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This document summarizes issues with floating point arithmetic calculations. It discusses how adding very small and very large floating point numbers can result in loss of precision, citing an example from Knuth's The Art of Computer Programming where adding 1 to a number close to 2^127 results in the same value being returned rather than the expected increment. It also provides code examples in Java and Delphi demonstrating how operations like addition, subtraction and division by zero can result in positive or negative infinity or NaN values depending on the language.
This document summarizes issues with floating point arithmetic calculations. It discusses how adding very small and very large floating point numbers can result in loss of precision, citing an example from Knuth's The Art of Computer Programming where adding 1 to a number close to 2^127 results in the same value being returned rather than the expected increment. It also provides code examples in Java and Delphi demonstrating how operations like addition, subtraction and division by zero can result in positive or negative infinity or NaN values depending on the language.