Abstract. Actor programs consist of a number of concurrent objects called actors, which communicate by exchanging messages. Nondeterminism in actors results from the different possible orders in which available messages are processed. Systematic testing of actor programs explores various feasible message processing schedules. Dynamic partial-order reduction (DPOR) techniques speed up systematic testing by pruning parts of the exploration space. Based on the exploration of a schedule, a DPOR algorithm may find that it need not explore some other schedules. However, the potential pruning that can be achieved using DPOR is highly dependent on the order in which messages are considered for processing. This paper evaluates a number of heuristics for choosing the order in which messages are explored for actor programs, and summarizes their advantages and disadvantages.
While in some cases, such selection is irrelevant, it is known that the pruning that can be achieved is highly dependent on the order in which tasks are considered for processing (see REF ).
Evaluating Ordering Heuristics for Dynamic Partial-order Reduction Techniques
FASE
Computer Science