Join Raghavendra Dixit for an in-depth discussion in this video Correctness of an algorithm, part of Introduction to Data Structures & Algorithms in Java.
- [Instructor] Now, how do we prove that that algorithm is correct? Well, formal proofs require mathematical reasoning. Like, we start with listing the statement to be proven. Then any assumptions that we may be making. And then we start from some dilemas and theorems, and using a chain of reasoning and assumptions, we would reach the statement to be proven. Proof could also be done in the reverse order. That is, starting from the statement to be proven, we try to reach some theory or dilema.
But in this course we will not be ready to guess with proofs. As this will not indice in mathematical regal. Later we will use some high level logical reasoning to make sure that they'll work on this correct. One way to check if an algorithm is correct is to see if it is incorrect. And checking the incorrectness need not be vigorous. All we need to do is to show that it does not work for some set of data.
And as logistics, when considering such data you may want to select a small set, especially the borderline cases. The main focus of this course is to help you easily understand data structures in algorithms. So we have used lots of animation in the video lectures and then there are quizzes in between video lectures to help replace what you've learned. I hope that you enjoy this course.
Note: This course was created by Packt Publishing. We are pleased to host this training in our library.
- Why study data structures and algorithms?
- How to calculate the time complexity
- Using Big O notation
- Using basic sorting and search algorithms
- Searching elements in unordered arrays and ordered arrays
- Implementing a linked list in Java
- Implementing stacks using arrays
- Queues using arrays
- Binary search trees
- Representing heaps using arrays
Skill Level Intermediate
1. Introduction to Algorithms
2. Analysis of Algorithms
3. Basic Sorting and Search Algorithms
4. Linked Lists
5. Stacks and Queues
7. Binary Search Trees
8. More Sorting Algorithms
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