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Payap University ICS220 - Data Structures and Algorithm Analysis Instructor: Dr. Ken Cosh

Case Study: A Recursive Descent Interpreter Implementation in C ++ (Source Code Courtesy of Dr. Adam Drozdek ). Payap University ICS220 - Data Structures and Algorithm Analysis Instructor: Dr. Ken Cosh Analysis and Presentation by Rob Agle. First, let’s clear up some terminology….

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Payap University ICS220 - Data Structures and Algorithm Analysis Instructor: Dr. Ken Cosh

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  1. Case Study:A Recursive Descent InterpreterImplementation in C++(Source Code Courtesy of Dr. Adam Drozdek) Payap University ICS220 - Data Structures and Algorithm Analysis Instructor: Dr. Ken Cosh Analysis and Presentation by Rob Agle

  2. First, let’s clear up some terminology…

  3. Interpreter • In general, a compiler is a program that converts an entire program from high level source code into some lower level representation (assembly or machine code for example). • An interpreter on the other hand, traditionally translates high level instructions and executes them on the fly (at runtime). • The lines between these two concepts are blurringhowever… Examples of “Interpreted” Languages • Python • Pearl • JavaScript • Ruby • Smalltalk • Java

  4. Interpreter • For our purposes – we can simply say that our interpreter will be used to translate and execute one instruction statement at a time.

  5. Interpreter • For our purposes – we can simply say that our interpreter will be used to translate and execute one instruction statement at a time.

  6. Interpreter • For our purposes – we can simply say that our interpreter will be used to translate and execute one instruction statement at a time.

  7. Interpreter • Things our interpreter understands: • Variable Names: Any alphanumeric string • Operators: + - / * = • Commands: Print, Status, End

  8. Recursive Descent • A process that allows us to descend – or “go down” to lower and lower levels of complexity via recursion, and then work “backwards” towards a solution once all the pieces are in place.

  9. Recursive Descent • A process that allows us to descend – or “go down” to lower and lower levels of complexity via recursion, and then work “backwards” towards a solution once all the pieces are in place.

  10. Recursive Descent • For Example: • var = 2*(3+5);

  11. Recursive Descent • For Example: • var = 2*(3+5);

  12. Recursive Descent • For Example: • The statement: var = 2*(3+5); can be parsed and broken down into its individual piecesusing recursion.

  13. Recursive Descent • For Example: • The statement: var = 2*(3+5); can be parsed and broken down into its individual piecesusing recursion.

  14. Recursive Descentvar = 2*(3+5); • Don’t worry about how, just imagine we magically use some combination of direct and indirect recursion to break down the above statement into the following…

  15. Recursive Descentvar = 2*(3+5); • Don’t worry about how, just imagine we magically use some combination of direct and indirect recursion to break down the above statement into the following…

  16. var = 2 * ( 3 + 5 ) ;

  17. var = 2 * ( 3 + 5 ) ; ID

  18. var = 2 * ( 3 + 5 ) ; ID Operator Operator Operator

  19. var = 2 * ( 3 + 5 ) ; ID Factor Factor Factor Operator Operator Operator

  20. var = 2 * ( 3 + 5 ) ; Term Term ID Factor Factor Factor Operator Operator Operator

  21. var = 2 * ( 3 + 5 ) ; Expression Expression Term Term ID Factor Factor Factor Operator Operator Operator

  22. var = 2 * ( 3 + 5 ) ; Expression Expression Term Term ID Factor Factor Factor Operator Operator Operator

  23. What do we need (object wise) to accomplish this? • Data: • a list of all ID’s (variables) • An array of characters to store an input statement • Functionality: • A way to get the input statement from the user • A way to parse the input, get values for expressions (if any) and its composite parts (terms, factors – if any) and perform indicated operations. • A few “black boxes”…

  24. Data

  25. What do we need (object wise) to accomplish this? • Data: • a list of all ID’s (variables) • An array of characters to store an input statement • Functionality: • A way to get the input statement from the user • A way to parse the input, get values for expressions (if any) and its composite parts (terms, factors – if any) and perform indicated operations. • A few “black boxes”…

  26. Functionality

  27. So – let’s go back to our concrete example and trace the program…

  28. Trace: Input -> var = 2*(3+5);

  29. Trace: Input -> var = 2*(3+5);

  30. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch =

  31. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = Runtime Stack getStatement() e = id = command =

  32. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = var Runtime Stack getStatement() e = id = command = var VAR

  33. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = var = Runtime Stack R expression() getStatement() e = id = command = ? var VAR

  34. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = = Runtime Stack R term() R expression() t = ? getStatement() e = id = command = ? var VAR

  35. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = = Runtime Stack R factor() R term() f = ? R expression() t = ? getStatement() e = id = command = ? var VAR

  36. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = = Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = ? R expression() t = ? getStatement() e = id = command = ? var VAR

  37. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = = 2 Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = ? R expression() t = ? getStatement() e = id = command = ? var VAR

  38. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = 2 Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = ? R expression() t = ? getStatement() e = id = command = ? var VAR

  39. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = 2 Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = ? R expression() t = ? getStatement() e = id = command = ? var VAR

  40. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = 2 * Runtime Stack R factor() var = 1.0 2.0 minus = 1.0 id = R term() f = ? R expression() t = ? getStatement() e = id = command = ? var VAR

  41. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = * Runtime Stack R factor() var = 2.0 minus = 1.0 id = R term() f = 2 ? R expression() t = ? getStatement() e = id = command = ? var VAR

  42. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = * Runtime Stack R factor() R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  43. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = * Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  44. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = ( * Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  45. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = ( Runtime Stack R factor() var = 1.0 minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  46. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = ( R expression() Runtime Stack R factor() var = 1.0 ? minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  47. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = ( R expression() Runtime Stack R factor() var = ? Here, we have our first recursive function call… minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  48. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = ( R expression() Runtime Stack R factor() var = ? This conveniently allows us to naturally follow mathematical precedence … minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  49. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = ( R term() R expression() Runtime Stack R factor() var = ? A series of additional indirect recursive calls will determine the value of (3+5)… minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

  50. Trace: Input -> var = 2*(3+5); statement.idList = Statement.ch = R factor() ( R term() R expression() Runtime Stack R factor() var = ? A series of additional indirect recursive calls will determine the value of (3+5)… minus = 1.0 id = R term() f = 2 * ? R expression() t = ? getStatement() e = id = command = ? var VAR

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