Oink is an implementation of modern parity game solvers written in C++. Oink aims to provide high-performance implementations of state-of-the-art algorithms representing different approaches to solving parity games.
Oink is licensed with the Apache 2.0 license and is aimed at both researchers and practitioners. For convenience, Oink compiles into a library that can be used by other projects.
Oink is developed (© 2017) by Tom van Dijk and the Formal Methods and Verification group at the Johannes Kepler University Linz as part of the RiSE project.
The main author of Oink is Tom van Dijk who can be reached via firstname.lastname@example.org. Please let us know if you use Oink in your projects.
The main repository of Oink is https://github.com/trolando/oink.
Oink implements various modern algorithms.
|NPP||Priority promotion (bitvector implementation by Benerecetti et al)|
|PP||Priority promotion (basic algorithm)|
|PPP||Priority promotion PP+ (better reset heuristic)|
|RR||Priority promotion RR (even better improved reset heuristic)|
|DP||Priority promotion PP+ with the delayed promotion strategy|
|RRDP||Priority promotion RR with the delayed promotion strategy|
|ZLK||(parallel) Zielonka's recursive algorithm|
|APT||APT algorithm by Kupferman and Vardi|
|PSI||(parallel) strategy improvement|
|TSPM||Traditional small progress measures|
|SPM||Accelerated version of small progress measures|
|MSPM||Maciej Gazda's modified small progress measures|
|SSPM||Succinct small progress measures|
|QPT||Quasi-polynomial time progress measures|
|TL||Tangle learning (base algorithm)|
|ATL||Alternating tangle learning|
|OTFTL||On-the-fly tangle learning|
|OTFATL||On-the-fly alternating tangle learning|
- The priority promotion family of algorithms has been proposed in 2016.
- The Zielonka implementation is inspired by work in 2017.
- The APT algorithm was published in 1998 and again in 2016.
- The parallel strategy improvement implementation is inspired by work in 2017 but uses a different approach with work-stealing.
- The accelerated SPM approach is a novel approach.
- The succinct small progress measures algorithm was published in 2017. (Jurdzinski and Lazic, at LICS 2017)
- The QPT progress measures algorithm was published in 2017. (Fearnley et al, at SPIN 2017.)
- The tangle learning algorithms are accepted at CAV 2018.
The parallel algorithms use the work-stealing framework Lace.
The solver can further be tuned using several pre-processors:
- Removing all self-loops (recommended)
- Removing winner-controlled winning cycles (recommended)
- Inflating or compressing the game before solving it
- SCC decomposition to solve the parity game one SCC at a time.
May either improve or deteriorate performance
Oink comes with several simple tools that are built around the library liboink.
|oink||The main tool for solving parity games|
|verify||Small tool that just verifies a solution (can be done by Oink too)|
|nudge||Swiss army knife for transforming parity games|
|dotty||Small tool that just generates a .dot graph of a parity game|
|simple||Very simple example of a tool that solves parity games|
Tools to generate games:
|rngame||Faster version of the random game generator of PGSolver|
|stgame||Faster version of the steady game generator of PGSolver|
|counter_rr||Counterexample to the RR solver|
|counter_dp||Counterexample to the DP solver|
|counter_m||Counterexample of Maciej Gazda, PhD Thesis, Sec. 3.5|
|counter_qpt||Counterexample of Fearnley et al, An ordered approach to solving parity games in quasi polynomial time and quasi linear space, SPIN 2017|
|counter_core||Counterexample of Benerecetti et al, Robust Exponential Worst Cases for Divide-et-Impera Algorithms for Parity Games, GandALF 2017|
|tc||Two Counters game (counterexample to TL, ZLK, PP family)|
Oink is compiled using CMake.
ccmake to set options.
By default, Oink does not compile the extra tools, only the library
liboink and the tool
Oink requires the Boost libraries, in particular
mkdir build && cd build cmake .. && make && make install
Oink provides usage instructions via
oink --help. Typically, Oink is provided a parity game either
via stdin (default) or from a file. The file may be zipped using the gzip or bzip2 format, which is detected if the
filename ends with
|What you want?||But how then?|
|To quickly solve a gzipped parity game:||
|To verify some solution:||
A typical call to Oink is:
oink [options] [solver] <filename> [solutionfile]. This reads a parity game from
filename, solves it with the chosen solver (default:
--atl), then writes the solution to
<solutionfile> (default: don't write).
Typical options are:
-vverifies the solution after solving the game.
-w <workers>sets the number of worker threads for parallel solvers. By default, these solvers run their sequential version. Use
-w 0to automatically determine the maximum number of worker threads.
--compressinflate/compress the game before solving it.
--sccrepeatedly solves a bottom SCC of the parity game.
--no-singledisable preprocessors that eliminate winner-controlled winning cycles, self-loops and single-parity games.
-z <seconds>kills the solver after the given time.
--sol <filename>loads a partial or full solution.
--dot <dotfile>writes a .dot file of the game as loaded.
-pwrites the vertices won by even/odd to stdout.
-t(once or multiple times) increases verbosity level.
For a very simple example of a tool that uses Oink, see
For a very simple example of extending Oink, see e.g. commits