Abstract. Many companies struggle with large amounts of legacy software that is difficult to maintain and to extend. Refactoring legacy code typically requires large efforts and introduces serious risks because often crucial business assets are hidden in legacy components. We investigate the support of formal techniques for the rejuvenation of legacy embedded software, concentrating on control components. Model learning and equivalence checking are used to improve a new implementation of a legacy control component. Model learning is applied to both the old and the new implementation. The resulting models are compared using an equivalence check of a model checker. We report about our experiences with this approach at Philips. By gradually increasing the set of input stimuli, we obtained implementations of a power control service for which the learned behaviour is equivalent.
We evaluate the effect of applying the commercial formal technique Analytical Software Design (ASD) to an industrial project. In ASD, interfaces and software designs are modelled using a formal tabular notation. The ASD tool set supports formal checks of these models, such as deadlock freedom and interface compliance. In addition, full code can be generated from design models. ASD has been applied at Philips Healthcare to develop parts of the software of interventional X-ray systems. We report about the experiences with the embedding of ASD into the development processes. The quality of the resulting code and the productivity has been analysed and compared to code developed with other techniques. We observe that the use of ASD leads to a strong reduction of the number of defects and an increase in productivity. The results are also compared to the literature about standards and related projects at other companies.
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