Combining eye tracking with navigation paths for identification of cross-language code dependencies

Konôpka, Martin

doi:10.1145/2786805.2807561

Cited by 5 publications

(1 citation statement)

References 21 publications

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“…• Konopka (2015) investigated the possibility of using eye-tracking data and navigation paths in order to identify and find source code dependencies. • Palmer and Sharif (2016) introduced a fixation shift algorithm in an attempt to correct the location of a fixation automatically, in cases of fixation drift or calibration inaccuracy.…”

Section: Data Collection Resultsmentioning

confidence: 99%

A Survey on the Usage of Eye-Tracking in Computer Programming

2018

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Traditional quantitative research methods of data collection in programming, such as questionnaires and interviews, are the most common approaches for researchers in this field. However, in recent years, eye-tracking has been on the rise as a new method of collecting evidence of visual attention and the cognitive process of programmers. Eyetracking has been used by researchers in the field of programming to analyze and understand a variety of tasks such as comprehension and debugging. In this paper, we will focus on reporting how experiments that used eye-trackers in programming research are conducted, and the information that can be collected from these experiments. In this mapping study, we identify and report on 63 studies, published between 1990 and June 2017, collected and gathered via manual search on digital libraries and databases related to computer science and computer engineering. Among the five main areas of research interest are program comprehension and debugging, which received an increased interest in recent years, non-code comprehension, collaborative programming and requirements traceability research, which had the fewest number of publications due to possible limitations of the eye-tracking technology in this type of experiments. We find that most of the participants in these studies were students and faculty members from institutions of higher learning, and while they performed programming tasks on a range of programming languages and programming representations, we find Java language and UML representation to be the most used materials. We also report on a range of eye-trackers and attention tracking tools that have been utilized, and find Tobii eye-trackers to be the most used devices by researchers.

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Section: Data Collection Resultsmentioning

confidence: 99%

A Survey on the Usage of Eye-Tracking in Computer Programming

2018

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What you see is what you trace: a two-stage interview study on traceability practices and eye tracking potential

Ahrens,

Nagel,

Schneider

2024

Requirements Eng

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The benefits of traceability have widely been discussed in research. However, studies have also shown that traceability practices are still not prevalent in industrial settings due to the high manual effort and lack of tool support. In this paper, we explore the feasibility of using eye tracking to automatically detect trace links to reduce manual effort and thereby increase practical applicability. We conducted a two-stage interview study in industry. In Stage 1 we interviewed 20 practitioners to provide an overview of how traceability is established in practice and how an eye tracking approach would need to be applied in order to be useful. In Stage 2 we conducted interviews with 16 practitioners from one project context to elicit role-specific workflows and analyzed which activities are suitable to obtain useful traceability links based on gaze data. As there is no one-fits-all solution to traceability, and technical limitations of eye tracking still exist, we collected information on used artifact types, tools and requirements management practices to adjust an approach to actual traceability stakeholders’ needs. We report on perspectives from different roles in software projects and give an overview of traced artifacts, current traceability experiences, as well as benefits and doubts concerned with using eye tracking to obtain links automatically. We discuss the implications for the evaluation and implementation of an automatic tracing approach in practice and how eye tracking can support requirements engineering activities.

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