Marie-Claude Gaudel

Test sets generation from algebraic specifications using logic programming

Abstract We present a method and a tool for generating test sets from algebraic data type specifications. We give formal definitions of the basic concepts required in our approach of functional testing. Then we discuss the problem of testing algebraic data types implementations. This allows the introduction of additional hypotheses and thus the description of a method for generating test sets. The implementation of the method is based on logic programming. Some limitations of PROLOG are discussed and two extensions are presented, METALOG and SLOG, which allow good implementations of our method.

A Theory of Software Reusability

Software reusability is a topic of first practical importance. Most of the current approaches are based on empirical methods and there is no general approach to this problem. This paper suggests a definition for software reusability based on algebraic specifications and modularity. This criterion is not completely constructive, but it provides a guideline to find out reusable software components and prove their reuse. Moreover, we state how to exploit reusability in hierarchical specifications.

Exception Handling: Formal Specification and Systematic Program Construction

We present an algebraic specification language (PLUSS) and a program construction method. Programs are built systematically from an algebraic specification of the data they deal with. The method was tested on a realistic problem (part of a telephone switching system). In these experiments, it turned out that error handling was the difficult part to specify and to program. This paper shows how to cope with this problem at the specification level and during the program development process.

Application of PROLOG to test sets generation from algebraic specifications

We present a method and a tool for generating test sets from algebraic data type specifications. We give formal definitions of the basic concepts required in our approach of functional testing. Then we discuss the problem of testing algebraic data types implementations. This allows the introduction of additional hypotheses and thus the description of an effective method for generating test sets. The method can be improved by using PROLOG. Indeed, it turns out that PROLOG is a very well suited tool for generating test sets in this context. Applicability of the method is discussed and a complete example is given.

Coverage-biased Random Exploration of Models

This paper describes a set of methods for randomly drawing traces in large models either uniformly among all traces, or with a coverage criterion as target. Classical random walk methods have some drawbacks. In case of irregular topology of the underlying graph, uniform choice of the next state is far from being optimal from a coverage point of view. Moreover, for the same reason, it is generally not practicable to get an estimation of the coverage obtained after one or several random walks: it would require some complex global analysis of the model topology. We present here some methods that give up the uniform choice of the next state. These methods bias this choice according to the number of traces, or states, or transitions, reachable via each successor.

Counting for random testing

The seminal works of Wilf and Nijenhuis in the late 70s have led to efficient algorithms for counting and generating uniformly at random a variety of combinatorial structures. In 1994, Flajolet, Zimmermann and Van Cutsem have widely generalised and systematised the approach. This paper presents several applications of these powerful results to software random testing, and random model exploration.