Titlebook: Optimising the Software Development Process with Artificial Intelligence; José Raúl Romero,Inmaculada Medina-Bulo,Francisco Book 2023 The

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Aurora Ramírez,Breno Miranda species-level conservation and recovery lens (emphasizing parameters such as critical habitat, abundance, and fecundity). The intersection of these two perspectives remains rare largely due to different disciplinary and professional traditions. This chapter proposes that the concept of the landscap

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Introduction,ption in the 1950s, the complexity of software systems, their environment and infrastructure, the associated requirements, and the methods and methodologies used have increased dramatically. This greater complexity of project management brings a significant increase in the associated risk, which is

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Artificial Intelligence in Software Project Managementquired to develop the software project, creating a software project schedule including allocation of human resources, managing project risks, monitoring progress, etc. Inadequate handling of such activities can thus lead to serious consequences to software companies. However, software project manage

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Statistical Models and Machine Learning to Advance Code Completion: Are We There Yet?coding by filling in the desired code and reducing common mistakes. The early, traditional code completion approaches rely on program analysis to produce a long, alphabetically sorted list of potential suggested code elements. More advanced code completion approaches have leveraged statistical model

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Artificial Intelligence Techniques in System Testing potential for Artificial Intelligence (AI) techniques like machine learning, natural language processing, or search-based optimization to improve the effectiveness and efficiency of system testing. This chapter presents where and how AI techniques can be applied to automate and optimize system test