pl11ch6.pdf

Concepts of Programming Languages Dr. Mohammed A. Awadallah First semester 2022/2023 Chapter 6 Data Types ISBN 0-321—49362-1 Chapter 6 Topics Introduction Primitive Data Types Character String Types Enumeration Types Array Types Ass...

Concepts of Programming Languages Dr. Mohammed A. Awadallah First semester 2022/2023 Chapter 6 Data Types ISBN 0-321—49362-1 Chapter 6 Topics Introduction Primitive Data Types Character String Types Enumeration Types Array Types Associative Arrays Record Types Tuple Types List Types Union Types Pointer and Reference Types Type Checking Strong Typing Type Equivalence Theory and Data Types Copyright © 2015 Pearson. All rights reserved. 1-3 Introduction A data type defines a collection of data objects and a set of predefined operations on those objects A descriptor is the collection of the attributes of a variable – In an implementation, a descriptor is an area of memory that stores the attributes of a variable. – If the attributes are all static, descriptors are required only at compile time. – These descriptors are built by the compiler, usually as a part of the symbol table, and are used during compilation Copyright © 2015 Pearson. All rights reserved. 1-4 Introduction – For dynamic attributes, part or all of the descriptor must be maintained during execution. In this case, the descriptor is used by the run-time system. – In all cases, descriptors are used for type checking and building the code for the allocation and deallocation operations. An object represents an instance of a user- defined (abstract data) type One design issue for all data types: What operations are defined and how are they specified? Copyright © 2015 Pearson. All rights reserved. 1-5 Primitive Data Types Almost all programming languages provide a set of primitive data types Primitive data types: Those not defined in terms of other data types Some primitive data types are merely reflections of the hardware Others require only a little non-hardware support for their implementation Copyright © 2015 Pearson. All rights reserved. 1-6 Primitive Data Types Integer Boolean Types Floating- Primitive Numeric Point Data types Types Complex Character Types Decimal Copyright © 2015 Pearson. All rights reserved. 1-7 Primitive Data Types: Integer Almost always an exact reflection of the hardware so the mapping is trivial The hardware of many computers supports several sizes of integers There may be as many as eight different integer types in a language – Java’s signed integer sizes: byte, short, int, long – C++ and C#, include unsigned integer types, which are types for integer values without signs. Copyright © 2015 Pearson. All rights reserved. 1-8 Primitive Data Types: Floating Point Floating Point data types model real numbers, but the representations are only approximations for many real values. Floating-point problems: – Representation of infinite number (i.e.,π) in finite amount of computer memory. On most computers, floating-point numbers are stored in binary, which exacerbates the problem. E.g., (0.1) 10 = (0000.0001100110011001101) 2 – Floating-point types is the loss of accuracy through arithmetic operations. Copyright © 2015 Pearson. All rights reserved. 1-9 Primitive Data Types: Floating Point Floating-point values are represented as fractions and exponents, a form that is borrowed from scientific notation. – 346.7893 = 3.467893E2 Languages for scientific use support at least two floating-point types (e.g., float and double; sometimes more Copyright © 2015 Pearson. All rights reserved. 1-10 Primitive Data Types: Floating Point float type is the standard size, usually stored in four bytes of memory. Double-precision variables usually occupy twice as much storage as float variables and provide at least twice the number of bits of fraction. Usually exactly like the hardware, but not always Copyright © 2015 Pearson. All rights reserved. 1-11 Primitive Data Types: Floating Point Copyright © 2015 Pearson. All rights reserved. 1-12 Primitive Data Types: Complex Some languages support a complex type, e.g., C99, Fortran, and Python Each value consists of two floats, the real part and the imaginary part Literal form (in Python): (7 + 3j), where 7 is the real part and 3 is the imaginary part Copyright © 2015 Pearson. All rights reserved. 1-13 Primitive Data Types: Decimal For business applications (money) – Essential to COBOL – C# offers a decimal data type Store a fixed number of decimal digits, in coded form Binary Coded Decimal (BCD) Advantage: accuracy – the number 0.1 (in decimal) can be exactly represented in a decimal type, but not in a floating-point type Disadvantages: limited range, wastes memory – because no exponents are allowed Copyright © 2015 Pearson. All rights reserved. 1-14 Primitive Data Types: Boolean Simplest of all Range of values: two elements, one for “true” and one for “false” Boolean types are often used to represent switches or flags in programs. Although other types, such as integers, can be used for these purposes, the use of Boolean types is more readable Could be implemented as bits, but often as bytes Copyright © 2015 Pearson. All rights reserved. 1-15 Primitive Data Types: Boolean C99 and C++ have a Boolean type, they also allow numeric expressions to be used as if they were Boolean. In such expressions, all operands with nonzero values are considered true, and zero is considered false. – Example: If(x=3) –This is not in Java and C# Copyright © 2015 Pearson. All rights reserved. 1-16 Primitive Data Types: Character Character data are stored in computers as numeric codings. Most commonly used coding: American Standard Code for Information Interchange (ASCII) which includes 128 characters An alternative, 16-bit coding: Unicode (UCS-2) – Includes characters from most natural languages – Originally used in Java – C#, JavaScript, Python, Perl, and F# also support Unicode 32-bit Unicode (UCS-4) – Supported by Fortran, starting with 2003 Copyright © 2015 Pearson. All rights reserved. 1-17 Character String Types A character string type is one in which the values consist of sequences of characters. Design issues: – Is it a primitive type or just a special kind of array? – Should the length of strings be static or dynamic? Copyright © 2015 Pearson. All rights reserved. 1-18 Character String Types Operations Typical operations: – Assignment and copying – Comparison (=, >, etc.) – Catenation – Substring reference A substring reference is a reference to a substring of a given string. – Pattern matching Copyright © 2015 Pearson. All rights reserved. 1-19 Character String Types Operations For example, consider the following declaration: char str[] = "apples"; str is an array of char elements, specifically apples0, where 0 is the null character. strcpy, which moves strings; strcat, which catenates one given string onto another strcmp, which lexicographically compares (by the order of their character codes) two given strings. strlen, which returns the number of characters, not counting the null, in the given string Copyright © 2015 Pearson. All rights reserved. 1-20 Character String Types Operations The string manipulation functions of the C standard library, which are also available in C++, are inherently unsafe and have led to numerous programming errors. The problem is that the functions in this library that move string data do not guard against overflowing the destination. For example, consider the following call to strcpy: strcpy(str1, str2); If the length of str1 is 20 and the length of str2 is 50, strcpy will write over the 30 bytes that follow str1. The point is that strcpy does not know the length of str1, so it cannot ensure that the memory following it will not be overwritten. The same problem can occur with several of the other functions in the C string library Copyright © 2015 Pearson. All rights reserved. 1-21 Character String Type in Certain Languages C and C++ – Not primitive – Use char arrays and a library of functions that provide operations SNOBOL4 (a string manipulation language) – Primitive – Many operations, including elaborate pattern matching Fortran and Python – Primitive type with assignment and several operations Java – Primitive via the String class Perl, JavaScript, Ruby, and PHP - Provide built-in pattern matching, using regular expressions Copyright © 2015 Pearson. All rights reserved. 1-22 Character String Length Options 1. Static length strings: COBOL, Python, Java’s String class, Ruby, and the.NET class library available to C# and F# – The length can be static and set when the string is created. 2. Limited Dynamic Length strings: C and C++ – In these languages, a special character is used to indicate the end of a string’s characters, rather than maintaining the length Copyright © 2015 Pearson. All rights reserved. 1-23 Character String Length Options 3. Dynamic (no maximum) length strings: SNOBOL4, Perl, JavaScript, and the standard C++ library – allow strings to have varying length with no maximum. – This kind requires the overhead of dynamic storage allocation and deallocation but provides maximum flexibility. Copyright © 2015 Pearson. All rights reserved. 1-24 Character String Type Evaluation String types are important to the writability of a language. Dealing with strings as arrays can be more cumbersome than dealing with a primitive string type. – For example, consider a language that treats strings as arrays of characters and does not have a predefined function that does what strcpy in C does. – Then, a simple assignment of one string to another would require a loop. Copyright © 2015 Pearson. All rights reserved. 1-25 Character String Type Evaluation Strings as a primitive type to a language is not costly in terms of either language or compiler complexity. As a primitive type with static length, they are inexpensive to provide--why not have them? Dynamic length is nice, but is it worth the expense? Copyright © 2015 Pearson. All rights reserved. 1-26 Character String Implementation Static length: compile-time descriptor – the name of the type. – the type’s length (in characters). – the address of the first character. Copyright © 2015 Pearson. All rights reserved. 1-27 Character String Implementation Limited dynamic length: require a run-time descriptor to store both the fixed maximum length and the current length. – C and C++ do not require run-time descriptors, because the end of a string is marked with the null character. Copyright © 2015 Pearson. All rights reserved. 1-28 Character String Implementation Dynamic length: require a simpler run-time descriptor because only the current length needs to be stored. Dynamic length strings require more complex storage management than others. The length of a string, and therefore the storage to which it is bound, must grow and shrink dynamically. Copyright © 2015 Pearson. All rights reserved. 1-29 Character String Implementation Three approaches to supporting the dynamic allocation and deallocation that is required for dynamic length strings: 1. Linked List. – The drawbacks to this method are the extra storage occupied by the links in the list representation and the necessary complexity of string operations. 2. Arrays of pointers – This method still uses extra memory, but string processing can be faster than with the linked-list Copyright © 2015 Pearson. All rights reserved. 1-30 Character String Implementation 3. Adjacent storage cells – The problem with this method arises when a string grows: How can storage that is adjacent to the existing cells continue to be allocated for the string variable? – This problem solved by moving the string to another storage place. – If no adjacent storage cells enough to store the sting? Copyright © 2015 Pearson. All rights reserved. 1-31 Enumeration Types All possible values, which are named constants, are provided in the definition C# example enum days {mon, tue, wed, thu, fri, sat, sun}; – The enumeration constants are typically implicitly assigned the integer values, 0, 1,... enum days {mon=5, tue, wed, thu, fri, sat, sun}; Copyright © 2015 Pearson. All rights reserved. 1-32 Enumeration Types Design issues – Is an enumeration constant allowed to appear in more than one type definition, and if so, how is the type of an occurrence of that constant checked? – Are enumeration values coerced to integer? – Any other type coerced to an enumeration type? If an enumeration variable is coerced to a numeric type, then there is little control over its range of legal operations or its range of values. If an int type value is coerced to an enumeration type, then an enumeration type variable could be assigned any integer value, whether it represented an enumeration constant or not. Copyright © 2015 Pearson. All rights reserved. 1-33 Enumeration Types In C++, we could have the following: enum colors {red, blue, green, yellow, black}; colors myColor = blue, yourColor = red; The expresion myColor++, would assign green to myColor. The expression myColor = 4, is illegal in C++. C# enumeration types are like those of C++, except that they are never coerced to integer. Copyright © 2015 Pearson. All rights reserved. 1-34 Enumeration Types In ML, enumeration types are defined as new types with datatype declarations. datatype weekdays = Monday | Tuesday | Wednesday | Thursday | Friday The type of the elements of weekdays is integer. F# has enumeration types that are similar to those of ML, except the reserved word type is used instead of datatype and the first value is preceded by an OR operator (|). Copyright © 2015 Pearson. All rights reserved. 1-35 Enumeration Types Interestingly, none of the relatively recent scripting languages include enumeration types. These include Perl, JavaScript, PHP, Python, Ruby, and Lua. Even Java was a decade old before enumeration types were added. public enum DayOfWeek { SUNDAY, MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY, SATURDAY } public enum DayOfWeek { SUNDAY(0), MONDAY(1), TUESDAY(2), WEDNESDAY(3), THURSDAY(4), FRIDAY(5), SATURDAY(6) } Copyright © 2015 Pearson. All rights reserved. 1-36 Enumeration Types public class Main { enum Level { LOW, MEDIUM, HIGH } public static void main(String[] args) { Level myVar = Level.MEDIUM; System.out.println(myVar); } } Copyright © 2015 Pearson. All rights reserved. 1-37 Evaluation of Enumerated Type Aid to readability, e.g., no need to code a color as a number Aid to reliability, e.g., compiler can check: – operations (don’t allow colors to be added) – No enumeration variable can be assigned a value outside its defined range – C# and Java 5.0 provide better support for enumeration than C++ because enumeration type variables in these languages are not coerced into integer types Copyright © 2015 Pearson. All rights reserved. 1-38 Evaluation of Enumerated Type enum colors {red =1, blue =1000, green =100000} In this example, a value assigned to a variable of colors type will only be checked to determine whether it is in the range of 1...100000. Copyright © 2015 Pearson. All rights reserved. 1-39 Array Types An array is a homogeneous aggregate of data elements in which an individual element is identified by its position in the aggregate, relative to the first element. The individual data elements of an array are of the same type. References to individual array elements are specified using subscript expressions Copyright © 2015 Pearson. All rights reserved. 1-40 Array Design Issues What types are legal for subscripts? Are subscripting expressions in element references range checked? When are subscript ranges bound? When does allocation take place? Are ragged or rectangular multidimensional arrays allowed, or both? What is the maximum number of subscripts? Can array objects be initialized? Are any kind of slices supported? Copyright © 2015 Pearson. All rights reserved. 1-41 Array Indexing Indexing (or subscripting) is a mapping from indices to elements array_name (index_value_list) → an element Index Syntax – Fortran and Ada use parentheses Ada explicitly uses parentheses to show uniformity between array references and function calls because both are mappings. (This reduced the readability) Sum := Sum + B(I); – Most other languages use brackets Copyright © 2015 Pearson. All rights reserved. 1-42 Arrays Index (Subscript) Types Two distinct types are involved in an array type: the element type and the type of the subscripts. The type of the subscripts is often integer. – E.g. double temp; (elements type is double) – Temp = 70.8; (3 is index) FORTRAN, C: integer only Java: integer types only (byte, short, int, and long) Copyright © 2015 Pearson. All rights reserved. 1-43 Arrays Index (Subscript) Types Index range checking – C, C++, Perl, and Fortran do not specify range checking – Java, ML, C# specify range checking – For example in Perl, for the array @list, the second element is referenced with $list. – One can reference an array element in Perl with a negative subscript, in which case the subscript value is an offset from the end of the array. $list[-2]. Copyright © 2015 Pearson. All rights reserved. 1-44 Subscript Binding and Array Categories The binding of the subscript type to an array variable is usually static, but the subscript value ranges are sometimes dynamically bound. In some languages, the lower bound of the subscript range is implicit. For example, in the C- based languages, the lower bound of all subscript ranges is fixed at 0. In some other languages, the lower bounds of the subscript ranges must be specified by the programmer. Copyright © 2015 Pearson. All rights reserved. 1-45 Subscript Binding and Array Categories 1. Static: subscript ranges are statically bound and storage allocation is static (before run-time) – Advantage: efficiency (i.e. No dynamic allocation or deallocation is required) – The disadvantage is that the storage for the array is fixed for the entire execution time of the program. Copyright © 2015 Pearson. All rights reserved. 1-46 Subscript Binding and Array Categories 2. Fixed stack-dynamic: subscript ranges are statically bound, but the allocation is done at execution time – Advantage: space efficiency large array in one subprogram can use the same space as a large array in a different subprogram, as long as both subprograms are not active at the same time. – The disadvantage is the required allocation and deallocation time Copyright © 2015 Pearson. All rights reserved. 1-47 Subscript Binding and Array Categories 3. Fixed heap-dynamic: is similar to a fixed stack- dynamic array, in that the subscript ranges and the storage binding are both fixed after storage is allocated. – The differences are that both the subscript ranges and storage bindings are done when the user program requests them during execution, – The storage is allocated from the heap, rather than the stack. – Advantage: flexibility – Disadvantages: allocation time from the heap, which is longer than allocation time from the stack. Copyright © 2015 Pearson. All rights reserved. 1-48 Subscript Binding and Array Categories 4. Heap-dynamic: binding of subscript ranges and storage allocation is dynamic and can change any number of times during the array’s lifetime. – Advantage: flexibility (arrays can grow or shrink during program execution as the need for space changes) – Disadvantages: is that allocation and deallocation take longer and may happen many times during execution of the program. Copyright © 2015 Pearson. All rights reserved. 1-49 Subscript Binding and Array Categories C and C++ arrays that include static modifier are static C and C++ arrays without static modifier are fixed stack-dynamic C and C++ provide fixed heap-dynamic arrays (By using new and delete ) In Java, arrays are fixed heap-dynamic. C# provides fixed heap-dynamic. C# includes a second array class ArrayList that provides fixed heap-dynamic Perl, JavaScript, Python, and Ruby support heap- dynamic arrays Copyright © 2015 Pearson. All rights reserved. 1-50 Array Initialization Some language allow initialization at the time of storage allocation – C, C++, Java, C# example int list [] = {4, 5, 7, 83} – Character strings in C and C++ char name [] = ″freddie″; The array name will have eight elements, because all strings are terminated with a null character (zero) – Arrays of strings in C and C++ char *names [] = {″Bob″, ″Jake″, ″Joe″]; – Java initialization of String objects String[] names = {″Bob″, ″Jake″, ″Joe″}; Copyright © 2015 Pearson. All rights reserved. 1-51 Heterogeneous Arrays A heterogeneous array is one in which the elements need not be of the same type Supported by Perl, Python, JavaScript, and Ruby Example in Python: mixedList = [1, 2, "three", 4] Copyright © 2015 Pearson. All rights reserved. 1-52 Arrays Operations APL provides the most powerful array processing operations for vectors and matrixes as well as unary operators (for example, to reverse column elements) The C-based languages do not provide any array operations. Perl supports array assignments but does not support comparisons. Python’s array assignments, but they are only reference changes. Python also supports array catenation and element membership operations Ruby also provides array catenation Copyright © 2015 Pearson. All rights reserved. 1-53 Arrays Operations In APL , the four basic arithmetic operations are defined for vectors (single-dimensioned arrays) and matrices. C = A * B C = A + B APL includes a collection of unary operators for vectors and matrices, some of which are as follows (where V is a vector and M is a matrix): ϕV reverses the elements of V ϕM reverses the columns of M θM reverses the rows of M ØM transposes M (its rows become its columns and vice versa) ÷M inverts M Copyright © 2015 Pearson. All rights reserved. 1-54 Rectangular and Jagged Arrays A rectangular array is a multi-dimensioned array in which all of the rows have the same number of elements and all columns have the same number of elements A jagged matrix has rows with varying number of elements – Possible when multi-dimensioned arrays actually appear as arrays of arrays C, C++, and Java support jagged arrays F# and C# support rectangular arrays and jagged arrays Copyright © 2015 Pearson. All rights reserved. 1-55 Rectangular and Jagged Arrays Jagged Arrays myarray Copyright © 2015 Pearson. All rights reserved. 1-56 Slices A slice is some substructure of an array; nothing more than a referencing mechanism Slices are only useful in languages that have array operations For example, if A is a matrix, then the first row of A is one possible slice, as are the last row and the first column. Copyright © 2015 Pearson. All rights reserved. 1-57 Slice Examples Python vector = [2, 4, 6, 8, 10, 12, 14, 16] mat = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] vector (3:6) is a three-element array (those elements with the subscripts 3, 4, and 5) mat[0:2] is the first and second element of the first row of mat Ruby supports slices with the slice method list.slice(2, 2) returns the third and fourth elements of list Copyright © 2015 Pearson. All rights reserved. 1-58 Slice Examples Fortran 95 Copyright © 2015 Pearson. All rights reserved. 1-59 Implementation of Arrays Access function maps subscript expressions to an address in the array Access function for single-dimensioned arrays: address(list[k]) = address (list[lower_bound]) + ((k-lower_bound) * element_size) List List List List List Copyright © 2015 Pearson. All rights reserved. 1-60 Accessing Single-dimensioned Arrays The descriptor includes information required to construct the access function. A compile-time descriptor for a Single- dimensional array Copyright © 2015 Pearson. All rights reserved. 1-61 Accessing Multi-dimensioned Arrays Two common ways: – Row major order (by rows) – used in most languages For example, if the matrix had the values 347 625 138 it would be stored in row major order as 3, 4, 7, 6, 2, 5, 1, 3, 8 – Column major order (by columns) – used in Fortran Copyright © 2015 Pearson. All rights reserved. 1-62 Accessing Multi-dimensioned Arrays A compile-time descriptor for a Multi-dimensional array Copyright © 2015 Pearson. All rights reserved. 1-63 Locating an Element in a Multi- dimensioned Array General format Location (a[i,j]) = address of a [row_lb,col_lb] + (((i - row_lb) * n) + (j - col_lb)) * element_size Copyright © 2015 Pearson. All rights reserved. 1-64 Compile-Time Descriptors Single-dimensioned array Multi-dimensional array Copyright © 2015 Pearson. All rights reserved. 1-65 Associative Arrays An associative array is an unordered collection of data elements that are indexed by an equal number of values called keys – User-defined keys must be stored Design issues: - What is the form of references to elements? - Is the size static or dynamic? Built-in type in Perl, Python, Ruby, and Lua – In Lua, they are supported by tables Copyright © 2015 Pearson. All rights reserved. 1-66 Associative Arrays in Perl Associative arrays in Perl are called hashes, because in the implementation their elements are stored and retrieved with hash functions. – Every hash variable name must begin with a percent sign (%). – Each hash element consists of two parts: a key, which is a string, a value, which is a scalar (number, string, or reference). Copyright © 2015 Pearson. All rights reserved. 1-67 Associative Arrays in Perl Names begin with %; literals are delimited by parentheses %hi_temps=("Mon" => 77, "Tue" => 79, "Wed" => 65, …); Subscripting is done using braces and keys $hi_temps{"Wed"} = 83; – Elements can be removed with delete delete $hi_temps{"Tue"}; – Elements can be added using $hi_temps{“Sun”} = 75; – To empty array using $hi_temps = (); Copyright © 2015 Pearson. All rights reserved. 1-68 Associative Arrays in Perl The exists operator returns true or false, depending on whether its operand key is an element in the hash. if (exists $salaries{"Shelly"}) The size of a Perl hash is dynamic, It grows when an element is added and shrinks when an element is deleted, and also when it is emptied by assignment of the empty literal. Python’s associative arrays, which are called dictionaries, are similar to those of Perl, except the values are all references to objects. The keys in PHP’s arrays, can be integers or strings. Copyright © 2015 Pearson. All rights reserved. 1-69 Dictionaries in Python thisdict = { "brand": "Ford", "electric": False, "year": 1964, "colors": ["red", "white", "blue"] } print(thisdict) Output {'brand': 'Ford', 'electric': False, 'year': 1964, 'colors': ['red', 'white', 'blue']} Copyright © 2015 Pearson. All rights reserved. 1-70 Record Types A record is a possibly heterogeneous aggregate of data elements in which the individual elements are identified by names The individual elements in the record are not of the same type or size. For example, information about a college student might include name, student number, grade point average, and so forth. Copyright © 2015 Pearson. All rights reserved. 1-71 Record Types In C, C++, and C#, records are supported with the struct data type. – In C++, structures are a minor variation on classes. – C# structs are stack-allocated value types, as opposed to class objects, which are heap-allocated reference types. – In Python and Ruby, records can be implemented as hashes, which themselves can be elements of arrays. Design issues: – What is the syntactic form of references to the field? – Are elliptical references allowed Copyright © 2015 Pearson. All rights reserved. 1-72 Record Types The main difference between Arrays and Records: – The fundamental difference between a record and an array is that record elements, or fields, are not referenced by indices. – Another difference between arrays and records is that records in some languages are allowed to include unions. Copyright © 2015 Pearson. All rights reserved. 1-73 Definition of Records in COBOL COBOL uses level numbers to show nested records; others use recursive definition 01 EMP-REC. 02 EMP-NAME. 05 FIRST PIC X(20). 05 MID PIC X(10). 05 LAST PIC X(20). 02 HOURLY-RATE PIC 99V99. – The PIC clauses show the formats of the field storage locations, with X(20)specifying 20 alphanumeric characters and 99V99 specifying four decimal digits with the decimal point in the middle. Copyright © 2015 Pearson. All rights reserved. 1-74 Definition of Records Record structures are indicated in an orthogonal way type Emp_Rec_Type is record First: String (1..20); Mid: String (1..10); Last: String (1..20); Hourly_Rate: Float; end record; Emp_Rec: Emp_Rec_Type; Copyright © 2015 Pearson. All rights reserved. 1-75 References to Records Record field references 1. COBOL field_name OF record_name_1 OF... OF record_name_n 2. Others (dot notation) record_name_1.record_name_2.... record_name_n.field_name Fully qualified references must include all record names Elliptical references allow leaving out record names as long as the reference is unambiguous, for example in COBOL FIRST, FIRST OF EMP-NAME, and FIRST of EMP-REC are elliptical references to the employee’s first name Copyright © 2015 Pearson. All rights reserved. 1-76 Evaluation and Comparison to Arrays Records are used when collection of data values is heterogeneous Access to array elements is much slower than access to record fields, because subscripts are dynamic (field names are static) Dynamic subscripts could be used with record field access, but it would disallow type checking and it would be much slower Copyright © 2015 Pearson. All rights reserved. 1-77 Implementation of Record Type Offset address relative to the beginning of the records is associated with each field Copyright © 2015 Pearson. All rights reserved. 1-78 Tuple Types A tuple is a data type that is similar to a record, except that the elements are not named Used in Python, ML, and F# to allow functions to return multiple values – Python Closely related to its lists, but immutable Create with a tuple literal myTuple = (3, 5.8, ′apple′) Referenced with subscripts (begin at 1) myTuple Catenation with + and deleted with del Copyright © 2015 Pearson. All rights reserved. 1-79 Tuple Types Adding an element to tuple in Python t = ('a', 4, 'string') t = t + (5.0,) print(t) out: ('a', 4, 'string', 5.0) Copyright © 2015 Pearson. All rights reserved. 1-80 Tuple Types (continued) ML val myTuple = (3, 5.8, ′apple′); - Access as follows: #1(myTuple) is the first element - A new tuple type can be defined type intReal = int * real; ❑ Values of this type consist of an integer and a real. F# let tup = (3, 5, 7) let a, b, c = tup This assigns a tuple to a tuple pattern (a, b, c) Copyright © 2015 Pearson. All rights reserved. 1-81 List Types Lists in Lisp and Scheme are delimited by parentheses and use no commas (A B C D) and (A (B C) D) Data and code have the same form As data, (A B C) is literally what it is As code, (A B C) is the function A applied to the parameters B and C The interpreter needs to know which a list is, so if it is data, we quote it with an apostrophe ′(A B C) is data Copyright © 2015 Pearson. All rights reserved. 1-82 List Types (continued) List Operations in Scheme – CAR returns the first element of its list parameter (CAR ′(A B C)) returns A – CDR returns the remainder of its list parameter after the first element has been removed (CDR ′(A B C)) returns (B C) - CONS puts its first parameter into its second parameter, a list, to make a new list (CONS ′A (B C)) returns (A B C) - LIST returns a new list of its parameters (LIST ′A ′B ′(C D)) returns (A B (C D)) Copyright © 2015 Pearson. All rights reserved. 1-83 List Types (continued) List Operations in ML – Lists are written in brackets and the elements are separated by commas – List elements must be of the same type – The Scheme CONS function is a binary operator in ML, :: 3 :: [5, 7, 9] evaluates to [3, 5, 7, 9] – The Scheme CAR and CDR functions are named hd and tl, respectively hd [5, 7, 9] is 5 tl [5, 7, 9] is [7, 9] Copyright © 2015 Pearson. All rights reserved. 1-84 List Types (continued) F# Lists – Like those of ML, except elements are separated by semicolons and hd and tl are methods of the List class List.hd [1; 3; 5; 7], which returns 1 Python Lists – The list data type also serves as Python’s arrays – Unlike Scheme, Common Lisp, ML, and F#, Python’s lists are mutable – Elements can be of any type – Create a list with an assignment myList = [3, 5.8, "grape"] Copyright © 2015 Pearson. All rights reserved. 1-85 List Types (continued) Python Lists (continued) – List elements are referenced with subscripting, with indices beginning at zero x = myList Sets x to 5.8 – List elements can be deleted with del del myList – List Comprehensions – derived from set notation [x * x for x in range(6) if x % 3 == 0] creates [0, 1, 2, 3, 4, 5, 6] range(6) Constructed list: [0, 9, 36] Copyright © 2015 Pearson. All rights reserved. 1-86  List Types (continued) Haskell’s List Comprehensions – The original [n * n | n (i * i) |] This statement creates the array [1; 4; 9; 16; 25] and names it myArray. Both C# and Java supports lists through their generic heap-dynamic collection classes, List and ArrayList, respectively Copyright © 2015 Pearson. All rights reserved. 1-87 Unions Types A union is a type whose variables are allowed to store different type values at different times during execution Design issue – Should type checking be required? – Should unions be embedded in records? Copyright © 2015 Pearson. All rights reserved. 1-88 Unions Types int int Copyright © 2015 Pearson. All rights reserved. 1-89 Discriminated vs. Free Unions C and C++ provide union constructs in which there is no language support for type checking; the union in these languages is called free union Type checking of unions require that each union include a type indicator called a discriminant – Supported by ML, Haskell, and F# Copyright © 2015 Pearson. All rights reserved. 1-90 Unions in C union flexType { int intEl; float floatEl; }; flexType el1; float x;... This last assignment is not type checked, because the system cannot determine the el1.intEl = 27; current type of the current value of el1, so it assigns the bit string representation x = el1.floatEl; of 27 to the float variable x, which of course is nonsense. Copyright © 2015 Pearson. All rights reserved. 1-91 Unions in F# Defined with a type statement using OR type intReal = | IntValue of int | RealValue of float;; intReal is the new type IntValue and RealValue are constructors To create a value of type intReal: let ir1 = IntValue 17;; let ir2 = RealValue 3.4;; Copyright © 2015 Pearson. All rights reserved. 1-92 Unions in F# (continued) Accessing the value of a union is done with pattern matching match pattern with | expression_list1 -> expression1 | … | expression_listn -> expressionn - Pattern can be any data type - The expression list can have wild cards (_) Copyright © 2015 Pearson. All rights reserved. 1-93 Unions in F# (continued) Example: let a = 7;; let b = ″grape″;; let x = match (a, b) with | 4, ″apple″ -> apple | _, ″grape″ -> grape | _ -> fruit;; Copyright © 2015 Pearson. All rights reserved. 1-94 Unions in F# (continued) To display the type of the intReal union: let printType value = match value with | IntVale value -> printfn ″int″ | RealValue value -> printfn ″float″;; If ir1 and ir2 are defined as previously, printType ir1 returns int printType ir2 returns float let ir1 = IntValue 17;; let ir2 = RealValue 3.4;; Copyright © 2015 Pearson. All rights reserved. 1-95 Evaluation of Unions Free unions are unsafe – Do not allow type checking unions can be safely used, as in their design in ML, Haskell, and F#. Java and C# do not support unions – Reflective of growing concerns for safety in programming language Copyright © 2015 Pearson. All rights reserved. 1-96 Pointer and Reference Types A pointer type variable has a range of values that consists of memory addresses and a special value, nil The value nil is not a valid address and is used to indicate that a pointer cannot currently be used to reference a memory cell. Provide the power of indirect addressing Provide a way to manage dynamic memory A pointer can be used to access a location in the area where storage is dynamically created (usually called a heap) Copyright © 2015 Pearson. All rights reserved. 1-97 Pointer and Reference Types Pointers, unlike arrays and records, are not structured types, although they are defined using a type operator (* in C and C++). They are also different from scalar variables because they are used to reference some other variable, rather than being used to store data. Two categories of variables are called reference types and value types. Copyright © 2015 Pearson. All rights reserved. 1-98 Design Issues of Pointers What are the scope of and lifetime of a pointer variable? What is the lifetime of a heap-dynamic variable? Are pointers restricted as to the type of value to which they can point? Are pointers used for dynamic storage management, indirect addressing, or both? Should the language support pointer types, reference types, or both? Copyright © 2015 Pearson. All rights reserved. 1-99 Pointer Operations Two fundamental operations: assignment and dereferencing Assignment is used to set a pointer variable’s value to some useful address Dereferencing yields the value stored at the location represented by the pointer’s value – Dereferencing can be explicit or implicit In languages that support object-oriented programming, allocation of heap objects is specified with the new operator. C++, which does not provide implicit deallocation, uses delete as its deallocation operator. Copyright © 2015 Pearson. All rights reserved. 1-100 Pointer Assignment Illustrated C++ uses an explicit operation via * j = *ptr sets j to the value located at ptr Copyright © 2015 Pearson. All rights reserved. 1-101 Problems with Pointers 1. Dangling pointers (dangerous) – A pointer points to a heap-dynamic variable that has been deallocated Copyright © 2015 Pearson. All rights reserved. 1-102 Problems with Pointers Dangling pointers are dangerous for several reasons. – If the new variable is not the same type as the old one, type checks of uses of the dangling pointer are invalid. – If the new dynamic variable is the same type, its new value will have no relationship to the old pointer’s dereferenced value. – If the dangling pointer is used to change the heap- dynamic variable, the value of the new heap-dynamic variable will be destroyed. – it is possible that the location now is being temporarily used by the storage management system, possibly as a pointer in a chain of available blocks of storage, thereby allowing a change to the location to cause the storage manager to fail. Copyright © 2015 Pearson. All rights reserved. 1-103 Problems with Pointers 2. Lost heap-dynamic variable – An allocated heap-dynamic variable that is no longer accessible to the user program (often called garbage) Pointer p1 is set to point to a newly created heap- dynamic variable Pointer p1 is later set to point to another newly created heap-dynamic variable The process of losing heap-dynamic variables is called memory leakage Copyright © 2015 Pearson. All rights reserved. 1-104 Pointers in C and C++ Extremely flexible but must be used with care Pointers can point at any variable regardless of when or where it was allocated Used for dynamic storage management and addressing Pointer arithmetic is possible Explicit dereferencing and address-of operators Domain type need not be fixed (void *) void * can point to any type and can be type checked (cannot be de-referenced) Copyright © 2015 Pearson. All rights reserved. 1-105 Pointer Arithmetic in C and C++ int *ptr; int count, init; ptr count... ptr = &init; 5 count = *ptr; init 5 float stuff; float *p; p = stuff; *(p+5) is equivalent to stuff and p *(p+i) is equivalent to stuff[i] and p[i] Copyright © 2015 Pearson. All rights reserved. 1-106 Pointer Arithmetic in C and C++ Some recent languages, such as Java, have replaced pointers completely with reference types, which, along with implicit deallocation, minimize the primary problems with pointers. A reference type is really only a pointer with restricted operations. Copyright © 2015 Pearson. All rights reserved. 1-107 Reference Types A reference type variable is similar to a pointer, with one difference: – A pointer refers to an address in memory, – reference refers to an object or a value in memory. C++ includes a special kind of pointer type called a reference type that is used primarily for formal parameters – Advantages of both pass-by-reference and pass-by-value int result = 0; int &ref_result = result;... ref_result = 100; In this code segment, result and ref_result are aliases. Copyright © 2015 Pearson. All rights reserved. 1-108 Reference Types Java extends C++’s reference variables and allows them to replace pointers entirely – References are references to objects, rather than being addresses String str1;... str1 = "This is a Java literal string"; – In this code, str1 is defined to be a reference to a String class instance or object. It is initially set to null. – The subsequent assignment sets str1 to reference the String object, "This is a Java literal string". Copyright © 2015 Pearson. All rights reserved. 1-109 Reference Types C# includes both the references of Java and the pointers of C++ All variables in the object-oriented languages Smalltalk, Python, Ruby, and Lua are references. They are always implicitly dereferenced. Copyright © 2015 Pearson. All rights reserved. 1-110 Evaluation of Pointers Dangling pointers and dangling objects are problems as is heap management Pointers are like goto's--they widen the range of cells that can be accessed by a variable Pointers or references are necessary for dynamic data structures--so we can't design a language without them The references of Java and C# provide some of the flexibility and the capabilities of pointers, without the hazards. Copyright © 2015 Pearson. All rights reserved. 1-111 Representations of Pointers In most larger computers, pointers and references are single values stored in memory cells. Intel microprocessors use segment and offset Copyright © 2015 Pearson. All rights reserved. 1-112 Solutions of Dangling Pointer Problem 1. Tombstone: every heap-dynamic variable includes a special cell, called a tombstone, that is itself a pointer to the heap-dynamic variable. – The actual pointer variable points only at tombstones – When heap-dynamic variable de-allocated, tombstone remains but set to nil, indicating that the heap-dynamic variable no longer exists. – Costly in time and space Copyright © 2015 Pearson. All rights reserved. 1-113 Solutions of Dangling Pointer Problem 1. Tombstone: (continued) Costly in time and space ▪ tombstones are never deallocated, their storage is never reclaimed. ▪ Every access to a heap-dynamic variable through a tombstone requires one more level of indirection. ▪ no widely used for the most of the programming languages. Copyright © 2015 Pearson. All rights reserved. 1-114 Solutions of Dangling Pointer Problem 2. Locks-and-keys: Pointer values are represented as (key, address) pairs – Heap-dynamic variables are represented as variable plus cell for integer lock value – When a heap-dynamic variable is allocated, a lock value is created and placed both in the lock cell of the heap- dynamic variable and in the key cell of the pointer that is specified in the call to new. – Every access to the dereferenced pointer compares the key value of the pointer to the lock value in the heap- dynamic variable. If they match, the access is legal; otherwise the access is treated as a run-time error. Copyright © 2015 Pearson. All rights reserved. 1-115 Solutions of Dangling Pointer Problem 2. Locks-and-keys: (continued) – Any copies of the pointer value to other pointers must copy the key value. – When a heap- dynamic variable is deallocated with dispose, its lock value is cleared to an illegal lock value. – Then, if a pointer other than the one specified in the dispose is dereferenced, its address value will still be intact, but its key value will no longer match the lock, so the access will not be allowed. – Lisp, Java and C# use this approach for their reference variables Copyright © 2015 Pearson. All rights reserved. 1-116 Solutions of Dangling Pointer Problem ptr1 12378 12378 ptr1 12378 12378 ptr2 12378 ptr1 12378 0 nil ptr2 12378 Copyright © 2015 Pearson. All rights reserved. 1-117 Heap Management A very complex run-time process Two separate situations: all heap storage is allocated and deallocated in units of Single-size or variable-size. Single-size cells Two approaches to reclaim garbage – Reference counters (eager approach): reclamation is gradual – Mark-sweep (lazy approach): reclamation occurs when the list of variable space becomes empty Copyright © 2015 Pearson. All rights reserved. 1-118 Reference Counter Reference counters: maintain a counter in every cell that store the number of pointers currently pointing at the cell If the reference counter reaches zero, it means that no program pointers are pointing at the cell, and it has thus become garbage and can be returned to the list of available space. Advantage: it is intrinsically incremental, so significant delays in the application execution are avoided Copyright © 2015 Pearson. All rights reserved. 1-119 Reference Counter Disadvantages: – space required for the counters is significant for each cell. – execution time required to maintain the counter values. – complications for cells connected circularly. The problem here is that each cell in the circular list has a reference counter value of at least 1, which prevents it from being collected and placed back on the list of available space. Copyright © 2015 Pearson. All rights reserved. 1-120 Mark-Sweep The run-time system allocates storage cells as requested and disconnects pointers from cells as necessary; mark-sweep then begins – Every heap cell has an extra bit used by collection algorithm – All cells initially set to garbage – All pointers traced into heap, and reachable cells marked as not garbage – All garbage cells returned to list of available cells Copyright © 2015 Pearson. All rights reserved. 1-121 Mark-Sweep The mark- sweep process consists of three distinct phases. – The first phase: all cells in the heap have their indicators set to indicate they are garbage. – The second phase: called the marking phase, Every pointer in the program is traced into the heap, and all reachable cells are marked as not being garbage. – The third phase, called the sweep phase, is executed: All cells in the heap that have not been specifically marked as still being used are returned to the list of available space. Copyright © 2015 Pearson. All rights reserved. 1-122 Mark-Sweep Copyright © 2015 Pearson. All rights reserved. 1-123 Marking Algorithm The method reverses pointers as it traces out linked structures. Copyright © 2015 Pearson. All rights reserved. 1-124 Mark-Sweep Disadvantages: in its original form, it was done too infrequently. – a significant delay in the progress of the application to find the available cells. – Contemporary mark-sweep algorithms avoid this by doing it more often—called incremental mark-sweep Incremental mark-sweep garbage collection occurs more frequently, long before memory is exhausted, making the process more effective in terms of the amount of storage that is reclaimed. Furthermore, time of required for each run of the process. to perform the mark-sweep process on parts, rather than all of the memory associated with the application, at different times. Copyright © 2015 Pearson. All rights reserved. 1-125 Variable-Size Cells All the difficulties of single-size cells plus more Required by most programming languages If mark-sweep is used, additional problems occur – The initial setting of the indicators of all cells in the heap is difficult Because the cells are different sizes, scanning them is a problem. solution is to require each cell to have the cell size as its first field. Some times need more time than its counterpart for fixed-size cells. – The marking process in nontrivial – Maintaining the list of available space is another source of overhead Copyright © 2015 Pearson. All rights reserved. 1-126 Variable-Size Cells (continued) – Maintaining the list of available space is another source of overhead The list can begin with a single cell consisting of all available space. Requests for segments simply reduce the size of this block. Reclaimed cells are added to the list. The problem is that before long, the list becomes a long list of various-size segments, or blocks. This slows allocation because requests cause the list to be searched for sufficiently large blocks. Eventually, the list may consist of a large number of very small blocks, which are not large enough for most requests. At this point, adjacent blocks may need to be collapsed into larger blocks. Copyright © 2015 Pearson. All rights reserved. 1-127 Type Checking Generalize the concept of operands and operators to include subprograms and assignments Type checking is the activity of ensuring that the operands of an operator are of compatible types A compatible type is one that is either legal for the operator, or is allowed under language rules to be implicitly converted, by compiler- generated code, to a legal type – This automatic conversion is called a coercion. For example, if an int variable and a float variable are added in Java, the value of the int variable is coerced to float and a floating-point add is done. Copyright © 2015 Pearson. All rights reserved. 1-128 Type Checking (continued) A type error is the application of an operator to an operand of an inappropriate type For example, in the original version of C, if an int value was passed to a function that expected a float value, a type error would occur. – Because compilers for that language did not check the types of parameters. Copyright © 2015 Pearson. All rights reserved. 1-129 Type Checking (continued) If all type bindings are static, nearly all type checking can be static If type bindings are dynamic, type checking must be dynamic – JavaScript and PHP, because of their dynamic type binding, allow only dynamic type checking. It is better to detect errors at compile time than at run time, because the earlier correction is usually less costly. Copyright © 2015 Pearson. All rights reserved. 1-130 Type Checking (continued) Type checking is complicated when a language allows a memory cell to store values of different types at different times during execution. – Such memory cells can be created with C and C++ unions and the discriminated unions of ML, Haskell, and F#. – In these cases, type checking, if done, must be dynamic and requires the run-time system to maintain the type of the current value of such memory cells. Copyright © 2015 Pearson. All rights reserved. 1-131 Strong Typing A programming language is strongly typed if type errors are always detected Advantage of strong typing: allows the detection of the misuses of variables that result in type errors Language examples: – C and C++ are not: parameter type checking can be avoided; unions are not type checked – Java and C# are, almost (because of explicit type casting) - ML and F# are Copyright © 2015 Pearson. All rights reserved. 1-132 Strong Typing (continued) The coercion rules of a language have an important effect on the value of type checking. – For example, expressions are strongly typed in Java. However, an arithmetic operator with one floating-point operand and one integer operand is legal. The value of the integer operand is coerced to floating-point, and a floating- point operation takes place. – However, the coercion also results in a loss of one of the benefits of strong typing—error detection. – For example, suppose a program had the int variables a and b and the float variable d. Now, if a programmer meant to type a + b, but mistakenly typed a + d, the error would not be detected by the compiler. The value of a would simply be coerced to float. So, the value of strong typing is weakened by coercion. Copyright © 2015 Pearson. All rights reserved. 1-133 Strong Typing (continued) Coercion rules strongly affect strong typing--they can weaken it considerably (C++ versus ML and F#) Java and C# have half as many assignment type coercions as C++, so their error detection is better than that of C++, but still not nearly as effective as that of ML and F#. Copyright © 2015 Pearson. All rights reserved. 1-134 Type Equivalence The compatibility rules dictate the types of operands that are acceptable for each of the operators and thereby specify the possible type errors of the language. The rules are called compatibility because in some cases the type of an operand can be implicitly converted by the compiler or run-time system to make it acceptable for the operator. Type equivalence Approaches: – name type equivalence – structure type equivalence. Copyright © 2015 Pearson. All rights reserved. 1-135 Name Type Equivalence Name type equivalence means the two variables have equivalent types if they are in either the same declaration or in declarations that use the same type name Easy to implement but highly restrictive: I. Subranges of integer types are not equivalent with integer types The types of the variables count and index would not be equivalent; count could not be assigned to index or vice versa. Copyright © 2015 Pearson. All rights reserved. 1-136 Name Type Equivalence II. Formal parameters must be the same type as their corresponding actual parameters. Like pass parameters in functions. Copyright © 2015 Pearson. All rights reserved. 1-137 Structure Type Equivalence Structure type equivalence means that two variables have equivalent types if their types have identical structures More flexible, but harder to implement Under name type equivalence, only the two type names must be compared to determine equivalence. Under structure type equivalence, however, the entire structures of the two types must be compared. This comparison is not always simple. Copyright © 2015 Pearson. All rights reserved. 1-138 Type Equivalence (continued) Consider the problem of two structured types: – Are two record types equivalent if they are structurally the same but use different field names? – Are two array types equivalent if they are the same except that the subscripts are different? (e.g. [1..10] and [0..9]) – Are two enumeration types equivalent if their components are spelled differently? – With structural type equivalence, you cannot differentiate between types of the same structure (e.g. different units of speed, both float) Copyright © 2015 Pearson. All rights reserved. 1-139 Type Equivalence (continued) For example, consider the following Ada-like declarations: type Celsius = Float; Fahrenheit = Float; – The types of variables of these two types are considered equivalent under structure type equivalence, allowing them to be mixed in expressions. Copyright © 2015 Pearson. All rights reserved. 1-140 Type Equivalence (continued) For example, consider the following Ada-like declarations: – An Ada subtype is a possibly range-constrained version of an existing type. – Variables of both types, Derived_Small_Int and Subrange_Small_Int, have the same range of legal values and both inherit the operations of Integer. – However, variables of type Derived_Small_Int are not compatible with any Integer type. – On the other hand, variables of type Subrange_Small_Int are compatible with variables and constants of Integer type and any subtype of Integer. Copyright © 2015 Pearson. All rights reserved. 1-141 Type Equivalence (continued) For example, consider the following Ada-like declarations: – The types of these two objects are equivalent, even though they have different names and different subscript ranges, because for objects of unconstrained array types, structure type equivalence rather than name type equivalence is used. – Because both types have 10 elements and the elements of both are of type Integer, they are type equivalent. Copyright © 2015 Pearson. All rights reserved. 1-142 Summary The data types of a language are a large part of what determines that language’s style and usefulness The primitive data types of most imperative languages include numeric, character, and Boolean types The user-defined enumeration and subrange types are convenient and add to the readability and reliability of programs Arrays and records are included in most languages Pointers are used for addressing flexibility and to control dynamic storage management Copyright © 2015 Pearson. All rights reserved. 1-143