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This open access book presents a set of basic techniques for estimating the benefit of IT development projects and portfolios. It also offers methods for monitoring how much of that estimated benefit is being achieved during projects. Readers can then use these benefit estimates together with cost estimates to create a benefit/cost index to help them decide which functionalities to send into construction and in what order. This allows them to focus on constructing the functionality that offers the best value for money at an early stage. Although benefits management involves a wide range of activities in addition to estimation and monitoring, the techniques in this book provides a clear guide to achieving what has always been the goal of project and portfolio stakeholders: developing systems that produce as much usefulness and value as possible for the money invested. The techniques can also help deal with vicarious motives and obstacles that prevent this happening. The book equips readers to recognize when a project budget should not be spent in full and resources be allocated elsewhere in a portfolio instead. It also provides development managers and upper management with common ground as a basis for making informed decisions.

Mathematical & statistical software --- Software Engineering --- Mathematical Software --- open access --- benefits management --- benefit points --- earned business --- value management --- benefit/costs index --- uncertainty assessment --- periodization --- Desenvolupament de programari --- Anàlisi cost-benefici

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This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

Mathematics. --- Numerical analysis. --- Computer mathematics. --- Computer software. --- Computational Science and Engineering. --- Numeric Computing. --- Mathematical Software. --- Numerical Analysis. --- Software, Computer --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Math --- Mathematics --- Computer systems --- Mathematical analysis --- Science --- Computer science. --- Electronic data processing. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Informatics --- Automation --- Numerical simulations --- programming --- Python

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

Mathematics. --- Numerical analysis. --- Computer mathematics. --- Computer software. --- Computational Science and Engineering. --- Numeric Computing. --- Mathematical Software. --- Numerical Analysis. --- Software, Computer --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Math --- Mathematics --- Computer systems --- Mathematical analysis --- Science --- Computer science. --- Electronic data processing. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Informatics --- Automation --- Computational Science and Engineering --- Numerical Analysis