Published February 12, 2024
                      
                       | Version 0.2
                    
                    
                      
                        
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                  On the Effectiveness of Machine Learning-based Call Graph Pruning: An Empirical Study
Creators
Description
This is the replication package for our empirical study "On the Effectiveness of Machine Learning-based Call Graph Pruning", which is accepted at the technical track of the MSR'24 conference. It contains source code and datasets needed to replicate the paper's results.
Note: before downloading the data files, check out the README.md file.
Also, check out the GitHub repository of this work for the latest fixes and updates.
Files
      
        ml4cgp_study_source_code.zip
        
      
    
    
      
        Files
         (40.8 GB)
        
      
    
    | Name | Size | Download all | 
|---|---|---|
| md5:2dcda89706ed85a94136a18d0134077a | 10.0 GB | Download | 
| md5:7461f8accdaab74b84b9855c1c187cf7 | 10.0 GB | Download | 
| md5:9fd0ecc4aca02cd610cadb55fbfc1f1a | 10.0 GB | Download | 
| md5:6d8a48db8a84777b093fe0dfd99190b6 | 10.0 GB | Download | 
| md5:78a59a75d874a2b1267c629b7b75f9ec | 813.7 MB | Download | 
| md5:62b241928465a25b9cb7ea3aac8c3715 | 95.1 kB | Preview Download | 
| md5:8db070480fe14a4c28d2d91ad96ad24c | 196 Bytes | Preview Download | 
Additional details
              
                Software
              
            
          - Repository URL
- https://github.com/mir-am/ml4cgp_study
- Programming language
- Python, Java, Shell
- Development Status
- Active