear, T., Taherkhani, A., Busjahn, T., Paterson, J.H.: An introduction to program comprehension for computer science educators. In: Proceedings of the 2010 ITiCSE Working Group Reports on Working Group Reports - ITiCSE-WGR 2010, p. 65 (2010). https://doi.org/10.1145/1971681.1971687
Macizo, P., Teresa Bajo, M.: When translation makes the difference: sentence processing in reading and translation. Psicológica 25, 181–205 (2004)
Buse, R.P.L., Weimer, W.R.: Learning a metric for code readability. IEEE Trans. Softw. Eng. 36, 546–558 (2010). https://doi.org/10.1109/TSE.2009.70
Boehm, B., Basili, V.R.: Software defect reduction top 10 list. Computer (2001). https://doi.org/10.1109/2.962984
Posnett, D., Hindle, A., Devanbu, P.: A simpler model of software readability. In: Proceeding of the 8th Working Conference on Mining Software Repositories - MSR 2011, p. 73 (2011). https://doi.org/10.1145/1985441.1985454
Scalabrino, S., Linares-Vasquez, M., Poshyvanyk, D., Oliveto, R.: Improving code readability models with textual features. In: IEEE International Conference on Program Comprehension, July 2016 (2016). https://doi.org/10.1109/icpc.2016.7503707
Dorn, J.: A general software readability model. MCS thesis (2012)
Sharif, B., Falcone, M., Maletic, J.I.: An eye-tracking study on the role of scan time in finding source code defects. In: Proceedings of the Symposium on Eye Tracking Research and Applications - ETRA 2012, pp. 381–384 (2012). https://doi.org/10.1145/2168556.2168642
Busjahn, T., Shchekotova, G., Antropova, M., Schulte, C., Sharif, B., Begel, A., Hansen, M., Bednarik, R., Orlov, P., Ihantola, P.: Eye tracking in computing education. In: Proceedings of the Tenth Annual Conference on International Computing Education Research - ICER 2014, pp. 3–10 (2014). https://doi.org/10.1145/2632320.2632344
Bednarik, R.: Expertise-dependent visual attention strategies develop over time during debugging with multiple code representations. Int. J. Hum. Compu. Stud. 70, 143–155 (2012). https://doi.org/10.1016/j.ijhcs.2011.09.003
Gilmore, D.J.: Models of debugging. Acta Physiol. (Oxf) 78, 151–172 (1991). https://doi.org/10.1016/0001-6918(91)90009-O
Rosch, J.L., Vogel-Walcutt, J.J.: A review of eye-tracking applications as tools for training. Cogn. Technol. Work (2013). https://doi.org/10.1007/s10111-012-0234-7
Hess, E.H.: Attitude and pupil size. Sci. Am. 212, 46–54 (1965). https://doi.org/10.1038/scientificamerican0465-46
Meghanathan, R.N., van Leeuwen, C., Nikolaev, A.R.: Fixation duration surpasses pupil size as a measure of memory load in free viewing. Front. Hum. Neurosci. 8 (2015). https://doi.org/10.3389/fnhum.2014.01063
Pachymeningitis Abscess, Pain Control, and Pain Management: Pupillary response. In: Encyclopedia of Intensive Care Medicine, 1934–1938. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-00418-6
Feigenspan, J., Kastner, C., Liebig, J., Apel, S., Hanenberg, S.: Measuring programming experience. In: 2012 20th IEEE International Conference on Program Comprehension (ICPC), pp. 73–82 (2012). https://doi.org/10.1109/icpc.2012.6240511
Voßkühler, A., Nordmeier, V., Kuchinke, L., Jacobs, A.M.: OGAMA (Open Gaze and Mouse Analyzer): open-source software designed to analyze eye and mouse movements in slideshow study designs. Behav. Res. Methods 40, 1150–1162 (2008). https://doi.org/10.3758/BRM.40.4.1150
Timmermann, D., Kautz, C.: Design of open educational resources for a programming course with a focus on conceptual understanding. In: Proceedings of the 44th SEFI Annual Conference on Design of Open, Tampere, Finland, pp. 12–15 (2016)
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Wulff-Jensen, A., Ruder, K., Triantafyllou, E., Bruni, L.E. (2019). Gaze Strategies Can Reveal the Impact of Source Code Features on the Cognitive Load of Novice Programmers. In: Ayaz, H., Mazur, L. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 775. Springer, Cham. https://doi.org/10.1007/978-3-319-94866-9_9
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