Learn to Predict “Affecting Changes” in Software Engineering Xiaoxia Ren Dec. 8, 2003.

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Presentation transcript:

Learn to Predict “Affecting Changes” in Software Engineering Xiaoxia Ren Dec. 8, 2003

Background Software systems evolve over time To adapt to environment To add desired functionality Graceful software evolution requires Only expected functionality changes occur How to guarantee the correctness? Unit or regression tests

Motivation Given: Two versions of a program, before and after editing A unit test compilable in both versions Question: For a specified edit (change), could we predict whether it affects the behavior of this unit test or not?

Data Format

Experimental Setup Data collected from Daikon System over year 2002 Each week labeled as a version Dataset was split at month boundary and each dataset included at least 800 instances Prediction based on cumulative data

Accuracy Comparison

True Positive Rate for “yes” class

Precision for “yes” class

Data Analysis and Some Thoughts Why TP and Precision rate so low? Change activity on Daikon was quite diverse. The distribution of training data is different from test data. The percentage of “yes” instance is too small (5.9%) Some Thoughts How about a project in a stable stage? Try other ML algorithms?

Q & A?