Nikos Mastorakis – författare

Recent Advances in Numerical Methods features contributions from distinguished researchers focused on significant aspects of current numerical methods and computational mathematics. This volume meets the need in the community for new computational methods that can solve complex scientific and engineering problems by presenting innovative methods that provide numerical solutions in effective computing times. Each chapter presents new and advanced methods and modern variations of known techniques that can solve difficult scientific problems efficiently and quickly.

Recent Advances in Numerical Methods features contributions from distinguished researchers focused on significant aspects of current numerical methods and computational mathematics. This volume meets the need in the community for new computational methods that can solve complex scientific and engineering problems by presenting innovative methods that provide numerical solutions in effective computing times. Each chapter presents new and advanced methods and modern variations of known techniques that can solve difficult scientific problems efficiently and quickly.

The European Computing Conference offers a unique forum for establishing new collaborations within present or upcoming research projects, exchanging useful ideas, presenting recent research results, participating in discussions and establishing new academic collaborations, linking university with the industry. Engineers and Scientists working on various areas of Systems Theory, Applied Mathematics, Simulation, Numerical and Computational Methods and Parallel Computing present the latest findings, advances, and current trends on a wide range of topics. This proceedings volume will be of interest to students, researchers, and practicing engineers.

Software testing has been considered so important that organizations can assign teams only for testing activities. Testing is an important activity to ensure software quality. Tests are usually run several times to certify that code ma- tenance did not accidentally insert defects into working parts of the software. In such situations, test teams shall be able to estimate the required effort to execute test cases in its schedules and to request more resources or negotiate deadlines when necessary. When regarding model-based testing approaches that we use in our documented Integrated and Optimized Software Testing methodology (IOSTP) [1–4], a high number of test cases can be automatically generated. As team resources are limited, it may be not practical to execute all generated test cases. Their complexity usually determines the effort required to execute them and it can be used for planning test resources and test suites. Several software development estimation models have been proposed over the years. However, these models do not estimate the effort for executing a given test suite, since their estimations are based on software development complexity instead of its test planning, test case design and test execution complexity. According to our reading of the literature (e. g. [5–14]), ‘‘best practices’’ in model-based effort estimation include: Local calibration (or LC); i. e. using local data to set two special tuning parameters; Stratification; i. e. given a database of past projects, and a current project to be estimated, restrict local calibration to just those records from similar projects.

Software testing has been considered so important that organizations can assign teams only for testing activities. Testing is an important activity to ensure software quality. Tests are usually run several times to certify that code ma- tenance did not accidentally insert defects into working parts of the software. In such situations, test teams shall be able to estimate the required effort to execute test cases in its schedules and to request more resources or negotiate deadlines when necessary. When regarding model-based testing approaches that we use in our documented Integrated and Optimized Software Testing methodology (IOSTP) [1–4], a high number of test cases can be automatically generated. As team resources are limited, it may be not practical to execute all generated test cases. Their complexity usually determines the effort required to execute them and it can be used for planning test resources and test suites. Several software development estimation models have been proposed over the years. However, these models do not estimate the effort for executing a given test suite, since their estimations are based on software development complexity instead of its test planning, test case design and test execution complexity. According to our reading of the literature (e. g. [5–14]), ‘‘best practices’’ in model-based effort estimation include: Local calibration (or LC); i. e. using local data to set two special tuning parameters; Stratification; i. e. given a database of past projects, and a current project to be estimated, restrict local calibration to just those records from similar projects.

Recent Advances in Numerical Methods features contributions from distinguished researchers focused on significant aspects of current numerical methods and computational mathematics. This volume meets the need in the community for new computational methods that can solve complex scientific and engineering problems by presenting innovative methods that provide numerical solutions in effective computing times. Each chapter presents new and advanced methods and modern variations of known techniques that can solve difficult scientific problems efficiently and quickly.

The European Computing Conference offers a unique forum for establishing new collaborations within present or upcoming research projects, exchanging useful ideas, presenting recent research results, participating in discussions and establishing new academic collaborations, linking university with the industry. Engineers and Scientists working on various areas of Systems Theory, Applied Mathematics, Simulation, Numerical and Computational Methods and Parallel Computing present the latest findings, advances, and current trends on a wide range of topics. This proceedings volume will be of interest to students, researchers, and practicing engineers.

Software testing has been considered so important that organizations can assign teams only for testing activities. Testing is an important activity to ensure software quality. Tests are usually run several times to certify that code ma- tenance did not accidentally insert defects into working parts of the software. In such situations, test teams shall be able to estimate the required effort to execute test cases in its schedules and to request more resources or negotiate deadlines when necessary. When regarding model-based testing approaches that we use in our documented Integrated and Optimized Software Testing methodology (IOSTP) [1–4], a high number of test cases can be automatically generated. As team resources are limited, it may be not practical to execute all generated test cases. Their complexity usually determines the effort required to execute them and it can be used for planning test resources and test suites. Several software development estimation models have been proposed over the years. However, these models do not estimate the effort for executing a given test suite, since their estimations are based on software development complexity instead of its test planning, test case design and test execution complexity. According to our reading of the literature (e. g. [5–14]), ‘‘best practices’’ in model-based effort estimation include: Local calibration (or LC); i. e. using local data to set two special tuning parameters; Stratification; i. e. given a database of past projects, and a current project to be estimated, restrict local calibration to just those records from similar projects.

This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering. Mathematical methods are presented in a unified manner, so they can be applied consistently to problems in applied electromagnetics, strength of materials, fluid mechanics, heat and mass transfer, environmental engineering, biomedical engineering, signal processing, automatic control and more.

This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering. Mathematical methods are presented in a unified manner, so they can be applied consistently to problems in applied electromagnetics, strength of materials, fluid mechanics, heat and mass transfer, environmental engineering, biomedical engineering, signal processing, automatic control and more.

This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering.