Towards Understanding Interactive Debugging

1. Towards Understanding
Interactive Debugging
Fabio Petrillo ∗† , Zéphyrin Soh † , Foutse Khomh † , Marcelo Pimenta∗ ,
Carla Freitas∗ , Yann-Gaël Guéhéneuc †
∗ Federal University of Rio Grande do Sul, RS, Brazil
École Polytechnique de Montréal, QC, Canada
IEEE International Conference on Software Quality, Reliability and Security (QRS’2016)

2. Is debugging important?
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3. Is debugging important?
Developers spend over two-thirds of their time (68%) investigating
code, and the majority of this time is spent debugging
code (33%) [LaToza 2010].
LaToza, T. D., & Myers, B. a. (2010). Developers ask reachability questions. 2010 ACM/IEEE 32nd
International Conference on Software Engineering, 1, 185–194.
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4. During debugging, a lonely developer
navigates the source code
steps into many statements
traverses dozens of method invocations
gains understanding about the system.
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5. if interactive debugging is important to create
knowledge about a software project,
why is this human knowledge lost?
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6. Can we collect and share
debugging session information?
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7. Our approach
Swarm Debugging
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8. 8

9. 9

10. Our implementation
Swarm Debug
Infrastructure
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11. Swarm Debug Infrastructure (SDI) is an open-
source infrastructure which allows
practitioners and researchers to collect and
share fine-grained data about developers’
interactive debugging activities.
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12. Infrastructure
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13. Architecture
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14. Metadata
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18. 18

19. Experimental
Study
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20. Experiment design
● 5 professional freelancers and 2 students
● Warm-up task
● 5 bug location tasks
● Open source project: JabRef 3.2
● 19 bug location sessions
● about 6 hours of effective of video recording
● 110 breakpoints and ~ 7000 invocations
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21. Results
3 RQs
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22. RQ1: Is there a correlation between the numbers of
invocations or toggled breakpoints and tasks’ elapsed
time?
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23. 23

24. RQ1: Is there a correlation between the numbers of
invocations or toggled breakpoints and tasks’ elapsed
time?
There is no correlation(ρ = −0.039, 0.093) between
the number of invocations(respectively the number
of breakpointstoggled) during a debugging session
and the spent time on the debugging task
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25. RQ2: Do developers explore/debug in different ways a
task?
● we observed two distinct debugging navigation patterns:
● fuzzydebugging pattern (several branches)
● straightdebugging pattern
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26. Fuzzy pattern
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27. 27

28. Straight pattern
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29. 29

30. RQ3: Is there a correlation between time of first
breakpoint and task’s elapsed time?
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31. RQ3: Is there a correlation between time of first
breakpoint and task’s elapsed time?
● there is a strong correlation (ρ = −0.637)
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32. RQ3: Is there a correlation between time of first
breakpoint and task’s elapsed time?
● there is a strong correlation (ρ = −0.637)
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33. 33

34. whether developers toggle
breakpoints carefully, they
complete tasks faster than
developers who toggle breakpoints
too quickly 34

35. ● Swam Debugging is an approach uses Swarm Intelligence and Information
Foraging Theory to provide knowledge from interactive debugging session
information
● There is a lot to investigate about interactive debugging phenomena!
● Swarm Debug Infrastructure (SDI) provides an infrastructure to create tools for
context-aware debugging
● Developers follow different debugging patterns
● When developers toggle breakpoints carefully, they complete tasks faster than
developers who toggle breakpoints too quickly
● There is a lot of investigating about interactive debugging phenomena!
Final Remarks
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36. ● It is free/open source and open research data
○ https://github.com/SwarmDebugging
○ http://server.swarmdebugging.org/
Swarm Debug Infrastructure is Free!
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37. Do you like work with
these data?
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38. Do you like work with
these data?
Go ahead!
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39. Towards Understanding
Interactive Debugging
IEEE International Conference on Software Quality, Reliability and Security (QRS’2016)
Thank you!
@petrillofabio
fabio@petrillo.com