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MACHINE LEARNING
Machine Learning is the study of computer algorithms that improve automatically through experience
- Tom Mitchell
SOFTWARE TEST LIFE CYCLE
Pre-execution
• Test planning
• Code Review
• Test case management
Execution
• Automated run
• Defect analysis
Post-execution
• Debugging
• Regression suite update
SOFTWARE TESTING
Critical task in Software development process
Overspend in time and resources
Automation limited to test execution
SOFTWARE TEST LIFE CYCLE
Pre-execution
• Test planning
• Code Review
• Test case management
Execution
• Automated run
• Defect analysis
Post-execution
• Debugging
• Regression suite update
SOFTWARE TEST ACTIVITIES AND ML
Software defect prediction
Test Planning
Test case management
Debugging
NAÏVE BAYES ALGO
Branch Count LOC Defective
5 15 No
3 5 No
9 20 No
15 40 Yes
16 35 Yes
Branch Count = 16 LOC = 39
C = No -> 0.000000912
C = Yes -> 0.0181Leandru Minku: Automated Software Defect Prediction Using Machine Learning
LINEAR REGRESSION – DEFECT DENSITY
http://openclassroom.stanford.edu/MainFolder/DocumentPage.php?course=MachineLearning&doc=exercises/ex2/ex2.html
LOC
Defe
ct D
ensity
TEST PLANNING
Database formation
Data collection
Classification of software
Analyzing the results
Test Cost prediction
Thomas J. Cheatham, Jungsoon P. Yoo, and Nancy J. Wahl. Software testing: a machine learning experiment.
Complexity
Cost
MELBA – MACHINE LEARNING BASED REFINEMENT OF BLACKBOX TEST SPECIFICATION
Lionel C. Briand. Novel applications of machine learning in software testing. Quality Software, International Conference on, 0:3–10,
2008.
AREAS OF APPLICATION
Machine Learning-based Software Testing: Towards a Classification Framework Mahdi Noorian1, Ebrahim Bagheri1,2, and Wheichang Du1
STEPS FORWARD
Black Box techniques
Finding the right patterns
Algorithm analysis for different types of test activity
Crowdsourcing