Paradoxes and theorems every developer should know

Paradoxes and theorems every developer should know

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Joshua Thijssen

October 09, 2016
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  1. 9.

    @jaytaph 8 Intelligence Statistics Actual June 1940 1000 169 June

    1941 1550 244 August 1942 1550 327 https://en.wikipedia.org/wiki/German_tank_problem
  2. 10.

    @jaytaph 8 Intelligence Statistics Actual June 1940 1000 169 June

    1941 1550 244 August 1942 1550 327 https://en.wikipedia.org/wiki/German_tank_problem 122
  3. 11.

    @jaytaph 8 Intelligence Statistics Actual June 1940 1000 169 June

    1941 1550 244 August 1942 1550 327 https://en.wikipedia.org/wiki/German_tank_problem 122 271
  4. 12.

    @jaytaph 8 Intelligence Statistics Actual June 1940 1000 169 June

    1941 1550 244 August 1942 1550 327 https://en.wikipedia.org/wiki/German_tank_problem 122 271 342
  5. 16.

    @jaytaph 9 ➡ Data leakage. ➡ User-id's, invoice-id's, etc ➡

    Used to approximate the number of iPhones sold in 2008.
  6. 17.

    @jaytaph 10 Monthly Invoice IDs Monthly Invoice IDs Monthly Invoice

    IDs Monthly Invoice IDs Jan 2476 2303 Feb 10718 14891 Mar 19413 27858 Apr 28833 41458 May 38644 55429 Jun 48633 55429 Jul 102606 59027 84961 Aug 109331 69715 100308 Sep 116388 80684 116020 Oct 123721 91935 132004 Nov 131241 103455 148341 Dec 139236 115276 164976
  7. 18.

    @jaytaph 11 Monthly Invoice IDs Monthly Invoice IDs Monthly Invoice

    IDs Monthly Invoice IDs Jan 2476 2303 Feb 10718 14891 Mar 19413 27858 Apr 28833 41458 May 38644 55429 Jun 48633 55429 Jul 102606 59027 84961 Aug 109331 69715 100308 Sep 116388 80684 116020 Oct 123721 91935 132004 Nov 131241 103455 148341 Dec 139236 115276 164976 Estimated subscriptions Estimated subscriptions Estimated subscriptions Estimated subscriptions Jan Feb 8242 12588 Mar 8695 12967 Apr 9420 13600 May 9811 13971 Jun 9989 14525 Jul 10394 15007 Aug 6725 10688 15347 Sep 7057 10969 15712 Oct 7333 11251 15984 Nov 7520 11520 16337 Dec 7995 11821 16635
  8. 19.

    @jaytaph 12 Monthly Invoice IDs Monthly Invoice IDs Monthly Invoice

    IDs Monthly Invoice IDs Jan 2476 2303 Feb 10718 14891 Mar 19413 27858 Apr 28833 41458 May 38644 55429 Jun 48633 55429 Jul 102606 59027 84961 Aug 109331 69715 100308 Sep 116388 80684 116020 Oct 123721 91935 132004 Nov 131241 103455 148341 Dec 139236 115276 164976 Estimated growth / size Estimated growth / size Estimated growth / size Estimated growth / size Jan Feb Mar 105% 103% Apr 108% 105% May 104% 103% Jun 102% 104% Jul 104% 103% Aug 103% 102% Sep 105% 103% 102% Oct 104% 103% 102% Nov 103% 102% 102% Dec 106% 103% 102%
  9. 20.

    @jaytaph ➡ Avoid (semi) sequential data to be leaked. ➡

    Adding randomness and offsets will NOT solve the issue. ➡ Use UUIDs (better: timebased short IDs, you don't need UUIDs) 13
  10. 28.

    @jaytaph 21 5 8 ? ? If a card shows

    an even number on one face, then its opposite face must be blue.
  11. 30.

    @jaytaph 23 coke beer 35 17 If you drink beer

    then you must be 18 yrs or older.
  12. 31.

    @jaytaph 23 coke beer 35 17 If you drink beer

    then you must be 18 yrs or older.
  13. 32.

    @jaytaph 23 coke beer 35 17 If you drink beer

    then you must be 18 yrs or older.
  14. 35.

    @jaytaph 26 5 8 ? ? If a card shows

    an even number on one face, then its opposite face must be blue.
  15. 36.

    @jaytaph 26 5 8 ? ? If a card shows

    an even number on one face, then its opposite face must be blue.
  16. 37.

    @jaytaph 26 5 8 ? ? If a card shows

    an even number on one face, then its opposite face must be blue.
  17. 39.

    @jaytaph Question: 28 > 50% chance 4 march 18 september

    5 december 25 juli 2 februari 9 october
  18. 46.

    @jaytaph Watch out for: 35 ➡ Too small hashes. ➡

    Unique data. ➡ Your data might be less "protected" as you might think.
  19. 50.

    @jaytaph 39 x position p momentum (mass x velocity) ħ

    0.0000000000000000000000000000000001054571800 (1.054571800E-34)
  20. 59.

    @jaytaph find . -name \*.php -exec wc -l {} \;

    | sort | cut -b 1 | uniq -c 48
  21. 60.

    @jaytaph find . -name \*.php -exec wc -l {} \;

    | sort | cut -b 1 | uniq -c 48 1073 1 886 2 636 3 372 4 352 5 350 6 307 7 247 8 222 9
  22. 63.
  23. 64.

    @jaytaph What is the chance that a message is spam

    when it contains certain words? 52
  24. 65.

    @jaytaph 53 P(A|B) P(A) P(B) P(B|A) Probability event A, if

    event B (conditional) Probability event A Probability event B Probability event B, if event A
  25. 66.

    @jaytaph 54 ➡ Figure out the probability a {mail, tweet,

    comment, review} is {spam, negative} etc.
  26. 67.

    @jaytaph ➡ 10 out of 50 comments are "negative". ➡

    25 out of 50 comments uses the word "horrible". ➡ 8 comments with the word "horrible" are marked as "negative". 55
  27. 70.

    @jaytaph 58 "Your product is horrible and does not work

    properly. Also, you suck." "I had a horrible experience with another product. But yours really worked well. Thank you!" Negative: Positive:
  28. 72.

    @jaytaph 60 Find me on twitter: @jaytaph Find me for

    development and training: www.noxlogic.nl / www.techademy.nl Find me on email: jthijssen@noxlogic.nl Find me for blogs: www.adayinthelifeof.nl