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Stanford CS 107 - Study Notes

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CS107L Handout 05 Autumn 2007 October 26, 2007 Introduction to C++ Inheritance This handout is a near-verbatim copy of Chapter 14 from this year’s CS106B/X course reader. Those who’ve taken CS106X recently were taught this material, but CS106B skipped over it, and because the chapter is new to the reader as of autumn 2006, those who took CS106 prior were denied inheritance coverage as well. Eric Roberts wrote the first version of the chapter, and Julie Zelenski updated everything last summer to use C++ inheritance. My edits are minimal—all I’ve done is updated the examples to make use of STL containers as opposed to CS106-specific ones. CS106B/X spend a good amount of time on binary search trees, because they serve to explain how trees work. Trees occur in many other programming contexts as well. In particular, trees often show up in the implementation of compilers, because they are ideal for representing the hierarchical structure of a program. By exploring this topic in some detail, you will learn quite a bit, not only about trees, but also about the compilation process itself. Understanding how compilers work removes some of the mystery surrounding programming and makes it easier to understand the programming process as a whole. Unfortunately, designing a complete compiler is far too complex to serve as a useful illustration. Typical commercial compilers require many person-years of programming, much of which is beyond the scope of this text. Even so, it is possible to give you a sense of how they work—and, in particular, of how trees fit into the process—by making the following simplifications: • Having you build an interpreter instead of a compiler. A compiler translates a program into machine-language instructions that the computer can then execute directly. Although it has much in common with a compiler, an interpreter never actually translates the source code into machine language but simply performs the operations necessary to achieve the effect of the compiled program. Interpreters are generally easier to write, but have the disadvantage that interpreted programs tend to run much more slowly than their compiled counterparts. • Focusing only on the problem of evaluating arithmetic expressions. A full-scale language translator for a modern programming language—whether a compiler or an interpreter—must be able to process control statements, function calls, type definitions, and many other language constructs. Most of the fundamental techniques used in language translation, however, are illustrated in the seemingly simple task of translating arithmetic expressions. For the purposes of this handout, arithmetic expressions will be limited to constants and variables combined using the operators +, –, *, /, and = (assignment). As in C++,2 parentheses may be used to define the order of operations, which is otherwise determined by applying precedence rules. • Limiting the types used in expressions to integers. Modern programming languages like C++ allow expressions to manipulate data of many different types. In our version, all data values are assumed to be of type int, which simplifies the structure of the interpreter considerably. Overview of the interpreter The primary goal of this larger example is to show you how to design a program that accepts arithmetic expressions from the user and then displays the results of evaluating those expressions. The basic operation of the interpreter is therefore to execute the following steps repeatedly as part of a loop in the main program: 1. Read in an expression from the user and translate it into an appropriate internal form. 2. Evaluate the expression to produce an integer result. 3. Print the result of the evaluation on the console. This iterated process is characteristic of interpreters and is called a read-eval-print loop. At this level of abstraction, the code for the read-eval-print interpreter is extremely simple. Although the final version of the program will include a little more code than is shown here, the following main program captures the essence of the interpreter: int main(int argc, char *argv[]) { while (true) { Expression *exp = ReadExp(); int value = exp->eval(); cout << value << endl; } return 0; } As you can see, the idealized structure of the main program is simply a loop that calls functions to accomplish each phase of the read-eval-print loop. In this formulation, the task of reading an expression is indicated by a call to the function ReadExp, which will be replaced in subsequent versions of the interpreter program with a somewhat longer sequence of statements. Conceptually, ReadExp is responsible for reading an expression from the user and converting it into its internal representation, which takes the form of an Expression object. The task of evaluating the expression falls to the eval member function, which returns the integer you get if you apply all the operators in the expression in the appropriate order. The print phase of the read-eval-print loop is accomplished by a simple stream insertion to displays the result. The operation of the ReadExp function consists of the three following steps:3 1. Input. The input phase consists of reading in a line of text from the user, which can be accomplished with a simple call to getline. 2. Lexical analysis. The lexical analysis phase consists of dividing user input into individual units called tokens, each of which represents a single logical entity, such as an integer constant, an operator, or a variable name. Fortunately, all the facilities required to implement lexical analysis are provided by an object-oriented version of streamtokenizer type you’ve seen in CS107. (The details of the streamtokenizer are being downplayed here, since the mechanics of tokenizing aren’t all that interesting and isn’t our focus.) 3. Parsing. Once the line has been broken down into its component tokens, the parsing phase consists of determining whether the individual tokens represent a legal expression and, if so, what the structure of that expression is. To do so, the parser must determine how to construct a valid parse tree from the individual tokens in the input. It would be easy enough to implement ReadExp as a single function that combined these steps. In many applications, however, having a ReadExp function is not really what you want. Keeping the individual phases of ReadExp

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