Studying Developer Reading Behavior on Stack Overflow during API Summarization Tasks

Saddler, Jonathan A.; Peterson, Cole S.; Sama, Sanjana; Nagaraj, Shruthi; Baysal, Olga; Guerrouj, Latifa; Sharif, Bonita

doi:10.1109/saner48275.2020.9054848

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…This has a huge impact on the reading behavior of the readers. Similarly, a study has proved that the number of paragraphs is inversely proportional to the reading efficiency [19].…”

Section: Related Workmentioning

confidence: 95%

Impact of Skim Reading Based on Different Screen Sizes

Mehmood¹,

Mahoto²,

Shaikh³

et al. 2021

Intelligent Automation &Amp; Soft Computing

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Digital technologies have identified themselves in several application domains. This has resulted in massive data availability over the internet. These web contents are generally too long to read. The reader, therefore, skims over the matter because of the limited time available while focusing on understanding the concept of the subject. A hypothesis suggests that full-screen skimming provides a better understanding of ideas as compared to mobile screen skimming. The small size of a mobile device screen is facilitated by a scrolling feature to cover the entire text. In contrast, a full screen provides a larger chunk of text on the screen. In this paper, a software prototype has been developed which sums the contents of the screen in short precis both for computer and mobile screen readers. Experiments have been conducted to analyze the memory of the readers in understanding the meaning of the given text on different screen sizes. The text used in the reading activity experiments has been classified as 1) important, 2) unimportant, and 3) inference sentences. In this study, a total of 50 participants performed a reading activity for a specific time, followed by an evaluation of the text in the form of true or false sentences. The memory of the participants was thereafter analyzed. It was observed that the skimming approach showed better memory about topics and ideas on a computer screen compared to the mobile screen. Thus, the findings of the study were validated in support of the skimming process known as satisficing.

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“…This has a huge impact on the reading behavior of the readers. Similarly, a study has proved that the number of paragraphs is inversely proportional to the reading efficiency [19].…”

Section: Related Workmentioning

confidence: 95%

Impact of Skim Reading Based on Different Screen Sizes

Mehmood¹,

Mahoto²,

Shaikh³

et al. 2021

Intelligent Automation &Amp; Soft Computing

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show abstract

“…CSE professionals often engage in loops of problem‐solving for their work and also in domain‐specific learning activities based on long‐term interests (Nerland, 2008). Empirical studies have shown that CSE professionals rely on multiple online platforms for these purposes, including tutorials and courses (T&C), Q&A and SCR platforms (Saddler et al, 2020; Xia et al, 2017). CSE professionals use these platforms to access different online resources, such as explanations, code snippets, discussions and solutions to coding problems, and to develop and submit contributions to open‐source projects.…”

Section: Use Of Platforms For Learning Activities—a Reviewmentioning

confidence: 99%

“…Empirical studies have shown that CSE professionals rely on multiple online platforms for these purposes, including tutorials and courses (T&C), Q&A and SCR platforms (Saddler et al, 2020;Xia et al, 2017).…”

Section: Use Of Platforms For Cse Domain-specific Learning Activitiesmentioning

confidence: 99%

Browsing to learn: How computer and software engineering students use online platforms in learning activities

Araos

Damşa

Gašević

2022

Computer Assisted Learning

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Background The surge of online platforms has generated interest in how specialized platforms support formal and informal learning in various disciplinary domains. Knowledge is still limited regarding how undergraduate students navigate and use platforms to learn. Objectives This study explores computer and software engineering students' learning practices, wherein online platforms are used as resources for both curricular learning activities and students' interest‐driven learning. Methods The learning practices of 73 students were examined using a mixed‐methods design and a conceptualization of practices accounting for the context and purpose of their enactment. The dataset includes students' self‐reports on domain‐specific learning activities, three‐month‐long web‐browsing history of multiple platforms and stimulated‐recall interviews. The data were analysed through latent class and thematic analyses. Results and Conclusion Five distinct patterns were found in the use of online platforms. These patterns show that different types of platforms were used purposely and in combination during curricular and interest‐driven activities aimed at learning software development. Moreover, students' purposes were driven by both the need to progress in their learning activities and the development of their interest in software development. The findings highlight the complexity of students' learning with online platforms, which develop quite extensively beyond curricular boundaries. Implications The findings stress the need to recognize that undergraduate students' learning practices involve multiple online platforms and activities beyond the formal curriculum and that these play a key role in developing students' interests in learning software development. Moreover, our findings indicate the importance of taking into account the way students' learning practices unfold within platforms and how these relate to domain‐specific practices.

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Deja Vu: semantics-aware recording and replay of high-speed eye tracking and interaction data to support cognitive studies of software engineering tasks—methodology and analyses

et al. 2022

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The paper introduces a fundamental technological problem with collecting high-speed eye tracking data while studying software engineering tasks in an integrated development environment. The use of eye trackers is quickly becoming an important means to study software developers and how they comprehend source code and locate bugs. High quality eye trackers can record upwards of 120 to 300 gaze points per second. However, it is not always possible to map each of these points to a line and column position in a source code file (in the presence of scrolling and file switching) in real time at data rates over 60 gaze points per second without data loss. Unfortunately, higher data rates are more desirable as they allow for finer granularity and more accurate study analyses. To alleviate this technological problem, a novel method for eye tracking data collection is presented. Instead of performing gaze analysis in real time, all telemetry (keystrokes, mouse movements, and eye tracker output) data during a study is recorded as it happens. Sessions are then replayed at a much slower speed allowing for ample time to map gaze point positions to the appropriate file, line, and column to perform additional analysis. A description of the method and corresponding tool, Deja Vu, is presented. An evaluation of the method and tool is conducted using three different eye trackers running at four different speeds (60 Hz, 120 Hz, 150 Hz, and 300 Hz). This timing evaluation is performed in Visual Studio, Eclipse, and Atom IDEs. Results show that Deja Vu can playback 100% of the data recordings, correctly mapping the gaze to corresponding elements, making it a well-founded and suitable post processing step for future eye tracking studies in software engineering. Finally, a proof of concept replication analysis of four tasks from two previous studies is performed. Due to using the Deja Vu approach, this replication resulted in richer collected data and improved on the number of distinct syntactic categories that gaze was mapped on in the code.

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Studying Developer Reading Behavior on Stack Overflow during API Summarization Tasks

Cited by 8 publications

References 21 publications

Impact of Skim Reading Based on Different Screen Sizes

Impact of Skim Reading Based on Different Screen Sizes

Browsing to learn: How computer and software engineering students use online platforms in learning activities

Deja Vu: semantics-aware recording and replay of high-speed eye tracking and interaction data to support cognitive studies of software engineering tasks—methodology and analyses

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