Test Input Data Generation for Choiceless Program Nets

Software testing is an important problem in designing a large software system and this problem is difficult to solve due to its computational complexity. Generating test input data is an effective way to approach this problem, and we try to use program net to find test input data. In our previous work, as the first step towards solving software testing problem, we have proposed algorithms to divide a whole program net into subnets that can structurally cover the original one based on a divide-and-conquer method. This paper aims to solve the remaining task of our approach, which is how to find test input data for each subnet to be called choiceless program net. First, definitions of program nets are extended and the properties of choiceless program nets are analysed. Then, polynomial algorithms are proposed to get all constraint conditions of any given choiceless program nets. Finally, a method to generate test input data under the obtained constraint conditions is proposed by adopting an SMT (Satisfiability Modulo Theory) solver called Z3 prover. An example is given to show the usefulness of our method.