Seeing the forest for the trees, UMons 2011

download Seeing the forest for the trees, UMons 2011

of 37

  • date post

    17-Dec-2014
  • Category

    Education

  • view

    306
  • download

    0

Embed Size (px)

description

Slides used during the talk at UMons in November 2011.

Transcript of Seeing the forest for the trees, UMons 2011

  • 1. Seeing the forest for the trees Bogdan Vasilescu b.n.vasilescu@tue.nl http://www.win.tue.nl/bvasiles/ Software Engineering and Technology group Eindhoven University of TechnologyNovember 23, 2011
  • 2. Eindhoven 2/21/ department of mathematics and computer science
  • 3. Eindhoven 2/21/ department of mathematics and computer science
  • 4. Computer Science @TU/e 3/21/ department of mathematics and computer science
  • 5. Computer Science @TU/e 3/21 Section Model Driven Software Engineering (MDSE) Group Software Engineering and Technology (SET) Mark van den Brand Alexander Serebrenik/ department of mathematics and computer science
  • 6. Interested in . . . 4/21 Software evolution Aggregation of code metrics Activity in open-source projects Computational geometry/ department of mathematics and computer science
  • 7. Interested in . . . 4/21 Software evolution Aggregation of code metrics Activity in open-source projects Computational geometry/ department of mathematics and computer science
  • 8. Aggregation of software metrics 5/21 Maintaining a software system is like renovating a house. Maintainability assessment precedes changing the software. Metrics are often applied to measure maintainability. But metrics are dened at a low level (method, class). We need aggregation techniques./ department of mathematics and computer science
  • 9. Aggregation of software metrics 6/21/ department of mathematics and computer science
  • 10. Traditional aggregation techniques 7/21 Standard summary statistics: mean, median, . . . Red line mean; blue line median/ department of mathematics and computer science
  • 11. Recent trend: Inequality indices 8/21 Econometrics: measure/explain the inequality of income or wealth. Software metrics and econometric variables have distributions with similar shapes. Source Lines of Code: freecol0.9.4 Household income in Ilocos, Philippines (1998) 100 200 300 400 500 400 300 Frequency Frequency 200 100 0 0 0 500 1000 1500 2000 2500 3000 0 500000 1500000 2500000 SLOC per class Income/ department of mathematics and computer science
  • 12. Degree of concentration of functionality 9/21 Lorenz curve for SLOC in Hibernate 3.6.0-beta4. 1.0 0.8 0.6 % SLOC 0.4 0.2 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 % Classes/ department of mathematics and computer science
  • 13. Degree of concentration of functionality 9/21 Lorenz curve for SLOC in Hibernate 3.6.0-beta4. A 2A A+ B = I Gini = I Hoover A B/ department of mathematics and computer science
  • 14. Degree of concentration of functionality 9/21 Lorenz curve for SLOC in Hibernate Measure inequality between: 3.6.0-beta4. individuals (e.g., classes) A groups 2A A+ B = I Gini = (e.g., components) I Hoover Often desirable to assess the contribution of the inequality A between the groups. B Decomposable indices Root-cause analysis/ department of mathematics and computer science
  • 15. Traceability via decomposability 10/21 Which individuals (classes in package) contribute to 80% of the inequality (of SLOC)? Which class contributes the most to the inequality?/ department of mathematics and computer science
  • 16. Other properties of inequality indices 11/21 Symmetry Inequality stays the same for any permutation of the population./ department of mathematics and computer science
  • 17. Other properties of inequality indices 11/21 Symmetry Inequality stays the same for any permutation of the population./ department of mathematics and computer science
  • 18. Other properties of inequality indices 11/21 Symmetry Inequality stays the same for any permutation of the population./ department of mathematics and computer science
  • 19. Other properties of inequality indices 12/21 Population principle Inequality does not change if the population is replicated any number of times./ department of mathematics and computer science
  • 20. Other properties of inequality indices 12/21 Population principle Inequality does not change if the population is replicated any number of times./ department of mathematics and computer science
  • 21. Other properties of inequality indices 12/21 Population principle Inequality does not