Nasreddine Aoumeur1, Kamel Barkaoui2 and Gunter Saake3, 1University of Science and Technology (USTO), Algeria, 2France, 3Universitat Magdeburg, Germany
Artificial Intelligence (AI) with its Machine-Learning (ML) vertiginous advances are dramatically reshaping our way of developing software either as (prompting) GenerativeAI- or purely ML-based ones. Nevertheless, this newly emerging AI-Era of software is unfortunately not significantly benefiting from decades of investigations and findings around software-engineering (SE) concepts, principles and methods. The resulting is plethora of GenerativeAI- and ML-based software: Black-boxed rigid ill-conceptually and completely isolated from our ”ordinary” yet mostly disciplined software landscape. The aim of this paper is to contribute in leveraging such unsatisfactory Prompting and ML-based software form to be well-conceptually, dynamically adaptable by intrinsically fitting it within our ”ordinary” domain-oriented software landscape: We refer generically to as AI-Powered (knowledge-intensive) applications software; thereby reconciliating Domain- and AI-Experts instead of contemporarily miserable ’confrontation’. We achieve such promising endeavour by exactly capitalizing on best advanced SE concepts and principles More precisely, we are putting forward an innovative stepwise integrated modeldriven approach that smoothly exhibits the following conceptual, founded and technological milestones. Firstly, any structural features are semi-formally modelled as UML components intrinsically thereafter mapped into (ordinary and ML based) Web-Services. Behavioural crucial features are then captured as intuitive business rules mostly at the inter-service interactions. Secondly, for the precise conceptualization of such inter-service behavioural rules, we are proposing tailored graphically appealing stereotyped primitives as ECA-driven architectural (interservice) connector glues, we refer to as ECA-driven interaction laws. Thirdly, for the rigorous certification, while staying ECA-Compliant we are tailoring Meseguer’s true-concurrent rewriting logic and its strategies-enabled Maude language for that purpose. Last but not least, for the efficient implementation we are proposing a four-level implementation still ECA-Compliant architecture, by relying on modern software technologies including python-empowered API with Django and its REST framework and Visual-Studio enterprise as advanced IDE. All approach milestones and steps are extensively illustrated using a quite realistic AI-powered software application dealing with Brain Tumor diagnostics while stressing all its benefits, with at-top reliability, dynamic-adaptability, self-learning and understandability
ECA-driven architectural interaction laws, UML and Service-orientation, Machine-Learning (ML), KNN, Brain-Tumor, Reliability and Adaptability, Rewriting Logic, Domain- and A
