CP-Detector

CP-Detector: Using Configuration-related Performance Properties to Expose Performance Bugs

To run the property suggester,

Step 1

Install requirements:

pip install -U prefixspan t

pip install spacy
pip install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz

and check all directory name in the three pyhon script fit the envirnment

Step 2

Generate universal unique id for each normalized word.
e.g., (NN, Resource) --> 58 (NN, Volume) --> 89 etc.

python MapWordAbstraction2UniqueNodeID.py

Step 3

1. Normalizing Words
2. Mining Association Rules (CARs)
3. Calculate the quality for each (CARs)

python Preprocessing & Mining.py

This will generate 10^6 - 10^7 CARs, we save it to disk (FreqSeq), and the quality of each CAR (S_C_L, stands for support, confidence, lift).

Step 4

4. Selecting Optimal rules.
5. build a voting classifier

python OptimalSelection & Classification.py

you can choose to use the Random-N or Top-N by changing RandomNOrTopN to 1 or 0.

Step 5

The result will be shown in python console, or we provide simple visualization code to help you.