Abstract

Context Legacy information systems age over time. These systems cannot be thrown away because they store a significant amount of valuable business knowledge over time, and they cannot be entirely replaced at an acceptable cost. This circumstance is similar to that of the monuments of ancient civilizations, which have aged but still hold meaningful information about their civilizations. Evolutionary maintenance is the most suitable mechanism to deal with the software ageing problem since it preserves business knowledge. But first, recovering the underlying business knowledge in legacy systems is necessary in order to preserve this vital heritage. Objective This paper proposes and validates a method for recovering and rebuilding business processes from legacy information systems. This method, which can be considered a business process archeology, makes it possible to preserve the business knowledge in legacy information systems. Method The business process archeology method is framed in MARBLE, a generic framework based on Architecture-Driven Modernization (ADM), which uses the Knowledge Discovery Metamodel (KDM) standard. The proposed method is validated using a case study that involves a real-life legacy system. The case study is conducted following the case study protocol proposed by Brereton et al. Results The study reports that the proposed method makes it possible to obtain business process models from legacy systems with adequate levels of accuracy. In addition, the effectiveness of the proposed method is also validated positively. Conclusion The proposed method semi-automatically rebuilds the hidden business processes embedded in a legacy system. Therefore, the business process archeology method quickly allows business experts to have a meaningful understanding of the organization’s business processes. This proposal is less time-consuming and more exhaustive (since it considers the embedded business knowledge) than a manual process redesign by experts from scratch. In addition, it helps maintainers to extract the business knowledge needed for the system to evolve.

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