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We present an efficient approach to prove termination of monotone programs with integer variables, an expressive class of loops that is often encountered in computer programs. Our approach is based on a lightweight static analysis method and takes advantage of simple %nice properties of monotone functions. Our preliminary implementation %beats shows that our tool has an advantage over existing tools and can prove termination for a high percentage of loops for a class of benchmarks.
Extending our own and others earlier approaches to reasoning about termination of probabilistic programs, we propose and prove a new rule for termination with probability one, also known as almost-certain termination. The rule uses both (non-strict)
Five algebraic notions of termination are formalised, analysed and compared: wellfoundedness or Noetherity, Lobs formula, absence of infinite iteration, absence of divergence and normalisation. The study is based on modal semirings, which are additiv
The termination behavior of probabilistic programs depends on the outcomes of random assignments. Almost sure termination (AST) is concerned with the question whether a program terminates with probability one on all possible inputs. Positive almost s
We present a reduction of the termination problem for a Turing machine (in the simplified form of the Post correspondence problem) to the problem of determining whether a continuous-time Markov chain presented as a set of Kappa graph-rewriting rules
We investigate the termination problem of a family of multi-path polynomial programs (MPPs), in which all assignments to program variables are polynomials, and test conditions of loops and conditional statements are polynomial equalities. We show tha