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CSCA48 Course Summary

CSCA48 Course Summary. Announcements. Exam period office hours: will be posted Check your marks! A1, E1, E2, E3, labs, midterms all posted Will post to Piazza when E4 and A2 marks available Report errors before the final exam Fill out course evaluations on intranet! By Monday, April 9th.

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CSCA48 Course Summary

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  1. CSCA48Course Summary

  2. Announcements • Exam period office hours: will be posted • Check your marks! • A1, E1, E2, E3, labs, midterms all posted • Will post to Piazza when E4 and A2 marks available • Report errors before the final exam • Fill out course evaluations on intranet! • By Monday, April 9th

  3. Course Summary • This course introduced the science of computing • Tools and techniques that affect all parts of the software lifecycle:specification, design, testing, and implementation

  4. Topics • classes & inheritance • abstract data types (ADTs) • object oriented analysis (OOA) • exceptions • testing • recursion • memory model • trees (including BSTs and heaps) • sorting • linked lists • time analysis (big O) • pygame basics

  5. Abstract Data Types (ADTs) • Standard abstractions that have proven useful in computer science • Abstract: the user doesn't want to know how it works (implementation), but how it will work (public interface) • Data: what information are you recording? • Type: a structure that encapsulates a concept that is common to an entire set (type) of instances

  6. ADTs we've seen • stack • operations: push(item), pop(), is_empty() • queue • operations: enqueue(item), dequeue(), is_empty() • priority queue • operations: insert(item, priority), extract_max(), is_empty() • list • operations: insert, remove, get item at index

  7. Data Structures • Data Structure: a particular way to implement an ADT. • "regular" lists • linked lists • trees • made from linked structures (with Node class) • made from lists • Binary Search Trees • Heaps • On the exam: • Trace through insert / remove algorithms for BSTs and heaps • Write functions dealing with trees and linked lists • more on data structures in CSCB63

  8. Testing • Test-driven development: a common, successful industry-developed approach to writing code • Write header, write docstring, write some tests, then implement • Add tests as you think of them • Mantras: 0, 1, many; even, odd; empty, full; general case • Tests serve to document code, especially at early stages • Test documentation needs to be clear about why tests exists • On the exam: • Design a set of test cases • Be able to use assert statements • Do not need to write unittest code from scratch

  9. Implementation • Properties of a good program • Abstraction: what real-world objects are you modeling? • Reuse: design your code to avoid duplication • Encapsulation: each method/function should do one thing; each class should model one concept • Exception handling: design your code to fail gracefully • On the exam: • Object Oriented Analysis! • Example: Give the class structure for a tic-tac-toe game. For each class, write the header and docstring for every method. • more on designing large programs in CSCB07

  10. Recursion • Thinking recursively • Termination / base case • Recursion vs. iteration • Examples • Fast sorting: mergesort, quicksort, heapsort • Tree traversals • CSCC24 is compellingly riddled with recursion

  11. Complexity and Time Analysis • How efficient is this program? • On the exam: • Big O notation • e.g. If a heap has n elements, extract_max takes O(log n) steps • Which operation is faster? • e.g. For a singly-linked list: Inserting near the front is faster than inserting near the end. • Do not need to write profiling code or read profiling output • More on analysis of programs in B36, C63, C73

  12. What's next? • Systems • Operating Systems • Compilers • Programming languages • Databases • Communications and security • Network protocols • Security • Concurrency • Software Engineering • Requirements analysis • Design patterns, architecture • Metrics to access / predict cost, quality, complexity • Tools for making robust software design in a team • Theory • What can you compute? • Proving code is correct • Analyzing running time and space used • Proving your algorithm takes minimal time and/or space • Time/space trade-offs • New data structures • Human-computer Interaction • Psychology • Usability studies • Interface design

  13. Final Exam • 3 hours • no aids allowed • material from lectures, labs, exercises, assignments, reading • What's it like? • http://eres.library.utoronto.ca/ • Recent exams are in Python • Older exams are in Java, but still have questions that work in Python • last pages are reference sheets (like on midterms)

  14. Sorts of Questions • Trace code (give output, draw memory model) • Write test cases • Play with linked lists, trees, stacks, queues, etc • lots of this! • Design / implement / use a class • Analyze runtime (big O, which is faster?)

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