Lionel Briand

Class responsibility assignment is not an easy skill to acquire. Though there are many methodologies for assigning responsibilities to classes, they all rely on human judgment and decision making. Our objective is to provide decision-making help to re-assign methods and attributes to classes in a class diagram. Our solution is based on a multi-objective genetic algorithm (MOGA) and uses class coupling and cohesion measurement. Our MOGA takes as input a class diagram to be optimized and suggests possible improvements to it. The choice of a MOGA stems from the fact that there are typically many evaluation criteria that cannot be easily combined into one objective, and several alternative solutions are acceptable for a given OO domain model. This article presents our approach in detail, our decisions regarding the multi-objective genetic algorithm, and reports on a case study. Our results suggest that the MOGA can help correct suboptimal class responsibility assignment decisions.

A number of activities involved in testing software are known to be difficult and time consuming. Among them is the definition and coding of test oracles and the isolation of faults once failures have been detected. Through a thorough and rigorous empirical study, we investigate how the instrumentation of contracts could address both issues. Contracts are known to be a useful technique in specifying the precondition and postcondition of operations and class invariants, thus making the definition of object‐oriented analysis or design elements more precise. It is one of the reasons the Object Constraint Language (OCL) was made part of the Unified Modeling Language. Our aim in this paper is to reuse and instrument contracts to ease testing. A thorough case study is run where we define OCL contracts, instrument them using a commercial tool and assess the benefits and limitations of doing so to support the automated detection of failures and the isolation of faults. As contracts can be defined at various levels of detail, we also investigate the cost and benefit of using contracts at different levels of precision. We then draw practical conclusions regarding the applicability of the approach and its limitations. Copyright © 2003 John Wiley & Sons, Ltd.