Proceedings of the 36th International Conference on Software Engineering 2014
DOI: 10.1145/2568225.2568252
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Understanding understanding source code with functional magnetic resonance imaging

Abstract: Program comprehension is an important cognitive process that inherently eludes direct measurement. Thus, researchers are struggling with providing suitable programming languages, tools, or coding conventions to support developers in their everyday work. In this paper, we explore whether functional magnetic resonance imaging (fMRI), which is well established in cognitive neuroscience, is feasible to more directly measure program comprehension. In a controlled experiment, we observed 17 participants inside an fM… Show more

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Cited by 163 publications
(138 citation statements)
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References 78 publications
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“…One of the early approaches in the software development domain mentioning biometric sensor technology is the Ginger2 environment by Torii and colleagues that included an eye-tracker and a skin resistance level sensor to empirically study developers [60]. In the context of software development, biometric sensors have been and are being used predominantly to gain a better understanding of developers' program comprehension either using eye-tracking [61]- [64] or by measuring brain activity [65], [66]. Recently, especially with the advances in sensor technology and the availability of more affordable biometric sensors, a few software engineering researchers have also looked at other aspects, for instance, using measures of cerebral blood flow, measures of sub-vocal utterances captured with electromyography (EMG), or EDA, eye-tracking and brain activity measures to asses task difficulty of small code snippets or programming tasks [67]- [69].…”
Section: Biometric Sensing In Software Developmentmentioning
confidence: 99%
“…One of the early approaches in the software development domain mentioning biometric sensor technology is the Ginger2 environment by Torii and colleagues that included an eye-tracker and a skin resistance level sensor to empirically study developers [60]. In the context of software development, biometric sensors have been and are being used predominantly to gain a better understanding of developers' program comprehension either using eye-tracking [61]- [64] or by measuring brain activity [65], [66]. Recently, especially with the advances in sensor technology and the availability of more affordable biometric sensors, a few software engineering researchers have also looked at other aspects, for instance, using measures of cerebral blood flow, measures of sub-vocal utterances captured with electromyography (EMG), or EDA, eye-tracking and brain activity measures to asses task difficulty of small code snippets or programming tasks [67]- [69].…”
Section: Biometric Sensing In Software Developmentmentioning
confidence: 99%
“…Given Example 2, any of the two statements could be counted as the one containing the duplication. However, reading and writing source code typically happens from top to bottom and from left to right (Siegmund et al 2014). Therefore, the only natural assessment is to flag lines and statements as problematic according to this strict left-right and top-down visual reading order: In Example 2, only when we have read the second statement do we know it is a duplicate of the first.…”
Section: Internal Threatsmentioning
confidence: 99%
“…Our a-posteriori repository mining approach assumes a top-to-bottom reading order of blocks and a left-toright reading order for individual lines. We know that developers "jump" in the code when reading a file, only focusing on what seems important to solve the task at hand (Busjahn et al 2015;Siegmund et al 2014). However, in order to understand small coherent logical units, such as micro-clones, developers must necessarily read in the control-flow-direction of the software -which is top-to-bottom, left-to-right.…”
Section: Internal Threatsmentioning
confidence: 99%
“…For replication purposes, a free trial of PVS-Studio is publicly available. 6 2) Inspect the corpus of warnings from PVS-Studio and remove false-positives and warnings not related to microcloning. 3) For each faulty micro-clone, count the total number of lines (RQ1) or statements (RQ2) and denote which lines or statements are faulty.…”
Section: A Study Designmentioning
confidence: 99%
“…Given Example 2, any of the two statements could be counted as the one containing the duplication. However, reading and writing source code typically happens from top to bottom and from left to right [6]. Therefore, the only natural assessment is to count the line as problematic according to this strict left-right/top-down-reading order: In Example 2, only when we read the second statement do we know it is a duplicate of the first.…”
Section: Threats To Validitymentioning
confidence: 99%