Commit d348254a authored by Gaurav Kumar's avatar Gaurav Kumar
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Update README.md

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......@@ -61,8 +61,10 @@ For example, we have used modified input [file](https://gitlab.uni-koblenz.de/gg
We have used output data visualized in the form of graph from thesis and produced count of mcr categories and percentages of dominance over each other which used as the input data of our process. Then we have produced results that the most dominant category is ‘Testing Frameworks’ with percentage of 59.63% which is calculated by excluding null values. Then further data has been used to compare the probabilities of usage of API with respect to mcr category.
# Process:
In the Process folder, inside repositories_visualizer.py, we have two methods calculate_dominant_mcrcategories () and api_probability_in_mcrcategories (). In addition we have two other files that we have reused as in the original master thesis - https://gitlab.uni-koblenz.de/ggaurav/applying-apis/-/blob/main/Process/repositories_visualizer.py
In the Process folder, inside repositories_visualizer.py, we have two methods calculate_dominant_mcrcategories () and api_probability_in_mcrcategories () - https://gitlab.uni-koblenz.de/ggaurav/applying-apis/-/blob/main/Process/repositories_visualizer.py
calculate_dominant_mcrcategories (): This method calculates the dominant mcr category percentage.
api_probability_in_mcrcategories (): This method calculates the probability of an api having a particular mcr category.
In addition we have two other files that we have reused as in the original master thesis.
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