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Titlebook: Handbook on Artificial Intelligence-Empowered Applied Software Engineering; VOL.1: Novel Methodo Maria Virvou,George A. Tsihrintzis,Lakhmi

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Book 2022g data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of so
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Synergies Between Artificial Intelligence and Software Engineering: Evolution and Trends experienced a growth in proposals based on the different branches of AI, given rise to novel areas of research and opening new possibilities to industrial practices. For example, search-based software engineering provides algorithms to search for better or optimised solutions to complex tasks in th
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Towards Software Co-Engineering by AI and Developersfers to a complex engineering-product development involving different engineering disciplines. Here, the vision is expanded to include AI and human developers working in collaboration as equal partners to co-create business and social values in software system development and operations. Towards thi
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Generalizing Software Defect Estimation Using Size and Two Interaction Variableslem is further compounded by not having distinctly distinguishable paths for estimation, i.e. if the estimation is at a pre-sales stage, during execution, for and during support, and what is the execution methodology of a software project. It was clear from prior and this work that though the accura
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Harmony Search-Enhanced Software Architecture Reconstructionk adaptation to meet rapidly evolving technology and business requirements, reduced system complexity, and increased system scalability. The quality of software architecture typically degrades due to the application of frequent changes made in source codes to satisfy the user and business requiremen
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Enterprise Architecture-Based Project Model for AI Service System Developmentng a system using AI technologies to support a business task in a company, all project members from both business and IT divisions must have a common understanding of the project to ensure success. Therefore, we propose an enterprise architecture-based business–IT alignment model for AI service syst
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