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The Evolution of Developer Work Rhythms

An Analysis Using Signal Processing Techniques

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Social Informatics (SocInfo 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11185))

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Abstract

We study the evolution of the work rhythms of software developers. We gather datasets and controls from GitHub, a prominent site among developers, and, with the help of signal processing techniques, we observe two temporal phenomena in the daily patterns (waveforms) related to daily work rhythms: regularization and precession. More regular daily work patterns, and earlier-in-the-day work patterns both appear in parallel to developers spending time in GitHub.

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Notes

  1. 1.

    https://developer.github.com/v3/.

  2. 2.

    For each time step n, a logical OR between sequences \((M_{n}^{p})_{p\in Q}\) is applied.

  3. 3.

    http://pilot.cnxproject.org/content/collection/col10064/latest/module/m34847/latest.

  4. 4.

    https://ccrma.stanford.edu/~jos/mdft/Spectrograms.html.

  5. 5.

    https://ccrma.stanford.edu/~jos/sasp/Hamming_Window.html.

  6. 6.

    There are 144 periods of 10 min in one day and 1008 in one week.

  7. 7.

    Given by: \(\frac{1}{144}\sum \limits _{n=0}^{143} (D_{Z,n}^{Q})^{2}\).

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Traullé, B., Dalle, JM. (2018). The Evolution of Developer Work Rhythms. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11185. Springer, Cham. https://doi.org/10.1007/978-3-030-01129-1_26

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  • DOI: https://doi.org/10.1007/978-3-030-01129-1_26

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