Seven principles of inductive software engineering: What we do is different

Seven principles of inductive software engineering: What we do is different

1. DIFFERENT AND IMPORTANT

   • Inductive software engineering is data-mining based on software applications
     • The core problem is the extraction of small patterns from larger data sets

2. PRINCIPLES

   • HUMANS BEFORE ALGORITHMS
     • Understandable results and understand that those results add value to their work.
     • DEVELOP A BROAD SKILL SET THAT USES A BIG TOOLKIT
       • inductive engineers come equipped with a very broad range of tools
   • PLAN FOR SCALE
     • The way it started was not the way it ended
     • The team size doubled at each stage -- it can be increasingly expensive and lose the control of the knowledge.
   • GET EARLY FEEDBACK
     • Take a long time to reach a conclusion
     • Apply simple tools to gain early feedback
     • SIMPLICITY FIRST!
   • BE SMART WITH YOUR LEARNING
     • BE OPEN MINDED
       • Avoid a fixed hypothesis
       • Avoid a fixed approach for data mining
     • LIVE WITH THE DATA YOU HAVE
       • mining with the data you have and not the data you hope to have
     • It also true that any inductive agent (and this includes you) can make mistakes.