Slide 1 Data Structures and Abstractions Stacks Lecture 21 * Temporary Storage When processing it is often necessary to put data into temporary storage. This can happen, for example, when: processing events in an event-driven OS; processing email in and out of a server; scheduling jobs on a main-frame; doing calculations; sorting or merging; The […]
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Hash Tables Data Structures and Abstractions Hash Tables Lecture 31 * Important Advice for Assignment2/Project You must demonstrate progress on the Assignment 2/project to your tutor. This is to ensure that the following good practices are being followed: 1. The work does not have to be complete but it must build (compile and link) and
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Graph Processing Algorithms Data Structures and Abstractions Minimum Spanning Tree Algorithms Lecture 34 * MST versus SPT The SPT problem of the previous lecture involved finding the shortest path from a single vertex to every other vertex. The MST problem involves finding the shortest way to connect all the vertices to each other, using any
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B215 Practical exercises – Week 7 ICT283 Assessed exercise 2 Objectives: To learn · BST concepts · To construct a simple BST · Understand recursion · Preparation for assignment 2 It is very important not to fall behind with these exercises. Internal students demonstrate exercise b to their tutor during the next lab session. Externals
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For part a, use the material from the lecture notes. Don’t just jump to code in the textbook (earlier editions) because the textbook also provides non-recursive implementations. We are not using these as recursive versions are needed for the lab. For trees, recursive implementations have less code as the tree structure is recursive, and therefore
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Searching, Sorting and Merging Data Structures and Abstractions Searching, Merging and Sorting Lecture 25 * When testing searching and merging algorithms, it is important to check boundary and unusual conditions: In other words test for containers with [1]: 0 elements; 1 element; 2 elements; 3 elements; a large number of odd elements; a large number
The labwork for this topic is assessed. It is the last lab assessment. Step 1: Complete all work from previous topics, if not already completed, then go through the powerpoint files in Content. Step 2: Go through any of Bucky’s tutorials that you didn’t complete Use codeblocks and do the tutorials instead of just watching
Searching, Sorting and Merging Data Structures and Abstractions Empirical Comparisons, and the STL Sorts Lecture 27 * Empirical Comparison 1 * Empirical Comparison 2 * Empirical Comparison 3 * Empirical Comparison 4 * Empirical Comparison 5 * STL Sorts There are a number of sort routines available in the STL algorithm library, a priority queue,
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B215 Practical exercises – Week 7 ICT283 (not assessed but must be attempted) Objectives: · More practice with use of an STL map · Continue with the data structures requirements of assignment 2 · Start work on specific assignment 2 requirements · Experiment with sorting and do empirical comparisons of their performance · Make us
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Searching, Sorting and Merging Sorting Algorithms animations of algorithms Lecture 26 Data Structures and Abstractions * Bubble Sort Bubble sort is the most commonly coded of the simple sorts. It is a stable exchange sort. Whilst not particularly fast—O(n2)—it is very simple to code and easy to understand. For anything less than 1000 items, bubble
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