Size-Space Bounds and Trade-offs for CDCL Proofs

ABSTRACT. A long line of research has shown that conflict-driven clause learning viewed as a proof system can polynomially simulate resolution. We give a more explicit description of this CDCL proof system, which allows us to define proof size and space in a natural way and also capture aspects such as clause learning schemes and restart policies. This in turn makes it possible to study which upper and lower bounds on size, space and size-space trade-offs in general resolution carry over to proofs actually realizable by CDCL solvers.