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Web Usage Patterns of Developers

Christopher Corley
September 29, 2015
Research
1
69

Web Usage Patterns of Developers

Developers often rely on the web-based tools for
troubleshooting, collaboration, issue tracking, code reviewing,
documentation viewing, and a myriad of other uses. Developers
also use the web for non-development purposes, such as reading
news or social media. In this paper we explore whether web
usage is detriment to a developer’s focus on work from a sample
over 150 developers. Additionally, we investigate if highly-focused
developers use the web differently than other developers. Our
qualitative findings suggest highly-focused developers use the web
differently, but we are unable to predict a developer’s focused
based on web usage alone. Further quantitative findings suggest
that web usage does not have a negative impact on a developer’s
focus.

Christopher Corley

September 29, 2015
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Transcript

  1. Christopher S. Corley
    Web Usage Patterns
    of Developers
    Federico Lois, Sebastián F. Quezada
    ABB Corporate Research Corvalius
    Joint work with Corvalius on their userbase of their tool Codealike

    View Slide

  2. Does social media lead to interruptions or
    information overload that could impair a
    developer’s performance?
    We were looking to answer this question posed by Storey et al,
    and we extended it to a more general question.

    View Slide

  3. Does social media lead to interruptions or
    information overload that could impair a
    developer’s performance?
    Does web usage lead to interruptions that
    could impair a developer’s performance?
    We were looking to answer this question posed by Storey et al,
    and we extended it to a more general question.

    View Slide

  4. Personal Analytics for Developers
    - Had users from their tool, Codealike, Personal Analytics
    - Install plugins for your IDE & web browser — Codealike derives metrics from that information so that you can reflect on how your day or week went.
    - We had a sample of 168 users over a 4 month time period.
    !
    When talking about dev performance, we looked at a dev’s “focus”

    View Slide

  5. Focus features
    - Focus determined by level of activity in IDE
    - explain flow zone.
    - Here, for each user I had minute-by-minute focus level

    View Slide

  6. Web tracking features
    Useful for capturing time spent working on a project, but was reading documentation rather than working in IDE.
    >>> Manual classification: We generated 27 categories
    !
    Here, I had for each user hourly summaries of web browsing history.

    View Slide

  7. Web tracking features
    27 categories
    !
    18 categories with substantial time spent
    Useful for capturing time spent working on a project, but was reading documentation rather than working in IDE.
    >>> Manual classification: We generated 27 categories
    !
    Here, I had for each user hourly summaries of web browsing history.

    View Slide

  8. Table 1: Categories and total time tracked for each
    Category Total time tracked
    Blogs, News & Reading 49d 23h 57m
    Courses & Education 15d 6h 38m
    Developer Tools 10d 23h 4m
    Gaming 19d 5h 55m
    Informational 8d 8h 35m
    Internal 53d 4h 9m
    Localhost 88d 4h 36m
    Management Tools 7d 0h 46m
    Music & Videos 78d 1h 29m
    O ce Collaboration 26d 14h 50m
    O ce Tools 19d 4h 51m
    Quantified Self 14d 0h 13m
    SCM & ALM 86d 8h 54m
    Search Engines 49d 11h 54m
    Shopping 17d 2h 50m
    Social Networks 135d 0h 33m
    Troubleshooting 104d 22h 3m
    Webmail Clients 68d 19h 24m
    1
    To give you an idea on where developers spend time.
    !
    Social networks, Troubleshooting, SCM, Music, Localhost…

    View Slide

  9. Does web usage lead to interruptions that
    could impair a developer’s performance?
    Had the focus and web activity of 168 users.
    Data had to go through a bunch of transformations that shaped how I could go about answering the main Q.
    I only had minute by minute focus data, hour summary web usage data.
    But, using these two features, we can come up with a pretty interesting dataset and some subquestions

    View Slide

  10. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    Had the focus and web activity of 168 users.
    Data had to go through a bunch of transformations that shaped how I could go about answering the main Q.
    I only had minute by minute focus data, hour summary web usage data.
    But, using these two features, we can come up with a pretty interesting dataset and some subquestions

    View Slide

  11. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    2. Does web usage during coding
    sessions affect focus?
    Had the focus and web activity of 168 users.
    Data had to go through a bunch of transformations that shaped how I could go about answering the main Q.
    I only had minute by minute focus data, hour summary web usage data.
    But, using these two features, we can come up with a pretty interesting dataset and some subquestions

    View Slide

  12. To determine if a developer was “highly focused” or not, I split them up by their focus level information.
    !
    Taking the daily average number of minutes they were able to break the community average.
    Plotted: x-axis each user, y-axis that daily average.
    Upper quartile (right), gets around 2 hours per day above average. Some had over 4!
    Rest linear, felt good about quartiles

    View Slide

  13. Daily average of minutes with focus in “flow zone”
    To determine if a developer was “highly focused” or not, I split them up by their focus level information.
    !
    Taking the daily average number of minutes they were able to break the community average.
    Plotted: x-axis each user, y-axis that daily average.
    Upper quartile (right), gets around 2 hours per day above average. Some had over 4!
    Rest linear, felt good about quartiles

    View Slide

  14. 0 20 40 60 80 100 120 140 160 180
    User
    0
    50
    100
    150
    200
    250
    300
    focusRank
    Daily average of minutes with focus in “flow zone”
    To determine if a developer was “highly focused” or not, I split them up by their focus level information.
    !
    Taking the daily average number of minutes they were able to break the community average.
    Plotted: x-axis each user, y-axis that daily average.
    Upper quartile (right), gets around 2 hours per day above average. Some had over 4!
    Rest linear, felt good about quartiles

    View Slide

  15. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Weekly focus times
    1st quartile (high focus group)
    2nd quartile
    3rd quartile
    4th quartile (low focus group)
    Using these quartiles, I created heatmaps of the average developer’s week from that quartile.
    !
    High focus dev works 8-5, low focus dev doesn’t sleep?

    View Slide

  16. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Social Networks
    Focus
    75, 66, 85, 57 — 10
    !
    135 days

    View Slide

  17. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Office Collaboration
    Focus
    83, 44, 76, 67 — 61
    !
    26days

    View Slide

  18. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Webmail Clients
    Focus
    82, 76, 86, 64 — 38
    !
    68 days

    View Slide

  19. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    SCM & ALM
    Focus
    89, 79, 85, 66 — 73
    !
    86 days

    View Slide

  20. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Search Engines
    Focus
    90, 86, 92, 59 — 69
    !
    49 days

    View Slide

  21. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Troubleshooting
    Focus
    94, 92, 92, 55 — 86
    !
    104 days (second most tracked category)

    View Slide

  22. 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
    Monday
    Tuesday
    Wednesday
    Thursday
    Friday
    Saturday
    Sunday
    Music & Videos
    Focus
    41, 54, 57, 32 — 03
    !
    78 days

    View Slide

  23. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    !
    2. Does web usage during coding
    sessions affect focus?
    RQ1: answer seems like yes
    !
    To follow up RQ1 and into RQ2, let’s look at how focus correlates with each specific browsing activity

    View Slide

  24. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    !
    2. Does web usage during coding
    sessions affect focus?
    Yes
    RQ1: answer seems like yes
    !
    To follow up RQ1 and into RQ2, let’s look at how focus correlates with each specific browsing activity

    View Slide

  25. 1Q 2Q 3Q 4Q Overall
    Music & Videos
    Management Tools
    Localhost
    Internal
    Informational
    Gaming
    Developer Tools
    Courses & Education
    Blogs, News & Reading
    0.41 0.54 0.57 0.32 0.03
    -0.10 -1.00 0.08 -0.35 0.00
    0.87 0.84 0.87 0.64 0.72
    0.89 0.80 0.89 0.53 0.65
    0.38 0.28 0.43 0.03 0.00
    -0.03 0.07 -0.33 -0.01 -0.25
    0.69 0.55 0.70 0.42 0.53
    0.61 0.08 0.34 0.37 0.13
    0.61 0.56 0.82 0.45 0.24
    1Q 2Q
    Webmail Clients
    Troubleshooting
    Social Networks
    Shopping
    Search Engines
    SCM & ALM
    Quantified Self
    Office Tools
    Office Collaboration
    0.82 0.76 0
    0.94 0.92 0
    0.75 0.66 0
    0.59 0.25 0
    0.90 0.86 0
    0.89 0.79 0
    0.77 0.69 0
    0.67 0.56 0
    0.83 0.44 0
    −0.8
    −0.4
    0.0
    0.4
    0.8
    Here, each quartile is on X-axis, and each Category on Y-axis. The values are their Pearson’s correlation for times they were browsing & were working.
    !
    Gaming and Management tools negative — timesheets not conducive for work
    Blogs news and reading had some correlation — probably devs reading “blog post” documentation

    View Slide

  26. 3Q 4Q Overall
    0.57 0.32 0.03
    0.08 -0.35 0.00
    0.87 0.64 0.72
    0.89 0.53 0.65
    0.43 0.03 0.00
    -0.33 -0.01 -0.25
    0.70 0.42 0.53
    0.34 0.37 0.13
    0.82 0.45 0.24
    1Q 2Q 3Q 4Q Overall
    Webmail Clients
    Troubleshooting
    Social Networks
    Shopping
    Search Engines
    SCM & ALM
    Quantified Self
    Office Tools
    Office Collaboration
    0.82 0.76 0.86 0.64 0.38
    0.94 0.92 0.92 0.55 0.86
    0.75 0.66 0.85 0.57 0.10
    0.59 0.25 0.40 0.20 0.09
    0.90 0.86 0.92 0.59 0.69
    0.89 0.79 0.85 0.66 0.73
    0.77 0.69 0.79 0.48 0.58
    0.67 0.56 0.69 -0.11 0.46
    0.83 0.44 0.76 0.67 0.61
    −0.8
    −0.4
    0.0
    0.4
    0.8
    −0.8
    −0.4
    0.0
    0.4
    0.8
    Mostly all positive categories here.
    !
    Trouble shooting high, searching high. Don’t waste time, Google your problem!
    Shopping positive for some groups, which was a little surprising.
    !
    >>> Hard to tell whether web usage during work affects focus… so I did what any responsible researcher does!…

    View Slide

  27. Throw machine learning at it!
    Throw machine learning at it!
    !
    Used support vector machine.
    Created mapping of web usage activity => focus quartile.
    !
    Since SVMs are effective in high dimensional spaces, we create vectors of the total time spent in each category for every hour any developer is active.

    View Slide

  28. Throw machine learning at it!
    SVM prediction of web usage activity => user focus quartile
    Throw machine learning at it!
    !
    Used support vector machine.
    Created mapping of web usage activity => focus quartile.
    !
    Since SVMs are effective in high dimensional spaces, we create vectors of the total time spent in each category for every hour any developer is active.

    View Slide

  29. Throw machine learning at it!
    SVM prediction of web usage activity => user focus quartile
    36% accuracy
    Throw machine learning at it!
    !
    Used support vector machine.
    Created mapping of web usage activity => focus quartile.
    !
    Since SVMs are effective in high dimensional spaces, we create vectors of the total time spent in each category for every hour any developer is active.

    View Slide

  30. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    !
    2. Does web usage during coding
    sessions affect focus?
    RQ2: many categories were positively correlated, but we couldn’t build a predictor for it

    View Slide

  31. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    !
    2. Does web usage during coding
    sessions affect focus?
    Yes
    RQ2: many categories were positively correlated, but we couldn’t build a predictor for it

    View Slide

  32. Does web usage lead to interruptions that
    could impair a developer’s performance?
    1. Do highly-focused developers
    use the web differently than
    lesser-focused developers?
    !
    2. Does web usage during coding
    sessions affect focus?
    Yes
    Somewhat
    RQ2: many categories were positively correlated, but we couldn’t build a predictor for it

    View Slide

  33. Conclusion
    Highly-focused developers use the web differently
    !
    Web usage a factor for certain categories
    !
    Unable to predict focus with web usage alone
    1. search for the problem, find documentation
    2. avoid social media unless it’s for information foraging

    View Slide

  34. Christopher S. Corley
    Web Usage Patterns
    of Developers
    Federico Lois, Sebastián F. Quezada
    ABB Corporate Research Corvalius

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    61, 56, 82, 45 — 24

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    69, 55, 70, 42 — 53

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    38, 28, 43, 03 — 00

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    61, 08, 34, 37 — 13

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    -03, 07, -33, -01 — -25

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    Focus
    59, 25, 40, 20 — 09

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    Focus
    89, 80, 89, 53 — 65

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    Focus
    87, 84, 87, 64 — 72

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    Focus
    67, 56, 69, -11 — 46

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    Focus
    -10, -100, 08, -35 — 0

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    Focus
    77, 69, 79, 48 — 58

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