1. CS 331, Principles of Programming Languages Chapter 4 Types: Data Representation

2. Data Representation Issues Storage Management –automatic, static Scope Internal vs. External

3. Type Concepts Instances of a type –individual constants, variables, expressions Basic types –built into a language, e.g. float and int in C –instances of basic types are also known as first- class objects User-defined types –defined using type expressions involving existing types

4. Basic and User-defined Types In most modern languages, basic types include integer, real, character, and Boolean Most PLs have two mechanisms for user- defined types, namely array and record

5. Internal vs. External Representations Integers in C are not the same as integers in arithmetic –word length introduces issues related to overflow e.g. -32767..32768 –so some operations don’t act as they should Floats and doubles are not the same as real numbers (or rationals!) –conversion to binary introduces small errors

6. Storage Classes Typically, automatic variables are associated with a given block –allocated (and initialized) when block is entered –known only within that block –freed when block is exited Compare to static variables, which are associated with a given block, but are allocated and initialized only once

7. User-directed Allocation In C, we have malloc and free –memory leaks can be a problem –uninitialized or invalid pointers can be problems In C++ we have constructors and destructors In Pascal and Modula, we have new() and dispose() In Lisp and Java, garbage collection is used

8. Data Aggregates Arrays are homogeneous –all the elements are of the same type Records (known as structs in C) are heterogeneous –components may be of different types Sets are available in languages like Pascal and Modula Type expressions are used to define these

9. Storage Allocation for Arrays Typically, array elements occupy a contiguous block of memory –hence C’s use of subscript 0 For multi-dimensional arrays, there are two schemes –row-major: the rightmost subscript varies fastest –column-major: the leftmost subscript varies

10. Records An example in C In Modula, it would be struct date { int day; int month; int year; } DoB, DoD; TYPE date = RECORD day, month, year: CARDINAL END; VAR DoB, DoD: date;

11. linuxbeta.gl.umbc.edu> cat -n recordeg.mod 1 MODULE recordeg; 2 3 FROM InOut IMPORT WriteLn, WriteCard; 4 5 TYPE date = RECORD 6 day, month, year: CARDINAL 7 END; 8 VAR DoB, DoD: date; 9 10 BEGIN 11 DoB.year := 1808; 12 DoD.year := 1865; 13 WriteCard(DoB.year,10); 14 WriteCard(DoD.year,10); 15 WriteLn; 16 END recordeg. linuxbeta.gl.umbc.edu> source modulasetup linuxbeta.gl.umbc.edu> gpmodula recordeg.mod linuxbeta.gl.umbc.edu> build recordeg linuxbeta.gl.umbc.edu> recordeg 1808 1865 linuxbeta.gl.umbc.edu>

12. Varying Records in C Note that foo.data.I or foo.data.F are defined, but not both Allows data of different types to share storage Polymorphic data types! type enum field_type {integer, real}; struct { ft field_type; union { int I; float F; } data; } foo; if (foo.data.ft == integer) printf(“%d”, foo.data.I); else if (foo.data.ft == real) printf(“%f”, foo.data.F); else printf(“error”);

13. Varying Records in Modula TYPE field_type = {integer, real}; TYPE foo_type = RECORD CASE ft: field_type OF I: INTEGER; F: REAL; END; (* of CASE *) END; (* of RECORD *) VAR foo: foo_type; IF (foo.ft = integer) WriteInt(foo.I) ELSE IF (foo.ft = real) WriteReal(foo.F) ELSE WriteString(“error”);

14. Sets as Types There are situations where sets come in handy –when only certain data values are allowed, e.g. program options or file permissions, and no existing subrange type is appropriate –[Mon..Sun] is not a set (Sethi book has a mistake on p. 123)

15. Example: Sets in Modula or Pascal Operations of membership (IN), union (+), intersection (*), and set difference (-) are common Commonly implemented as bit strings TYPE colors = (white,yellow,blue,green,cyan,black,red); (* note that white < yellow < blue < … < red *) VAR CRT1, CRT2: SET OF colors; VAR testColor: colors; CRT1 := {cyan,yellow,green}; CRT2 := {red,green,blue}; IF (testColor IN CRT1) THEN WriteLn;

16. Type Coercion PLs differ in their approach to type coercion –coercion refers to automatic conversion from one type to another –if a PL is strongly typed, then coercion is restricted and/or explicit –if a PL is weakly typed, then coercion is taken care of by the compiler, which might cause errors –in recent years, the trend is towards strong typing

17. Determining an Object’s Type For static or automatic objects it’s easy –static float x; int y; For other objects it can be hard if (x) float *f = new float[250]; else char *f = new char[1000]; … /* other statements */ /* the following statement must have a semantic error, but at compile time C++ can’t tell which one is wrong since it can’t know x in advance */ cout << sqrt(f[0]) << strlen(f);

18. Static and Dynamic Checking Type checking is needed to make sure operations are well-defined on the objects to which they’re being applied Static type-checking is done once, typically at compile-time Dynamic type-checking is done whenever an operation is applied to an object whose type could not be determined in advance

19. How is Dynamic Type-Checking Done? When an object is created, a “tag” is attached to that object to indicate its type When that object is involved in some operation, the tag is checked to make sure that the operation is defined on such objects A hassle in terms of storage and execution time Smalltalk and other O-O PLs do this, but not C++