Leveraging Biometric Data to Boost Software Developer Productivity

Fritz, Thomas; Müller, Sebastian

doi:10.1109/saner.2016.107

Cited by 33 publications

(28 citation statements)

References 81 publications

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“…According to Fritz and Muller, cognitive load refers to the cognitive effort that developers should apply to perform a development task [55,57]. Today, we have learned from previous studies [55,[57][58][59] that the effort that developers invest to do a development task can be narrowly related to the cognitive load realised by them. This means that the higher measures of cognitive effort, the lower performance of developers [56].…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

“…Ali Idri and Alain Abran were the third most active researcher with 14 publications. Cognitive load: recent studies have used the measure of cognitive load as a base to calculate the performance of developers on software‐development tasks [55, 56]. According to Fritz and Muller, cognitive load refers to the cognitive effort that developers should apply to perform a development task [55, 57]. Today, we have learned from previous studies [55, 57–59] that the effort that developers invest to do a development task can be narrowly related to the cognitive load realised by them.…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

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Software development effort estimation: a systematic mapping study

2020

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The field of software-development effort estimation explores ways of defining effort through prediction approaches. Even though this field has a crucial impact on budgeting and project planning in industry, the number of works classifying and examining currently available approaches is still small. This article, therefore, presents a comprehensive overview of these approaches, and pinpoints research gaps, challenges and trends. A systematic mapping of the literature was designed and performed based on well-established practical guidelines. In total, 120 primary studies were selected, analysed and categorised, after applying a careful filtering process from a sample of 3746 candidate studies to answer six research questions. Over 70% of the selected studies adopted multiple effort estimation approaches; over 45% adopted evaluation research as a research method; over 90% of the participants were students, rather than professionals; most studies had their quality assessed as high, and were most commonly published in journals. Our study benefits practitioners and researchers by providing a body of knowledge about the current literature, serving as a starting point for upcoming studies. This article reports challenges worth investigating, regarding the use of cognitive load and team interaction. 2 Planning This section aims to outline our review protocol. Fig. 1 introduces the adopted systematic mapping process, which is formed by three

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Section: Discussion and Future Directionsmentioning

confidence: 99%

Section: Discussion and Future Directionsmentioning

confidence: 99%

Software development effort estimation: a systematic mapping study

2020

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“…The most comprehensive research on utilizing physiological sensors during software developers' work was conducted by Müller and Fritz [5,9,10]. During their study [5] on 17 software developers, they collected the following data: electroencephalography (EEG) data using a Neurosky MindBand sensor, temperature, electrodermal activity (EDA) and blood volume pulse (BVP) using an Empatica E3 wrist band, and eye-tracking data using Eye Tribe.…”

Section: Related Workmentioning

confidence: 99%

Applicability of Emotion Recognition and Induction Methods to Study the Behavior of Programmers

Wróbel¹

2018

Applied Sciences

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Recent studies in the field of software engineering have shown that positive emotions can increase and negative emotions decrease the productivity of programmers. In the field of affective computing, many methods and tools to recognize the emotions of computer users were proposed. However, it has not been verified yet which of them can be used to monitor the emotional states of software developers. The paper describes a study carried out on a group of 35 participants to determine which of these methods can be used during programming. During the study, data from multiple sensors that are commonly used in methods of emotional recognition were collected. The participants were extensively questioned about the sensors' invasiveness during programming. This allowed us to determine which of them are applicable in the work of programmers. In addition, it was verified which methods are suitable for use in the work environment and which are only suitable in the laboratory. Moreover, three methods for inducing negative emotions have been proposed, and their effectiveness has been verified.

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“…have performed a similar study applying fMRI to understand the mental activities surrounding program comprehension [9]. c) Ensemble of bio-metric sensors: An alternative approach has been to use an ensemble of bio-metric sensors like eye trackers for measuring pupil size and eye blinks, electroencephalography to determine brain activity, electrodermal activity sensors to detect skin-related activity, and heart-related sensors [10], [17], [29]. This approach was applied in a series of investigations which will be described below.…”

Section: Introductionmentioning

confidence: 99%

Initial evaluation of the brain activity under different software development situations

Ikramov¹,

Ivanov²,

Masyagin³

et al. 2019

International Conferences on Software Engineering and Knowledge Engineering

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The use of biological signals to understand software development has become more popular in the last few years but poses new challenges with respect to the overall experimental settings. In this paper we present such challenges and the approach we took to overcome them. We illustrate our approach by evaluating two programming situations: pair programming and programming with music. The subjects involved in the experimentation are mostly students, however, in the largest case we involved graduate students coming from industry with at least three years of working experience. The results in general support the validity of this approach and encourage to go further in this research line. Moreover, as a byproduct, the analysis of pair programming confirms, from a biological perspective, early hypotheses that pair programming induces higher level of concentration.

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Leveraging Biometric Data to Boost Software Developer Productivity

Cited by 33 publications

References 81 publications

Software development effort estimation: a systematic mapping study

Software development effort estimation: a systematic mapping study

Applicability of Emotion Recognition and Induction Methods to Study the Behavior of Programmers

Initial evaluation of the brain activity under different software development situations

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