The following is outdated please check new post with new steps:
For EMSE paper I am using the following:
101 repo new with corrected code for search indices for comments and API names, using eclipse JDT parser
public static String PROJECTS_ROOT = "E://101projects";
public static String DATABASE = "jdbc:mysql://localhost/101reponew?useSSL=false&user=root";
public static String LUCENE_INDEX_DIR = "F:/temp/101reponew";
FACER repo Building Code:
F:\PhD\PhD Defense\FACERGitRepository\FACER\src\replicateparser\ParseContextAction.java
Now you have to manually add api_call_index_id column in api_call table
Then execute code to populate the column using F:\PhD\PhD Defense\Code\MyUPMiner\src\_1_api_call_index\APICallIndexing.java
Then you have to populate sequence table using F:\PhD\PhD Defense\Code\MyUPMiner\src\_2_SeqSim\PairwiseSequenceScoring.java
Then you have to generate a CSV for clustering the sequences using
select host_method_id as methodID,api_call_index_id as APICall from api_call
where api_call_index_id!=0
Export it to a CSV and put it on Codec, use putty to execute Nicks.R script.
Command is Rscript Nicks.R
Make sure that the input and output csv file names in Nicks.R are set to the ones you need
Populate the clusters table and Execute the code F:\PhD\PhD Defense\Code\MyUPMiner\src\_3_i_WriteClustersFromR\WriteClusters.java
Make sure to set the correct database url for the constants file.
Create transaction table using F:\PhD\PhD Defense\Code\FASeR_Recommender\src\_1_TransactionTable\TransactionTable.java
Make sure to set the correct database url for the constants file.
Save the file as TransactionTablefor101reponew.txt and Input it to spmf FPClose algo to get the frequent patterns and save it as a text file 101reponew.txt
Mine frequent patterns using F:\PhD\PhD Defense\Code\spmf\ca\pfv\spmf\test\MainTestFPClose_saveToFile.java
make sure to change the input (101reponew.txt) output files (output_101reponew_point03.txt)
Copy the output file to FASER Recommender folder
Populate related features using F:\PhD\PhD Defense\Code\FASeR_Recommender\src\_3_PopulateRelatedFeatures\PopulateRelatedFeatures.java
make sure to change the input file name to the one you mined i.e. output_101reponew_point03.txt
For EMSE paper I am using the following:
101 repo new with corrected code for search indices for comments and API names, using eclipse JDT parser
public static String PROJECTS_ROOT = "E://101projects";
public static String DATABASE = "jdbc:mysql://localhost/101reponew?useSSL=false&user=root";
public static String LUCENE_INDEX_DIR = "F:/temp/101reponew";
FACER repo Building Code:
F:\PhD\PhD Defense\FACERGitRepository\FACER\src\replicateparser\ParseContextAction.java
Now you have to manually add api_call_index_id column in api_call table
Then execute code to populate the column using F:\PhD\PhD Defense\Code\MyUPMiner\src\_1_api_call_index\APICallIndexing.java
Then you have to populate sequence table using F:\PhD\PhD Defense\Code\MyUPMiner\src\_2_SeqSim\PairwiseSequenceScoring.java
Then you have to generate a CSV for clustering the sequences using
select host_method_id as methodID,api_call_index_id as APICall from api_call
where api_call_index_id!=0
Export it to a CSV and put it on Codec, use putty to execute Nicks.R script.
Command is Rscript Nicks.R
Make sure that the input and output csv file names in Nicks.R are set to the ones you need
Populate the clusters table and Execute the code F:\PhD\PhD Defense\Code\MyUPMiner\src\_3_i_WriteClustersFromR\WriteClusters.java
Make sure to set the correct database url for the constants file.
Create transaction table using F:\PhD\PhD Defense\Code\FASeR_Recommender\src\_1_TransactionTable\TransactionTable.java
Make sure to set the correct database url for the constants file.
Save the file as TransactionTablefor101reponew.txt and Input it to spmf FPClose algo to get the frequent patterns and save it as a text file 101reponew.txt
Mine frequent patterns using F:\PhD\PhD Defense\Code\spmf\ca\pfv\spmf\test\MainTestFPClose_saveToFile.java
make sure to change the input (101reponew.txt) output files (output_101reponew_point03.txt)
Copy the output file to FASER Recommender folder
Populate related features using F:\PhD\PhD Defense\Code\FASeR_Recommender\src\_3_PopulateRelatedFeatures\PopulateRelatedFeatures.java
make sure to change the input file name to the one you mined i.e. output_101reponew_point03.txt
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