Metaphors We Compute By

We think in words, we talk with words, we understand the world thanks to words. Metaphors take words to the next level explaining concepts that were escaping our understanding before. In 1980 George Lakoff revolutionised the Linguistic and Philosophic worlds when he studied how metaphors affect our thinking, how they influence our actions and even shape who we are. What happens with the metaphors that we use in the Software Industry?

In this talk we are going to review the importance that metaphors have in our code quality, in the algorithms we choose, and the products we ship.

As a practical example we are going to see why Microservices and Containers have been so successful in the past couple of years. We’ll try to understand why they have redefined how we package and ship products in our industry.

Transcript

1. METAPHORS WE COMPUTE BY ALVARO VIDELA - @old_sound
2. THE YEAR IS 1980
3. METAPHORS WE LIVE BY GEORGE LAKOFF & MARK JOHNSON
4. METAPHOR ISN’T JUST A MATTER OF POETRY AND RHETORICAL FLOURISH
5. METAPHORS PERMEATE ALL AREAS OF OUR LIVES METAPHORS DICTATE
6. METAPHORS PERMEATE ALL AREAS OF OUR LIVES METAPHORS DICTATE ▸ How we think
7. METAPHORS PERMEATE ALL AREAS OF OUR LIVES METAPHORS DICTATE ▸ How we think ▸ How we behave
8. METAPHORS PERMEATE ALL AREAS OF OUR LIVES METAPHORS DICTATE ▸ How we think ▸ How we behave ▸ How we perceive
9. METAPHORS PERMEATE ALL AREAS OF OUR LIVES METAPHORS DICTATE ▸ How we think ▸ How we behave ▸ How we perceive ▸ How our conceptual system is built
10. ARGUMENT IS WAR
11. METAPHORS IN EVERYDAY EXPRESSIONS ARGUMENT IS WAR
12. METAPHORS IN EVERYDAY EXPRESSIONS ARGUMENT IS WAR ▸ Your claims are indefensible
13. METAPHORS IN EVERYDAY EXPRESSIONS ARGUMENT IS WAR ▸ Your claims are indefensible ▸ He attacked every weak point in my argument
14. METAPHORS IN EVERYDAY EXPRESSIONS ARGUMENT IS WAR ▸ Your claims are indefensible ▸ He attacked every weak point in my argument ▸ I demolished his argument
15. METAPHORS IN EVERYDAY EXPRESSIONS ARGUMENT IS WAR ▸ Your claims are indefensible ▸ He attacked every weak point in my argument ▸ I demolished his argument ▸ I never won an argument with him
16. METAPHORS IN EVERYDAY EXPRESSIONS ARGUMENT IS WAR ▸ Your claims are indefensible ▸ He attacked every weak point in my argument ▸ I demolished his argument ▸ I never won an argument with him ▸ His criticisms were right on target
17. WHAT IF ARGUMENT IS A DANCE?
18. I’M NOT CONVINCED
19. LET’S TALK ABOUT POLITICS
20. I’M STILL NOT CONVINCED
21. HUMAN RESOURCE MANAGEMENT
22. PEOPLE ARE NOT RESOURCES
23. TRIGGER WARNING
24. GIVING A PLATFORM TO RACISTS
25. “WRESTLING WITH INCLUSION AT XYZCONF”
26. “WRESTLING WITH INCLUSION AT XYZCONF”
27. LET’S TALK ABOUT COMPUTERS
29. COMPUTERS
30. METAPHORS ENABLE UNDERSTANDING
31. JULIET IS LIKE THE SUN
32. JULIET GAVE ME SKIN CANCER
33. METAPHORS OBSCURE UNDERSTANDING
34. TELE-GRAPH
35. “SOMETIMES OUR TOOLS DO WHAT WE TELL THEM TO. OTHER TIMES, WE ADAPT OURSELVES TO OUR TOOLS' REQUIREMENTS” Nicholas Carr THE SHALLOWS
36. METAPHORS ARE THE TOOLS OF THOUGHT
37. METAPHORS AND CODE
39. BEST UNKNOWN PAPER
40. “TO PROGRAM IS TO WRITE TO ANOTHER PROGRAMMER ABOUT OUR SOLUTION TO A PROBLEM” Charles Baker A PROGRAMER’S ROLE
41. “NO ONE HAS SEEN A PROGRAM WHICH THE MACHINE COULD NOT COMPREHEND BUT WHICH HUMANS DID” Charles Baker A PROGRAMER’S ROLE
42. TYPES ARE THE CHARACTERS THAT TELL THE STORY OF OUR PROGRAMS
43. PROGRAMMING WITH ABSTRACT DATA TYPES
44. WITHOUT TYPES WE JUST HAVE OPERATIONS ON STREAM OF BYTES
45. CHOOSING THE RIGHT DATA STRUCTURE
46. CHOOSE THE RIGHT DATA STRUCTURE
47. CHOOSE THE RIGHT DATA STRUCTURE ▸ Array
48. CHOOSE THE RIGHT DATA STRUCTURE ▸ Array ▸ Set
49. CHOOSE THE RIGHT DATA STRUCTURE ▸ Array ▸ Set ▸ LinkedList
50. CHOOSE THE RIGHT DATA STRUCTURE ▸ Array ▸ Set ▸ LinkedList ▸ Queue
51. CHOOSE THE RIGHT DATA STRUCTURE ▸ Array ▸ Set ▸ LinkedList ▸ Queue ▸ Stack
52. A PROGRAM’S EXPLANATORY POWER IS THE MEASURE OF ITS OWN ELEGANCE
53. DATA STRUCTURES HAVE EXPLANATORY POWER
54. COGNITIVE LEAPS
55. TASK SCHEDULING
56. QUEUEING THEORY TASK SCHEDULING
57. ROUTE PLANNING
58. GRAPH THEORY ROUTE PLANNING
59. DATABASE REPLICATION
60. RUMOUR MONGERING DATABASE REPLICATION
61. EPIDEMICS DATABASE REPLICATION
62. SO EVERYTHING IS A METAPHOR?
63. I DON’T BELIEVE YOU
64. Whenever nodes need to agree on a common value, we start a consensus algorithm to decide on a value. There's usually a leader process that takes care of making the final decision based on the votes it has received from its peers. SEVEN METAPHORS DISTRIBUTED SYSTEMS METAPHORS
65. SEVEN METAPHORS DISTRIBUTED SYSTEMS METAPHORS Nodes communicate sending messages over a channel, which might get congested due to too much traffic. This could create an information bottleneck, with queues at each end of the channels backing up.
66. FOUR METAPHORS DISTRIBUTED SYSTEMS METAPHORS These bottlenecks might render one or more nodes unresponsive, causing network partitions. Is the process that's taking too long to respond dead? We won't know unless we set a timeout…
67. INTERMEZZO
68. PACKAGING
70. BUILDING GHC
72. CONTAINERS ▸ Standard ▸ Ship Anywhere ▸ Train, Ships, Trucks ▸ Stackable ▸ Reusable
74. MICROSERVICES
75. MICROSERVICES ▸ Decentralised Governance ▸ Monolith vs. Microservice ▸ Isolation ▸ Collaboration ▸ Small is better - Big is cumbersome ▸ David vs. Goliath
76. BRING POWER BACK TO THE DEVELOPER AND THE DEVELOPER WILL MAKE YOU A KING
77. ERLANG ANYONE?
78. “IN ANOTHER DIRECTION, ONE COULD ARGUE THAT MICROSERVICES ARE THE SAME THING AS THE ERLANG PROGRAMMING MODEL, BUT APPLIED TO AN ENTERPRISE APPLICATION CONTEXT”
79. WHAT’S ERLANG’S ELEVATOR PITCH?
80. MASTER THE ART OF METAPHOR SELECTION
81. FIRST GET PEOPLE TO UNDERSTAND THINGS
82. THEN EXPLAIN HOW THINGS ACTUALLY WORK
83. RABBITMQ A JOB SERVER?
84. MASTER THE ART OF MEANING AMPLIFICATION
85. OUR PROGRAM IS THE METAPHOR FOR THE SOLUTION WE FOUND
86. REFERENCES ▸ Lakoff, George, and Mark Johnson. “Metaphors We Live By” ▸ Gleick, James. “The Information: A History, a Theory, a Flood” ▸ Geary, James. “I Is an Other: The Secret Life of Metaphor and How It Shapes the Way We See the World” ▸ Demers, Alan, Dan Greene, Carl Hauser, Wes Irish, and John Larson. “Epidemic Algorithms for Replicated Database Maintenance”
87. CREDITS - CC BY-NC-ND ▸ Office Workers: https://flic.kr/p/5WwpeV ▸ Sun: https://flic.kr/p/9Q6SY1 ▸ Queue: https://flic.kr/p/8AqWW7 ▸ Consensus: https://flic.kr/p/aws7dH ▸ Bottlenecks: https://flic.kr/p/EJ5Q3 ▸ Gossip: https://flic.kr/p/4bCDr2 ▸ Containers: https://flic.kr/p/nWLQxE
88. @old_sound THANK YOU!