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UNDERSTANDING SOFTWARE DEV
USING EQUATIONS
jacques@nreality.com
@jacdevos
Why this talk?
β€’ Hard!
β€’ Non-intuitive
β€’ Misunderstood
β€’ Seen as black-art done by amateurs
Software engineering is:
I’m not a mathematician
Mental models, rather than
precise calculations
Why do systems get so
complicated?
Handing complexity with
𝒏 𝒏 βˆ’ 𝟏
𝟐
10
1
2
34
5
𝒏 𝒏 βˆ’ 𝟏
𝟐
66
1
2
3
4
5
6
7
8
9
10
11
12
Complexity is caused by:
quadratic increase in
connections
How do we reduce complexity?
4
44 3
15!1
2
3
4
5
6
7
8
9
10
11
12
Org structure
or
Code structure?
Design reduces dependencies
Summary:
What is the effect of messy
code?
Go slow to go fast with
𝑻 𝒏 = 𝑢(𝒏)
0
50
100
150
200
250
300
10 20 30 40 50 60 70 80 90 100
TIME+RISKTOMAKECHANGE
FEATURES BUILT
CODE CHANGE COMPLEXITY
O(n) O(n2)
Clean Code gives
β€’ Easy to read
β€’ SOLID design
β€’ Boy scout refactoring
β€’ Self-testing
β€’ TDD
𝑢(𝒏)
Messy code gives
β€’ Manual regression testing
β€’ Spaghetti dependencies
β€’ Hart to understand
𝑢(𝒏 𝟐
)
Your algorithm of work
determines order of time
complexity
In summary
We’re so busy! Why don’t we get
stuff done?
Credit: http://www.autoevolution.com/
Maximise efficiency with
π‘­π’π’π’˜ = 𝑺𝒑𝒆𝒆𝒅 . π‘«π’†π’π’”π’Šπ’•π’š
π‘½π’†π’‰π’Šπ’„π’π’†π’”
𝑯𝒐𝒖𝒓
=
𝑴𝒆𝒕𝒆𝒓𝒔
𝑯𝒐𝒖𝒓
.
π‘½π’†π’‰π’Šπ’„π’π’†π’”
𝑴𝒆𝒕𝒆𝒓
youtu.be/Suugn-p5C1M
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
0
20
40
60
80
100
120
140
50 100 150 200 250 300 350 400 450 500
FLOWRATE(VEHICLES/HOUR)
SPEED(KILOMETER/HOUR)
DENSITY (VEHICLES/KILOMETER)
OPTIMAL FLOW
Speed (Km/h) Flow (Vehicles/h)
UnstableStable
Speed decreases as
density increases.
This is not intuitive.
Optimum flow at
speed 60 and
density 250.
Neither MAXED!
Speed = (1 – Density . JamDens) . MaxSpeed
How does this apply to software?
β€’ πΉπ‘™π‘œπ‘€ = 𝑆𝑝𝑒𝑒𝑑. 𝐷𝑒𝑛𝑠𝑖𝑑𝑦
β€’ Velocity = Throughput = Flow (avg # features delivered per week)
β€’ WIP = Density (avg # features started but not completed)
β€’ 𝐢𝑦𝑐𝑙𝑒 π‘‘π‘–π‘šπ‘’ =
1
𝑆𝑝𝑒𝑒𝑑
(avg time it takes to complete a feature)
β€’ π‘‡β„Žπ‘œπ‘’π‘”β„Žπ‘π‘’π‘‘ =
π‘ŠπΌπ‘ƒ
𝐢𝑦𝑐𝑙𝑒 π‘‡π‘–π‘šπ‘’
(aka Little’s Law)
π‘½π’†π’π’π’„π’Šπ’•π’š =
π‘¨π’—π’ˆ 𝒇𝒆𝒂𝒕𝒖𝒓𝒆𝒔 π’Šπ’ π’‘π’“π’π’ˆπ’“π’†π’”π’”
π‘¨π’—π’ˆ π’•π’Šπ’Žπ’† 𝒕𝒐 π’„π’π’Žπ’‘π’π’†π’•π’† 𝒂 𝒇𝒆𝒂𝒕𝒖𝒓𝒆
In summary
Improve continuously with
𝑨 = 𝑷𝒆 𝒓𝒕
http://jamesclear.com/marginal-gains
β€’ r = -1% per week (decay rate)
β€’ t = 104 weeks/2 years (time in weeks)
This gives us
β€’ 34% of original
β€’ Degraded 66% over 2 years!
Is this how technical debt behaves?
𝒆 𝒓𝒕
β€’ r = 1% per week (improvement rate)
β€’ t = 104 weeks/2 years (time in weeks)
This gives us
β€’ 294% improvement over 2 years!
π‘°π’Žπ’‘π’“π’π’—π’†π’Žπ’†π’π’• = 𝒆 𝒓𝒕
In summary
Simplify by removing dependencies
Go slow to go fast
Remove congestion to flow
Continuous improvement compounds
Other equations
β€’ Entropy
β€’ Bayesian Inference
β€’ The software engineering equation
β€’ Yours?
jacques@nreality.com
@jacdevos
DISCUSS.

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UNDERSTANDING SOFTWARE DEV WITH EQUATIONS

Editor's Notes

  1. Not an abstract theoretical construct.
  2. https://en.wikipedia.org/wiki/Metcalfe%27s_law
  3. Metcalfe's law – Net work
  4. Both!
  5. Note: things that change together
  6. Β Big O notation: the algorithm hasΒ order of n2Β time complexity Code change complexity/speed The way we work determines the difficulty in changes over time Don’t just optimise for short term Common trap: the way we work slows us down in the long term O(n2) - difficulty in building new feature safely if no test - O(logn) - the speed you can add new features if you don’t test or refactor. O(n) - can it scale? - apply to process, code, structure - SELF TEST GIVES O(n) - not test gives O(n2) We don’t have time to write tests. We need to get this out quickly! We can worry about quality later. Inspired by (but a different take on it): https://michaelfeathers.silvrback.com/code-change-complexity
  7. Credit : www.improvetraffic.org World’s largest traffic jam in Chine – 100km, 11 days
  8. Fundamental Relations of Traffic Flow https://www.civil.iitb.ac.in/tvm/1111_nptel/512_FundRel/plain/plain.html https://en.wikipedia.org/wiki/Fundamental_diagram_of_traffic_flow
  9. When density goes up – speed goes down
  10. When density goes up – speed goes down
  11. Also known as little's law
  12. Are we appreciating or depreciating Let’s start improving Common trap: we are too busy to improve https://www.youtube.com/watch?v=o5QRdHH8aeQ htps:/t/en.wikipedia.org/wiki/Compound_interest#Mathematics_of_interest_rates
  13. http://jamesclear.com/marginal-gains
  14. http://www.mathwarehouse.com/calculators/continuous-compound-interest-calculator.php
  15. http://www.mathwarehouse.com/calculators/continuous-compound-interest-calculator.php
  16. Are we appreciating or depreciating Let’s start improving Common trap: we are too busy to improve