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Presented by Smitha Thumbikkat and Milan Chandrahasn, Collabera Solutions at the Best Practices Sharing Event in 2012 conducted by the Computer Society of India held,in Bangalore
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Smitha T, Milan C
Collabera Solutions
Bangalore
A New Paradigm in Software Quality
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Fundamental challenge - measurability
Pe
op
le
E n g i n e e r i n g
Genrich Altshuller scanned 400,000 patent descriptions, and found that only 2% were really new. This means, 98% of all new problems can be solved using previous experience/learning(s).
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Industrial Revolution
1913
1955
1976
Requirements structure
Test case adequacy Code
structure
Structural application profile
“. . . .Yo u r h a n d s c a n ’ t
h i t w h a t yo u r e ye s
c a n ’ t s e e … . .”
M u h a m m a d A l i
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Requirements Architecture Design & Coding
Unit Testing System
/Functional Testing
Requirements & Architecture
Baseline Continuous Integration & Iteration Releases
T y p i c a l L i f e c y c l e i n C o l l a b e r a
Can ‘defect prone’ tendency be isolated? 9
Cyclomatic complexity
%Branch Statements
Depth of Inheritance
Calls/method
Methods / Class
Class Coupling
Maintainability Index Boolean Expression
complexity
Class Data Abstraction coupling
Class Fan Out Complexity
Npath Complexity
Java NCSS
% comment Lines Density of comment lines
Public undocumented API
Duplicated lines
Duplicated blocks
Number of children
Afferent couplings
Lack of cohesion methods
Package dependencies to cut
Violations
Complexity distribution by method
Complexity distribution by class
File dependencies to cut
The problem of plenty…
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II
B r i d g i n g t h e e a g l e ’ s e y e a n d w o r m ’ s v i e w Slide 11
% Branches Block Depth
Cyclomatic Complexity
Correlating SIT with engineering metrics
% Branches Block Depth
Max Cyclomatic Complexity
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Influence of complexity attribute
Composite parameter analysis
92%
4%
2% 1% 1%
Number of Class vs SIT defects
8% of classes is contributing to 100% of SIT defects
Study from European university
Key parameters measured
Cyclomatic complexity/LOC No. of methods/class No. of Calls/method LOC/method
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Toxicity Analysis
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Detailed study of the data shows most of the SIT & AT defects are occurring amongst the top four Java classes shown in the sample data above which have highly toxic code with high method length
Correlates to AT & SIT defects
2.3.10.1
2.3.9.2 2.3.6.2
2.3.53.2
2.3.52.2
2.3.5.2 2.3.4.2 2.3.36.2
2.3.35.2
2.3.34.2
2.3.33.2
2.3.32.2 2.3.30.2 2.3.20.2 2.3.19.2
2.3.10.2
2.3.7.2
2.3.50.2
2.3.49.2
2.3.20.2
2.3.13.2 2.3.44.2 2.3.43.2 2.3.42.2 2.3.41.2
2.3.40.2
2.3.39.2
2.3.38.2
2.3.37.2
2.3.11.2
2.3.12.2
2.3.27.2
2.3.2.2
2.3.1.2
2.3.48.2
2.3.47.2
2.3.46.2
2.3.45.2
2.3.26.2
2.3.25.2
2.3.23.2
2.3.22.2
2.3.18.2
2.3.17.2
2.3.16.2
2.3.15.2
UC complexity v/s cyclomatic complexity
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See code akin to a city map...
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Developer’s Structural Analysis Kit
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Parameters
• Max /Avg. Cyclomatic Complexity
• Methods Per Class
• Avg Statements Per Method
• % Branch statements
• Max Block Depth
• No. of Calls/method
• LOC/method
• Data abstraction coupling
Tools
• Source monitor
• PMD
• Checkstyle
• iPlasma & Code city
• Sonar
Process
• Integration to build tools
• Prior to code review
• Analysis before release
Shifting to the better – Project level
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Shifting to the better – Org level
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Max CodeComplexity
Methods perClass
Statementper Method
Branches % Max BlockDepth
Dec-10
Dec-11
Improved Pre-SIT Detection
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Dec-09 Dec-11 Till Date
Shift in defect distribution
Requirements & Design review
Code Review Unit Test System Test Post Release
Pre Post
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Customer Satisfaction
Engagement Planning Engagement Execution Engagement Results People
Overall 20102011
Qualitative Benefits
• Objective measures; language of developer
• Improve ability to isolate and deal with the defective ones
• Improved risk management and transparency
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Future Study..
• Profiling maintenance enhancements to be defect prone changes upfront
• Profiling application security and performance than just maintainability and functional quality
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