2 repositorios
Systematically varying command-line arguments to analyze the impact of different inputs on performance.
Distinct from Parameter Sampling: Focuses on CLI argument variation for benchmarking rather than sampling values for model optimization
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Command Parameter Scanning. Refine with filters or upvote what's useful.
Hyperfine is a command-line benchmarking tool used to measure the execution time of shell commands through multiple runs and statistical analysis. It functions as a comparative benchmarking utility and a shell performance analyzer, allowing for the evaluation of multiple commands against a reference baseline to determine relative speed. The tool distinguishes itself by isolating actual command performance through shell overhead correction and the ability to bypass the shell entirely using system calls. It supports parameterized execution, enabling benchmarks to run across a range of varying i
Runs benchmarks across a range of varying input parameters to analyze how specific changes impact execution speed.
Arjun is an HTTP parameter discovery tool that identifies valid parameters on web endpoints by testing large dictionaries of parameter names against target URLs. It systematically probes endpoints using GET, POST, JSON, and XML request formats to find which parameters the server accepts, and can detect parameters whose values appear reflected in the response body. The tool distinguishes itself through its multi-method scanning approach, passive parameter collection from public archives like OTX and CommonCrawl, and its ability to detect value-sensitive parameters that only trigger a response
Probes endpoints with GET, POST, JSON, and XML request formats to discover parameters across different input types.