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After you do these steps, Visual Studio will add a GridView control and a SqlDataSource control to your page, populate them with all the information needed to retrieve the data from the Customers table, and present it in the gridwithout you needing to write a single line of code If you look at your code-behind file at this point, you will see that it is still empty All of the code needed to set up the binding is added in the markup code of the ASPX file itself, as shown in Listing A3



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average-case bound Measurement of running time as an average over all the possible inputs of size N (p 209) Big-Oh The notation used to capture the most dominant term in a function; it is similar to less than or equal to when growth rates are being considered (p 196) Big-Omega The notation similar to greater than or equal to when growth rates are being considered (p 208) Big-Theta The notation similar to equal to when growth rates are being considered (p 208) binary search The search method used if the input array has been sorted and is performed from the middle rather than the end The binary search is logarithmic because the search range is halved in each iteration (p 215) harmonic number The Nth harmonic number is the sum of the reciprocals of the first N positive integers The growth rate of the harmonic numbers is logarithmic (p 21 3) interpolation search A static searching algorithm that has better BigOh performance on average than binary search but has limited practicality and a bad worst case (p 218) linear-time algorithm An algorithm that causes the running time to grow as O(N) If the size of the input increases by a factor ofJI then the running time also increases by a factor o f f It is the preferred running time for an algorithm (p 21 1)





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In the last several chapters, we ve learned about Web service connections and how InfoPath consumes their data In this section, we ll take the next step by looking at two Web service speci c technologies that make using Web services more discoverable and useful in real-world situations First, we ll talk about searching Web services by using UDDI The ability to share and search Web service de nitions fosters a growing and collaborative public community The second extended topic on Web services is the use of ADONET to connect to a database ADONET is a exible and viable alternative to traditional database connections Instead of connecting directly to a database, ADONET adds a middle-tier Web service to abstract the database through the Web service interface We ll provide a sample to guide our discussion

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Little-Oh The notation similar to less than when growth rates are being considered (p 208) logarithm The exponent that indicates the power to which a number is raised to produce a given number For example, the logarithm of N (to the base 2) is the value X such that 2 raised to the power of X equals N (p 21 1 ) repeated doubling principle Holds that, starting at I , repeat doubling can occur only logarithmically many times until N is reached (p 2 13) repeated halving principle Holds that, starting at N, repeated halving can occur only logarithmically many times until I is reached This process is used to obtain logarithmic routines for searching (p 2 13) sequential search A linear search method that steps through an array until a match is found (p 2 14) static search Accesses data that are never altered (p 2 14) subquadratic algorithm An algorithm whose running time is strictly slower than quadratic, which can be written as o(N2) (p 208) worst-case bound A guarantee over all inputs of some size (p 209)

1 For nested loops, the total time is affected by the product of the loop sizes For consecutive loops, it is not 2 Do not just blindly count the number of loops A pair of nested loops that each run from 1 to N2 accounts for O(N4) time 3 Do not write expressions such as O(2N2) or O(N2 + N) Only the dominant term, with the leading constant removed, is needed 4 Use equalities with Big-Oh, Big-Omega, and so onWriting that the running time is > O(N2) makes no sense because Big-Oh is an upper bound Do not write that the running time is < O(N2); if the intention is to say that the running time is strictly less than quadratic, use Little-Oh notation 5 Use Big-Omega, not Big-Oh, to express a lower bound 6 Use the logarithm to describe the running time for a problem solved by halving its size in constant time If more than constant time is required to halve the problem, the logarithm does not apply 7 The base of the logarithm is irrelevant for the purposes of Big-Oh To include it is an error

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