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members of the array are of the same class, the dashed, pluralized form of the first element s class name is used as a default Otherwise the default :root is records

Instead of JDBC s result set model where data is presented in rows and columns, JPA deals directly with Java objects and provides facilities for mapping them to relational database tables

B13 active support/core ext/array/

Figure 41 A block diagram for a generic static analysis security tool At a high level, almost all static analysis security tools work this way

Active Support provides a method for extracting Rails-style options from a variablelength set of argument parameters

extract options!

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The rst thing a static analysis tool needs to do is transform the code to be analyzed into a program model, a set of data structures that represent the code As you would expect, the model a tool creates is closely linked to the kind of analysis it performs, but generally static analysis tools borrow a lot from the compiler world In fact, many static analysis techniques were developed by researchers working on compilers and compiler optimization problems If you are interested in an in-depth look at compilers, we recommend both the classic textbook Compilers: Principles, Techniques, and Tools (often called the dragon book ), by Aho, Sethi, and Ullman [Aho et al, 2006], and Appel s Modern Compiler Implementation series (often called the tiger books ) [Appel, 1998] We now take a brief tour of the most important techniques and data structures that compilers and static analysis tools share Lexical Analysis Tools that operate on source code begin by transforming the code into a series of tokens, discarding unimportant features of the program text such as whitespace or comments along the way The creation of the token stream is called lexical analysis Lexing rules often use regular expressions to identify tokens Example 41 gives a simple set of lexing rules that could be used to process the following C program fragment:

Extracts options from a variable set of arguments It s a bang method because it removes and returns the last element in the array if it s a hash; otherwise, it returns a blank hash and the source array is unmodified

def options(*args) argsextract_options! end >> options(1, 2) => {} >> options(1, 2, :a => :b) => {:a=>:b}

Having covered the lower-level JDBC API, we now turn to how to use JPA with SCA components Even though JPA was developed in response to the de ciencies of EJB Entity Beans, its object/relational mapping (O/R) approach to persistence is particularly effective in building loosely coupled, service-based architectures Instead of JDBC s result set model where data is presented in rows and columns, JPA deals directly with Java objects and provides facilities for mapping them to relational database tables Although we assume some familiarity with JPA, we list its main bene ts here: Less code By working with objects and automating much of the mapping process to relational tables, JPA results in less application code than JDBC Less complexity JPA handles tasks such as unique ID generation, versioning (that is, guarding against overlapping updates of the same data by different clients), and entity relationships that typically require complex application code with JDBC Portability Most JPA implementations have built-in features for handling the idiosyncrasies of various databases, making code more portable Performance gains Despite the mapping overhead, JPA implementations can actually improve performance by supporting advanced optimizations, such as delayed ushing and operation batching, that would require complex manual coding if done using JDBC

The in_groups method splits an array into a number of equally sized groups If a fill_with parameter is provided, its value is used to pad the groups into equal sizes

if (ret) // probably true mat[x][y] = END_VAL;

%w(1 2 3 4 ["1", "2", ["5", "6", ["8", "9", %w(1 2 3 4 ["1", "2", ["4", "5", ["6", "7", 5 6 7 8 9 10)in_groups(3) {|group| p group} "3", "4"] "7", nil] "10", nil] 5 6 7)in_groups(3, ' ') {|group| p group} "3"] " "] " "]

In the special case that you don t want equally sized groups (in other words, no padding) then pass false as the value of fill_with

This code produces the following sequence of tokens:

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