Mining biometric data to predict programmer expertise and task difficulty

Lee, Seolhwa; Hooshyar, Danial; Ji, Hyesung; Nam, Kichun; Lim, Heuiseok

doi:10.1007/s10586-017-0746-2

Cited by 45 publications

(39 citation statements)

References 26 publications

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“…We analyze eye-tracking data based on method size using the same approach in RQ1 by adjusting the gaze time and number of visits for each location (signature, body, calls, control flow). Then, methods are divided by their size -large (40-80 LOC), medium (23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39), and small (9-22 LOC). For each category, the eye movements on signature, call, and control flow statements are analyzed.…”

Section: B Rq2 Results: Methods Sizementioning

confidence: 99%

“…Eye Tracking Studies: Eye-tracking technology is being used in software engineering [20][21][22][23][24][25] to study how programmers read [4,[26][27][28][29][30], review [31][32][33], and summarize [17,28,34] source code. Crosby et al [4] conducted an early eye-tracking study of high and low experience programmers reading a binary search algorithm.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Developer Reading Behavior While Summarizing Java Methods: Size and Context Matters

Abid

Sharif

Dragan

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)

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An eye-tracking study of 18 developers reading and summarizing Java methods is presented. The developers provide a written summary for methods assigned to them. In total, 63 methods are used from five different systems. Previous studies on this topic use only short methods presented in isolation usually as images. In contrast, this work presents the study in the Eclipse IDE allowing access to all the source code in the system. The developer can navigate via scrolling and switching files while writing the summary. New eye-tracking infrastructure allows for this improvement in the study environment. Data collected includes eye gazes on source code, written summaries, and time to complete each summary. Unlike prior work that concluded developers focus on the signature the most, these results indicate that they tend to focus on the method body more than the signature. Moreover, both experts and novices tend to revisit control flow terms rather than reading them for a long period. They also spend a significant amount of gaze time and have higher gaze visits when they read call terms. Experts tend to revisit the body of the method significantly more frequently than its signature as the size of the method increases. Moreover, experts tend to write their summaries from source code lines that they read the most.

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Section: B Rq2 Results: Methods Sizementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Developer Reading Behavior While Summarizing Java Methods: Size and Context Matters

Abid

Sharif

Dragan

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)

View full text Add to dashboard Cite

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“…Some studies found that the increasing cognitive load impacts on developers' performance during the cognitive process, such as, comprehending source code [6,19]. In the case of certain level of cognitive workload jeopardize the developers' comprehension, then the software project probably will be compromised too [14]. The cognitive workload level also is an information that can be used to a wide range of purposes such as, for indicating the level of learning, to promote task recommendations based on their cognitive work load.…”

Section: Research Agenda and Challengesmentioning

confidence: 99%

“…Applications: There are a lot of applications which researchers in the software engineering research field are interested such as, identifying the level of expertise of developers [6], measuring the task difficulty according to developers' perception [19,14], and improving the developers' well-being [10]. However, there are many shortcomings which academia and industry must overcome in order to deploy the cognitive load indicator in realistic scenarios definitively.…”

Section: Introductionmentioning

confidence: 99%

Towards the Measurement of Mental Effort in Software Engineering: A Research Agenda

Gonçales¹,

Farias²

2020

IJCA

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Cognitive load refers to the mental effort applied to perform cognitive processes. In software engineering, developers are involved in cognitive processes such as program comprehension and change tasks. Measuring cognitive load would be a human-centered solution, instead of using measurements based on artifacts which have been shown to have no correlation with developers' perception. Therefore, evaluate the cognitive load of the developer has potential to leverage the identification of source code issues and also improve the developers experience with their work environment. To determine a potential searcher to identify and organize this article a research agenda in relation to the measure of cognitive load of developers. This article also discusses the implications of using the cognitive load as a multipurpose indicator in software engineering. Finally, this article provides for practitioners and researchers a way to advance in the research about developers' cognitive load in software engineering in realistic scenarios.

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“…Recently, an attempt has been made to analyze and compare bio signals and physical activity information for accurate analysis and diagnosis. In addition, data processing and analysis techniques using big data and data mining are used for bio signal processing for precise diagnosis [7], [8]. However, in order to measure the ECG data for a long time, a storage space of several Mbytes and a wide bandwidth for wireless transmission are required.…”

Section: Introductionmentioning

confidence: 99%

Implementation of The Variable Data Transmission System of Abnormal ECG with Activity State

Noh

Seo

Nam

et al. 2019

Int. J. Adv. Sci. Eng. Inf. Technol.

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The cause of death among modern people are the highest death rate from heart disease and monitoring and management of ECG signals to cope with these heart diseases is necessary. ECG is a bio-signal that is an important criterion for determining the presence or absence of cardiac activity states. Recently, an attempt has been made to analyze and compare biological signals and physical activity information for accurate analysis and diagnosis. However, in order to measure the ECG data for a long time, a storage space of several Mbytes and a wide bandwidth for wireless transmission are required. To solve this problem, cost, time, and high-performance systems are additional required. The implemented system minimizes the amount of packets generated during wireless data transmission as well as abnormal heartbeat detection and activity information, and enables monitoring of heart activity status and activity information in real time through a smart phone. In order to evaluate the data packet transmission and restoration performance of the system implemented in this research, the MIT / BIH Arrhythmia Database 100 record was embedded in the system controller section and the packet was transmitted to the smartphone. In addition, ECG evaluation experiments were conducted according to the activity status during daily life. As a result of the performance evaluation, both experiments confirmed the data packet generated and signal restoration performance.

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Mining biometric data to predict programmer expertise and task difficulty

Cited by 45 publications

References 26 publications

Developer Reading Behavior While Summarizing Java Methods: Size and Context Matters

Developer Reading Behavior While Summarizing Java Methods: Size and Context Matters

Towards the Measurement of Mental Effort in Software Engineering: A Research Agenda

Implementation of The Variable Data Transmission System of Abnormal ECG with Activity State

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