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Data Structures and Algorithms for Information Processing

Data Structures and Algorithms for Information Processing. Lecture 1: Introduction. Course Web Site. http://www.andrew.cmu.edu/~mm6. Structure of the Course. Lectures / class participation Homeworks (programming) Midterm examination Final examination. Readings.

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Data Structures and Algorithms for Information Processing

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  1. Data Structures and Algorithms for Information Processing Lecture 1: Introduction Lecture 1: Introduction

  2. Course Web Site • http://www.andrew.cmu.edu/~mm6 Lecture 1: Introduction

  3. Structure of the Course • Lectures / class participation • Homeworks (programming) • Midterm examination • Final examination Lecture 1: Introduction

  4. Readings • Readings from the required text are assigned for each lecture -- read them in advance • The book contains self-test exercises in each section • Work these exercises (especially if you are new to the material) Lecture 1: Introduction

  5. Grading • Homework (5-6) 50% • Midterm Exam 25% • Final Exam 25% Lecture 1: Introduction

  6. Definitions • A data structure is an organized collection of data with specific aggregate properties • An algorithm is a sequence of program instructions designed to compute a particular result Lecture 1: Introduction

  7. Five Steps per Datatype • Understand it Abstractly • Write a Specification • Write Applications • Select an existing, or Design and Implement our own • Analyze the Implementation in terms of performance Lecture 1: Introduction

  8. Abstract vs. Concrete • An abstract data type (ADT) specifies behavior, but not implementation • An implementation uses a particular low-level datatype to implement the desired behavior Lecture 1: Introduction

  9. Quick Example • A stack is an abstract data type (ADT). • We push and pop from the top. • Consider three implementations: (1) Every push causes all elements in an array to shift down 1 before the insertion at s[0]. (2) We add at stackTop and then add one to stackTop. (3) A linked list use where the top is always at the list’s front end. • Each implementation can be written correctly. • Implementation (1) runs in Θ(n). • Implementations (2) and (3) run in Θ(1). Lecture 1: Introduction

  10. Step 1: Understanding • Grasp the datatype at the level of concepts and picturese.g., visualize a stack and the operations of pushing / popping • Understand simple applications • Simulate by hande.g., use a stack to reverse the order of letters in a word Lecture 1: Introduction

  11. Step 2: Specification • Write a specification for a Java class that could implement the datatype (see javadoc Appendix H) • Headings for constructor, public methods, public features • Includes precondition / postcondition for each method • Independent of implementation! Lecture 1: Introduction

  12. Step 3: Application • Based on the specification, write small applications to illustrate the use of the datatype • “Test the specification” prior to implementation • Code not yet compiled / run Lecture 1: Introduction

  13. Step 4: Implementation • Select appropriate data structure • Implement as private class vars • Write rules relating instance variables to abstract specification:the invariant of the ADT • Each method knows the invariant is true when it starts • Each method upholds the invariant Lecture 1: Introduction

  14. Step 5: Analysis • Correctness • Flexibility • When possible, compare different implementations of the same ADT • Time Analysis • number of operations • big-O notation, e.g., Lecture 1: Introduction

  15. Phases of Software Development • Specification of the Task • Design of a Solution • Implementation of the Solution • Running Time Analysis • Testing and Debugging • Maintenance and Evolution • Obsolescence Lecture 1: Introduction

  16. Java • Conceived in 1991 at Sun • Has Similarities to C++ • Is simpler than C++ • Object-Oriented Programming (OOP) • information hiding • component re-use • programs (methods) and data are grouped together into classes • we will not be using the collection classes Lecture 1: Introduction

  17. What You Should Know Already • How to use a Java development environment (java, javac, javadoc) • How to write, compile, and run short Java programs • Java primitive types (number types, char, boolean) and arrays • Easy to pick up with prior programming experience Lecture 1: Introduction

  18. Specifying a Java Method • Specification: what a method does not how it does it • A form of information hiding called procedural abstraction • Method signaturepublic static double celsiusToFahrenheit(double c) • Method calldouble fahrenheit = celsiusToFahrenheit(celsius); Lecture 1: Introduction

  19. Elements of Specification • Short Introduction • Parameter Description • Returns • Specify the meaning of return value • Throws list • error conditions (exceptions) “thrown” by this method • Precondition and Postcondition Lecture 1: Introduction

  20. Preconditions • A precondition is a statement giving the condition that should be true when the method is called • The method is not guaranteed to perform as it should unless the precondition is true. • If violated, ignore (like c) or throw an exception (like Java). Lecture 1: Introduction

  21. Postconditions • A postcondition is a statement describing what will be true when a method call completes • If the method is correct and precondition was met, then the method will complete, and the postcondition will be true when it does • Use Java assert statement for post-condition checks during debugging. Not during deployment. Lecture 1: Introduction

  22. Example Specification • celsiusToFahrenheitpublic static double celsiusToFahrenheit(double c) • convert a temperature from Celsius degrees to Fahrenheit degrees • Parameters:c - a temperature in Celsius degrees • Precondition: c>= -273.16 • Returns: temperature c in Fahrenheit • Throws: IllegalArgument Exception Lecture 1: Introduction

  23. More on Pre/Postconditions • Slides from Main’s Lectures Lecture 1: Introduction

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