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Description
                    LibFuzzer serves as an in-process, coverage-guided engine for evolutionary fuzzing. By being linked directly with the library under examination, it injects fuzzed inputs through a designated entry point, or target function, allowing it to monitor the code paths that are executed while creating variations of the input data to enhance code coverage. The coverage data is obtained through LLVM’s SanitizerCoverage instrumentation, ensuring that users have detailed insights into the testing process. Notably, LibFuzzer continues to receive support, with critical bugs addressed as they arise. To begin utilizing LibFuzzer with a library, one must first create a fuzz target—this function receives a byte array and interacts with the API being tested in a meaningful way. Importantly, this fuzz target operates independently of LibFuzzer, which facilitates its use alongside other fuzzing tools such as AFL or Radamsa, thereby providing versatility in testing strategies. Furthermore, the ability to leverage multiple fuzzing engines can lead to more robust testing outcomes and clearer insights into the library's vulnerabilities.
                
            
        
            Description
                    The hevm project serves as a tailored implementation of the Ethereum Virtual Machine (EVM) designed for tasks like symbolic execution, unit testing, and debugging of smart contracts. Created by DappHub, it seamlessly integrates with the suite of tools offered by the same developer. The hevm command line interface enables users to symbolically execute smart contracts, conduct unit tests, debug contracts interactively while displaying the Solidity source code, or execute any arbitrary EVM code. It allows computations to be carried out using a local state established within a testing framework or retrieved from live networks through RPC calls. Users can initiate symbolic execution with specified parameters to detect assertion violations and can also customize certain function signature arguments while keeping others abstract. Notably, hevm adopts an eager approach to symbolic execution, meaning that it initially strives to investigate all branches of the program. This comprehensive method enhances the reliability and robustness of smart contract development and testing.
                
            
        
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    C
            
            
        
        
    
        
        
            
                
    C++
            
            
        
        
    
        
        
            
                
    ClusterFuzz
            
            
        
        
    
        
        
            
                
    Ethereum
            
            
        
        
    
        
        
            
                
    Fuzzbuzz
            
            
        
        
    
        
        
            
                
    Google ClusterFuzz
            
            
        
        
    
        
        
            
                
    Jazzer
            
            
        
        
    
        
        
            
                
    Solidity
            
            
        
        
    
                
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                Vendor Details
Company Name
LLVM Project
Founded
2003
Website
llvm.org/docs/LibFuzzer.html
Vendor Details
Company Name
DappHub
Website
github.com/dapphub/dapptools/blob/master/src/hevm/README.md