Constraint-Based Testing (CBT) is the process of generating test cases against a testing objective by using constraint solving techniques. When programs contain dynamic memory allocation and loops, constraint reasoning becomes challenging as new variables and new constraints are created during the test data generation process. In this paper, we address this problem by proposing a new constraint model of C programs based on operators that model dynamic memory management. These operators apply deduction rules on abstract states of the memory allowing so to enhance the constraint reasoning process that permits to generate test data for these programs. We illustrate our approach on structural testing of a complex program that contains dynamic memory allocation/deallocation, structures and loops. An implementation is in progress and first experimental results obtained on this program show the highly deductive potential of the approach.

Abstract-In this paper, we introduce a constraint-based reasoning approach to automatically generate test input for Java bytecode programs. Our goal-oriented method aims at building an input state of the Java Virtual Machine (JVM) that can drive program execution towards a given location within the bytecode. An innovative aspect of the method is the definition of a constraint model for each bytecode that allows backward exploration of the bytecode program, and permits to solve complex constraints over the memory shape (e.g., p == p.next enforces the creation of a cyclic data structure referenced by p). We implemented this constraint-based approach in a prototype tool called JAUT, that can generate input states for programs written in a subset of JVM including integers and references, dynamic-allocated structures, objects inheritance and polymorphism by virtual method call, conditional and backward jumps. Experimental results show that JAUT generate test input for executing locations not reached by other state-of-the-art code-based test input generators such as jCUTE, JTEST and Pex.

Constraint-Based Testing (CBT) is the process of generating test cases against a testing objective by using constraint solving techniques. When programs contain dynamic memory allocation and loops, constraint reasoning becomes challenging as new variables and new constraints should be created during the test data generation process. In this paper, we address this problem by proposing a new constraint model of C programs based on operators that model dynamic memory management. These operators apply powerful deduction rules on abstract states of the memory enhancing so the constraint reasoning process. This allows to automatically generate test data respecting complex coverage objectives. We illustrate our approach on a well-known difficult example program that contains dynamic memory allocation/deallocation, structures and loops. We describe our implementation and provide preliminary experimental results on this example that show the highly deductive potential of the approach.

Constraint-Based Testing (CBT) is the process of generating test cases against a testing objective by using constraint solving techniques. When programs contain dynamic memory allocation and loops, constraint reasoning becomes challenging as new variables and new constraints should be created during the test data generation process. In this paper, we address this problem by proposing a new constraint model of C programs based on operators that model dynamic memory management. These operators apply powerful deduction rules on abstract states of the memory enhancing so the constraint reasoning process. This allows to automatically generate test data respecting complex coverage objectives. We illustrate our approach on a well-known difficult example program that contains dynamic memory allocation/deallocation, structures and loops. We describe our implementation and provide preliminary experimental results on this example that show the highly deductive potential of the approach.