Best Practices for Scientific Computing

I reproduce here below principles from the amazing paper Best Practices for Scientific Computing, published on 2012 by a group of US and UK professors. The main purpose of the paper is to “teach”  good programming habits shared from professional developers to people  that weren’t born developer, and became developers just for professional purposes.

Scientists spend an increasing amount of time building and using software. However, most scientists are never taught how to do this efficiently

1. Write programs for people, not computers.

   1. a program should not require its readers to hold more than a handful of facts in memory at once
   2. names should be consistent, distinctive and meaningful
   3. code style and formatting should be consistent
   4. all aspects of software development should be broken down into tasks roughly an hour long

2. Automate repetitive tasks.

   1. rely on the computer to repeat tasks
   2. save recent commands in a file for re-use
   3. use a build tool to automate scientific workflows

3. Use the computer to record history.

   1. software tools should be  used to track computational work automatically

4. Make incremental changes.

   1. work in small steps with frequent feedback and course correction

5. Use version control.

   1. use a version control system
   2. everything that has been created manually should be put in version control

6. Don’t repeat yourself (or others).

   1. every piece of data must have a single authoritative representation in the system
   2. code should be modularized rather than copied and pasted
   3. re-use code instead of rewriting it

7. Plan for mistakes.

   1. add assertions to programs to check their operation
   2. use an off-the-shelf unit testing library
   3. use all available oracles when testing programs
   4. turn bugs into test cases
   5. use a symbolic debugger

8. Optimize software only after it works correctly.

   1. use a profiler to identify bottlenecks
   2. write code in the highest-level language possible

9. Document design and purpose, not mechanics.

   1. document interfaces and reasons, not implementations
   2. refactor code instead of explaining how it works
   3. embed the documentation for a piece of software in that software

10. Collaborate.

    1. use pre-merge code reviews
    2. use pair programming when bringing someone new up to speed and when tackling particularly tricky problems

if you want to discover more, you can download your copy of Best Practice Scientific Computing here below

donwload a copy of Best Practices for Scientific Computing

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