An approach to fault modeling and fault seeding using the program dependence graph

Abstract

We present a fault-classification scheme and a fault-seeding method that are based on the manifestation of faults in the program dependence graph (PDG). We enhance the domain/computation fault classification scheme developed by Howden to further characterize faults as structural and statement-level depending on the differences between the PDG for the original program and the PDG for the faulty program. We perform transformations on the PDG to produce the different types of faults described in our PDG-based fault-classification scheme. To demonstrate the usefulness of our technique, we implemented a fault seeder to embed faults in C programs. Our fault seeder makes controlled fault transformations to the PDG for a C program, and generates C code from the transformed PDG. The current version of the fault seeder creates multiple fault-seeded versions of the original program, each with one known fault. To demonstrate the operation of the fault seeder, we used it to perform a study of the effectiveness of dataflow testing and mutation testing using a set of faulty programs generated by our fault seeder. We also used the faulty programs to determine the mutation adequacy and detaflow adequacy of the fault-detecting test sets.