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+# OptiMin
+
+OptiMin is a corpus minimizer that uses a
+[MaxSAT](https://en.wikipedia.org/wiki/Maximum_satisfiability_problem) solver
+to identify a subset of functionally distinct files that exercise different code
+paths in a target program.
+
+Unlike most corpus minimizers, such as `afl-cmin`, OptiMin does not rely on
+heuristic and/or greedy algorithms to identify these functionally distinct
+files. This means that minimized corpora are generally much smaller than those
+produced by other tools.
+
+## Building
+
+To build the `optimin` just execute the `build_optimin.sh` script.
+
+## Running
+
+Running `optimin` is the same as running `afl-cmin`:
+
+```
+./optimin -h
+OVERVIEW: Optimal corpus minimizer
+USAGE: optimin [options] <target program> [target args...]
+
+OPTIONS:
+
+Color Options:
+
+  --color     - Use colors in output (default=autodetect)
+
+General options:
+
+  -C          - Keep crashing inputs, reject everything else
+  -O          - Use binary-only instrumentation (FRIDA mode)
+  -Q          - Use binary-only instrumentation (QEMU mode)
+  -U          - Use unicorn-based instrumentation (unicorn mode)
+  -f          - Include edge hit counts
+  -i dir      - Input directory
+  -m megs     - Memory limit for child process (default=none)
+  -o dir      - Output directory
+  -p          - Display progress bar
+  -t msec     - Run time limit for child process (default=5000)
+  -w csv      - Weights file
+
+Generic Options:
+
+  --help      - Display available options (--help-hidden for more)
+  --help-list - Display list of available options (--help-list-hidden for more)
+  --version   - Display the version of this program
+```
+
+Example: `optimin -i files -o seeds -- ./target @@`
+
+### Weighted Minimizations
+
+OptiMin allows for weighted minimizations. For examples, seeds can be weighted
+by file size (or execution time), thus preferencing the selection of smaller (or
+faster) seeds.
+
+To perform a weighted minimization, supply a CSV file with the `-w` option. This
+CSV file is formatted as follows:
+
+```
+SEED_1,WEIGHT_1
+SEED_2,WEIGHT_2
+...
+SEED_N,WEIGHT_N
+```
+
+Where `SEED_N` is the file name (**not** path) of a seed in the input directory,
+and `WEIGHT_N` is an integer weight.
+
+## Further Details and Citation
+
+For more details, please see the paper [Seed Selection for Successful
+Fuzzing](https://dl.acm.org/doi/10.1145/3460319.3464795). If you use OptiMin in
+your research, please cite this paper.
+
+Bibtex:
+
+```bibtex
+@inproceedings{Herrera:2021:FuzzSeedSelection,
+  author = {Adrian Herrera and Hendra Gunadi and Shane Magrath and Michael Norrish and Mathias Payer and Antony L. Hosking},
+  title = {Seed Selection for Successful Fuzzing},
+  booktitle = {30th ACM SIGSOFT International Symposium on Software Testing and Analysis},
+  series = {ISSTA},
+  year = {2021},
+  pages = {230--243},
+  numpages = {14},
+  location = {Virtual, Denmark},
+  publisher = {Association for Computing Machinery},
+}
+```