A Look into Programmers’ Heads

Peitek, Norman; Siegmund, Janet; Apel, Sven; Kästner, Christian; Parnin, Chris; Bethmann, Anja; Leich, Thomas; Saake, Gunter; Brechmann, André

doi:10.1109/tse.2018.2863303

Cited by 45 publications

(31 citation statements)

References 95 publications

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“…Other novel findings in the present study were potential involvement of the left IT, right MFG, and right IFG Tri with programming expertise. Importantly, these regions were not specified by previous studies focusing on the relationship between brain activity and program comprehension processes [17][18][19][20] , suggesting that the regions might be more related to programming expertise than program comprehension processes. Because the left IT is well known for the function in high-level visual processing including word recognition and categorical object representations [45][46][47] , our results may suggest that high-level visual cortex in expert programmers' brain could be fine-tuned by their training experience to realize faster program comprehension process.…”

Section: Discussionmentioning

confidence: 69%

“…Despite the difference in research aims, a subset of brain regions specified in this study was similar to those specified by prior fMRI studies on programmers [17][18][19] . In particular, this study associated the left IFG, MTG, IPL, SMG with programming expertise while previous studies related them with program comprehension processes.…”

Section: Discussionmentioning

confidence: 90%

“…We then searched in the open codeset for Java code snippets implementing one of the selected algorithms and found 1251 candidates. The reasons why we focused on Java in this study were because the language has been one of the most famous programming languages 67 and prior fMRI studies on programmers also used Java code snippets as experimental stimuli [17][18][19] . To meet the screen size constraint in the MRI scanner, we excluded code snippets with lines of code (LOC) more than 30 and characters per line (CPL) more than 120.…”

Section: Source Code Selection and Normalizationmentioning

confidence: 99%

“…Several studies have also tried to investigate neural correlates of subject-wise programming expertise but failed to find a systematic trend. For example, a study reported no significant correlation between BOLD activation strength and subjective estimates of programming experience 19 . Although an exploratory study argued the correlation between activity pattern discriminability and students' GPA score 20 , the assumed relationship of GPA scores to programming expertise was ambiguous and not empirically validated.…”

Section: Introductionmentioning

confidence: 99%

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Expert programmers have fine-tuned cortical representations of source code

Ikutani

Kubo

Nishida

et al. 2020

Preprint

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Expertise enables humans to achieve outstanding performance on domain-specific tasks, and programming is no exception. Many have shown that expert programmers exhibit remarkable differences from novices in behavioral performance, knowledge structure, and selective attention. However, the underlying differences in the brain are still unclear. We here address this issue by associating the cortical representation of source code with individual programming expertise using a data-driven decoding approach. This approach enabled us to identify seven brain regions, widely distributed in the frontal, parietal, and temporal cortices, that have a tight relationship with programming expertise. In these brain regions, functional categories of source code could be decoded from brain activity and the decoding accuracies were significantly correlated with individual behavioral performances on source-code categorization. Our results suggest that programming expertise is built up on fine-tuned cortical representations specialized for the domain of programming.

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Section: Discussionmentioning

confidence: 69%

Section: Discussionmentioning

confidence: 90%

Section: Source Code Selection and Normalizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Expert programmers have fine-tuned cortical representations of source code

Ikutani

Kubo

Nishida

et al. 2020

Preprint

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“…The software engineering research community has studied the relationship between the developers' cognitive statemeasured using physiological signals-and several aspects of software development, like code comprehension [17], productivity [18], and software quality [19].…”

Section: Use Of Biometrics In Software Engineeringmentioning

confidence: 99%

A Replication Study on Code Comprehension and Expertise using Lightweight Biometric Sensors

Fucci

Girardi

Novielli

et al. 2019

2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)

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Code comprehension has been recently investigated from physiological and cognitive perspectives using medical imaging devices. Floyd et al. (i.e., the original study) used fMRI to classify the type of comprehension tasks performed by developers and relate their results to their expertise. We replicate the original study using lightweight biometrics sensors. Our study participants-28 undergrads in computer science-performed comprehension tasks on source code and natural language prose. We developed machine learning models to automatically identify what kind of tasks developers are working on leveraging their brain-, heart-, and skin-related signals. The best improvement over the original study performance is achieved using solely the heart signal obtained through a single device (BAC 87% vs. 79.1%). Differently from the original study, we did not observe a correlation between the participants' expertise and the classifier performance (τ = 0.16, p = 0.31). Our findings show that lightweight biometric sensors can be used to accurately recognize comprehension tasks opening interesting scenarios for research and practice.

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Biometric Measurement in Software Engineering

Fagerholm

Fritz

2020

Contemporary Empirical Methods in Software Engineering

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Biometric sensor technology provides new opportunities to measure physiological changes in the human body that can be linked to various psychological processes. In software engineering, these biometric measurements can be used to gain insights on fundamental cognitive and emotional processes of software developers while they are working. In addition, biometric measures may be used to provide better and more instantaneous tool support for developers, for instance by preventing defects from being introduced in the code or supporting focused work. In this book chapter, we motivate the use of biometric measurements, introduce common types of biometric sensors and measures, discuss how to choose the right set of them and considerations for analyzing the collected data. We also discuss work in the area of software engineering and recommend further reading.

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A Look into Programmers’ Heads

Cited by 45 publications

References 95 publications

Expert programmers have fine-tuned cortical representations of source code

Expert programmers have fine-tuned cortical representations of source code

A Replication Study on Code Comprehension and Expertise using Lightweight Biometric Sensors

Biometric Measurement in Software Engineering

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