2012/02/20 by Amir M. Ben-Amram, Ben-Amram, Amir M., Michael Vainer +1
Computer Science · #D.2.4 #D.2.8 #F.2.0 #F.3.1 #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #Formal Methods in Verification #Logic in Computer Science (cs.LO) #Logic, programming, and type systems #cs.FL #cs.LO #semigroups and automata theory
paper · pdf · doi:10.48550/arxiv.1202.4281
46 pages. Research has been presented at DICE 2011 (Saarbruecken, Germany, March 2011), 2FC 2011 (Novi Sad, Serbia, May 2011) and DANSAS (Odense, Denmark, August 2011). Revised (twice) to correct errors in previous versions
openalex publication_date 2012/02/20 · arxiv created 2014/04/30 · arxiv updated 2014/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Intuitively, if we can prove that a program terminates, we expect some conclusion regarding its complexity. But the passage from termination proofs to complexity bounds is not always clear. In this work we consider Monotonicity Constraint Transition Systems, a program abstraction where termination is decidable (based on the size-change termination principle). We show that these programs also have a decidable complexity property: one can determine whether the length of all transition sequences can be bounded in terms of the initial state. This is the Bounded Termination problem. Interestingly, if a bound exists, it must be polynomial. We prove that the bounded termination problem is PSPACE-complete. We also discuss, theoretically, the use of bounds on the abstract program to infer conclusions on a concrete program that has been abstracted. The conclusion maybe a polynomial time bound, or in other cases polynomial space or exponential time. We argue that the monotonicity-constraint abstraction promises to be useful for practical complexity analysis of programs.