Software Development

Agile and Iterative Development: A Manager's Guide by Craig Larman PDF

By Craig Larman

ISBN-10: 0131111558

ISBN-13: 9780131111554

Agile and iterative tools have emerged because the most well-liked methods to software program improvement, and with reliable cause. learn (examined and pointed out intimately inside this publication) exhibits that iterative equipment decrease the danger of failure, in comparison to conventional versions of improvement. This ebook is an effective creation for either managers and practitioners that want a distilled and thoroughly prepared studying reduction for the hands-on practices from making plans to necessities to trying out and the values that outline those tools. the writer additionally presents facts of the worth of switching to agile and iterative equipment. by means of learning this publication, the reader will learn how to follow the most important principles in agile and iterative improvement, the main points and comparability of 4 influential iterative tools (Scrum, severe Programming, Evo, and the Unified Process), solutions to commonly asked questions, and demanding similar administration abilities. The book's target is caliber details that may be quick understood and utilized.

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Numeric(c("a","4","c")) [1] NA 4 NA Warning message: NAs introduced by coercion If you try to coerce complex numbers to numeric the imaginary part will be discarded. numeric are never both TRUE. frame). A lot of testing involves the NOT operator ! in functions to return an error message if the wrong type is supplied. numeric(x)) stop ("Input must be numeric") if(min(x)<=0) stop ("Input must be greater than zero") exp(mean(log(x))) } Testing this: geometric(c(2,3,0,4)) Error in geometric(c(2, 3, 0, 4)) : Input must be greater than zero But when the data are OK there will be no messages, just the numeric answer: geometric(c(10,1000,10,1,1)) [1] 10 When vectors are created by calculation from other vectors, the new vector will be as long as the longest vector used in the calculation and the shorter variable will be recycled as necessary: here A is of length 10 and B is of length 3: A <- 1:10 B <- c(2,4,8) A * B [1] 2 8 24 8 20 48 14 32 72 20 Warning message: longer object length is not a multiple of shorter object length in: A * B The vector B is recycled three times in full and a warning message in printed to indicate that the length of the longer vector (A) is not a multiple of the shorter vector (B).

Typically therefore, two floating point numbers will not reliably be equal unless they were computed by the same algorithm, and not always even then. You can see this by squaring the square root of 2: surely these values are the same? x <- sqrt(2) x * x == 2 [1] FALSE In fact, they are not the same. 440892e-16 This is not a big number, but it is not zero either. So how do we test for equality of real numbers? The best advice is not to do it. Try instead to use the alternatives ‘less than’ with ‘greater than or equal to’, or conversely ‘greater than’ with ‘less than or equal to’.

Thus * indicates the main effects plus interaction (rather than multiplication), : indicates the interaction between two variables (rather than generate a sequence) and ˆ means all interactions up to the indicated power (rather than raise to the power). You will learn more about these ideas in Chapter 9. 7 Integers Integer vectors exist so that data can be passed to C or Fortran code which expects them, and so that small integer data can be represented exactly and compactly. The range of integers is from −2 000 000 000 to + 2 000 000 000 (-2*10ˆ9 to +2*10ˆ9, which R could portray as -2e+09 to 2e+09).

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Agile and Iterative Development: A Manager's Guide by Craig Larman

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