A Practical Taxonomy of Bugs and How to Squash Them-SunshinePHP

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Catching software bugs is a mysterious magic, unknowable by science and untouchable by process.

False! Programming bugs, like real bugs, can be organized into a taxonomy. Come with me and I'll show you how classification can help you build “programmer’s instinct” into a logical debugging process.

Debugging may be instinctual but those instincts come from seeing, identifying and diagnosing patterns. In this talk, we’ll use phenetic taxonomy to build a debugging decision making network based on attributes and behaviors of common bugs. Newer developers will learn how to apply systematic pattern matching to debugging while seasoned developers will learn how to use their instincts to teach debugging.

Transcript

1. A PRACTICAL TAXONOMY OF BUGS AND HOW TO SQUASH THEM https://joind.in/talk/3f670
2. Instinctual Indications…6 Research Methods…9 Practical Taxonomy…13 Bohrbug…17 Schrödinbug…25 Fractalbug…24 Heisenbug…35 Mandelbug…44 Resources…55 Table of Contents
3. Debugging Skills
4. “As you familiarize yourself with the application, you’ll build up some debugging instincts"
5. “Whenever I see something like this happening, the first thing I do is scan the logs to see if this process is completing or is sending a weird message.”
7. Debugging Instincts “ ”
10. “Whenever I see #{x}, I always check #{y}”
11. Instincts are just internalized rulesets
12. Research Methods • containment sometimes takes priority over squashing • we can only work with facts • we can’t squash every bug in this talk
13. Observable Attributes
14. Phenetics { ]
15. Warning: Contrived Scenarios Ahead
16. A PRACTICAL TAXONOMY OF BUGS AND HOW TO SQUASH THEM
17. A Practical Taxonomy of Bugs Upsettingly Observable Wildly Chaotic {
18. Upsettingly Observable Bugs
19. Wildly Chaotic Bugs
20. How to Squash Them
21. upsettingly observable bug #1 UPSETTINGLY OBSERVABLE
22. Observable Attributes is the bug observable in production?
23. Observable Attributes is the bug observable in production? can it be reproduced locally?
24. Observable Attributes is the bug observable in production? can it be reproduced locally? does it seem to be restricted to one area?
25. Bohrbug deterministic, highly reproducible UPSETTINGLY OBSERVABLE
26. Bohrbug Commonly found in code,sometimes on server UPSETTINGLY OBSERVABLE
27. Bohrbug likes to hide in complex branching in functions, classes or config UPSETTINGLY OBSERVABLE
28. Bohrbug In the wild: validation UPSETTINGLY OBSERVABLE
29. Bohrbug UPSETTINGLY OBSERVABLE Easy to squash
30. Reproduction & Resolution replicate locally and in test UPSETTINGLY OBSERVABLE
31. Reproduction & Resolution replicate locally and in test write the simple solution UPSETTINGLY OBSERVABLE
32. Reproduction & Resolution replicate locally and in test write the simple solution rewrite to be highly readable and extendable UPSETTINGLY OBSERVABLE
33. Bohrbug UPSETTINGLY OBSERVABLE
34. upsettingly observable bug #2 UPSETTINGLY OBSERVABLE
35. Observable Attributes how does this work?
36. Observable Attributes how does this work? does this work?
37. Observable Attributes how does this work? does this work? wait, what is this even testing?
38. Observable Attributes how does this work? does this work? wait, what is this even testing? did this ever work?
39. Schrödinbug stick-like body appendages look like twigs UPSETTINGLY OBSERVABLE
40. Schrödinbug Likes to pretend to be working code. On close inspection, reveals itself to be a bug. UPSETTINGLY OBSERVABLE
41. Schrödinbug UPSETTINGLY OBSERVABLE Type I. Type II.
42. Schrödinbug Type I. Code that never worked UPSETTINGLY OBSERVABLE
43. Schrödinbug Type I. Reveal themselves via side-effects UPSETTINGLY OBSERVABLE
44. Schrödinbug Type I. In the wild: UI shows update but database entry not updated. UPSETTINGLY OBSERVABLE
45. Schrödinbug Type II. Code that doesn’t work how you thought UPSETTINGLY OBSERVABLE
46. Schrödinbug Type II. In the wild: Same function being called multiple times UPSETTINGLY OBSERVABLE
47. Basic Reproduction & Resolution replicate locally and in test write the simple solution rewrite to be highly readable and extendable UPSETTINGLY OBSERVABLE
48. -You “How can I reproduce this without knowing exactly what is happening?”
49. Logging as Verification Tool
50. Git Bisect Tool
51. Reproduction & Resolution reproduce the “broken” state locally and in test
52. Reproduction & Resolution reproduce the “broken” state locally and in test add log statements until you can verify what causes the broken state.
53. Reproduction & Resolution reproduce the “broken” state locally and in test add log statements until you can verify what causes the broken state. if the bug did work at some point, find the point at which it did work.
54. Reproduction & Resolution reproduce the “broken” state locally and in test add log statements until you can verify what causes the broken state. if the bug did work at some point, find the point at which it did work. write tests to represent the configuration and flow of the fixed state
55. Schrödinbug UPSETTINGLY OBSERVABLE
56. wildly chaotic bug #1 WILDLY CHAOTIC
57. Observable Attributes Does it appear non-deterministic?
58. Observable Attributes Does it appear non-deterministic? Does it seem to disappear once you observe or debug it?
59. Heisenbug “now you see it, now you don’t” WILDLY CHAOTIC
60. Heisenbug WILDLY CHAOTIC Type I. Type II.
61. Heisenbug Type I. WILDLY CHAOTIC Lives in code
62. Heisenbug Type II. WILDLY CHAOTIC Lives in data
63. -You “How can I reproduce this without testing on production?”
64. Profiling for Verification https://kcachegrind.github.io/html/CallgrindFormat.html Tool
65. FLAME GRAPHS http://www.brendangregg.com/FlameGraphs/cpu-mysql-updated.svg Tool
66. Reproduction & Resolution use profiling to find the trigger state
67. Reproduction & Resolution use profiling to find the trigger state use the app (not fixtures or DB manipulation) to get the data in this state
68. Reproduction & Resolution use profiling to find the trigger state use the app (not fixtures or DB manipulation) to get the data in this state recreate that state in test
69. Reproduction & Resolution use profiling to find the trigger state use the app (not fixtures or DB manipulation) to get the data in this state recreate that state in test follow borhbug instruction
70. Heisenbug WILDLY CHAOTIC
71. wildly chaotic bug #2 WILDLY CHAOTIC
72. Observable Attributes is everything broken?
73. Observable Attributes is everything broken? all of it?
74. Observable Attributes is everything broken? all of it? send help??
75. Mandelbug WILDLY CHAOTIC
76. Mandelbug seems like everything is broken at once WILDLY CHAOTIC
77. Mandelbug people are very upset with you WILDLY CHAOTIC
78. Mandelbug likely an issue with your system, not code WILDLY CHAOTIC
79. “The bug is huge and everywhere at once. SQL: could not connect to server: Connection refused was bubbling up all over the place. Jobs won’t run, emails won’t send, every submit button on the site fatal errored.” on-call log WILDLY CHAOTIC
80. Disk Usage Tool df -h
81. Logging as Verification Tool
82. Reproduction & Resolution use df -h to find if all the storage is being use
83. Reproduction & Resolution use df -h to find if all the storage is being use attempt to connect to server & view logs
84. Reproduction & Resolution use df -h to find if all the storage is being used attempt to connect to server & view logs can that be restarted, rotated or killed at this time?
85. Mandelbug WILDLY CHAOTIC
86. A Practical Taxonomy of Bugs Upsettingly Observable Wildly Chaotic { bohrbug schrödinbug mandelbug heisenbug
87. “Debugging Instincts”
88. Debugging Skills
89. Observe & Classify
90. Verify with logging and time travel
91. Verify without changing state by profiling
92. Use server tools to observe entire process
93. Observe & Classify Verify with logging and time travel Verify without changing state by profiling Use server tools to observe entire process
94. Build Up Your Own Toolkit and Share it
95. Resources & Further Study • “Linux Debugging Tools I Love”, Julia Evans • Systems Performance, Brendan Gregg • “Why Do Computers Stop and What Can Be Done About It?”, Jim Gray • “Debug Patterns for Efficient High- levelSystemC Debugging”, Frank Rogin, Erhard Fehlauer, Christian Haufe, Sebastian Ohnewald
96. https://joind.in/talk/3f670