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صفحه اصلی
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هفتمین همايش ملی پيشرفت های معماری سازمانی
Improving enterprise architecture mining methods
نویسندگان :
Mohsen Mohammadinezhad (دانشگاه شهید بهشتی) , Fereidoon Shams Aliee (دانشگاه شهید بهشتی)
کلمات کلیدی :
Enterprise Architecture Mining،Enterprise Architecture Smells،Enterprise Architecture Debts،Knowledge Graph،Archimate
چکیده :
Enterprise architecture takes a step in the path of digital transformation by providing a comprehensive system with an integrated view of the organization. In traditional methods, architects manually prepare enterprise architecture products. The manual methods of producing enterprise architecture products have many challenges. One of the main challenges is the production of volumes of documentation, the complexity and difficulty of making enterprise architecture artifacts, and their costly and error-prone nature. In response to these challenges, enterprise architecture mining is proposed, automatically producing outputs and artifacts of enterprise architecture instead of manual modeling. Surveys show that the field of enterprise architecture analysis has yet to reach maturity, and the presented works are far from reaching complete automation. Some methods may be successful in some layers, but reaching a method that automatically provides an integrated enterprise architecture model with sufficient accuracy remains the challenge. This research will use model analysis methods to improve enterprise architecture mining. At first, the presented method extracts enterprise architecture models automatically. In the next step, this method extracts the enterprise architecture debts by detecting the enterprise architecture smells. Ultimately, it improves the extracted models using reconstructing methods. We expect that the proposed method can improve the accuracy and quality of the extracted models.
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