What are data structures and algorithms?

Every program does two things: it keeps data (beams, users, orders, pixels) and it does work with that data (search, sort, add up, find a path). Data structures and algorithms are simply the study of doing those two things well.

• A data structure is a way of organising data in memory so that the operations you need are fast. An array, a list, a dictionary and a tree are all data structures.
• An algorithm is a precise, step-by-step recipe that turns an input into the right output in a finite number of steps. “Check each beam until you find the one with this ID” is an algorithm.

The two go together. The right structure makes a simple algorithm fast; the wrong one makes even a clever algorithm slow. Try it: the same question asked of the same data, stored three different ways.

Why learn this if .NET already has List and Dictionary?

You will rarely write your own hash table at work, but you choose between structures every day, and the wrong choice is one of the most common causes of slow software. Knowing how they work inside tells you which one to pick and what it costs.

• Performance: a check that takes 1 second on 1,000 elements might take 11 days on a million if the algorithm is O(n²). BIM models easily have a million elements.
• Interviews: almost every developer interview has DSA questions, from freshers to senior roles.
• Problem solving: many “hard” problems become easy once you recognise them as a known pattern: a graph search, a sliding window, a heap.

The main data structures at a glance

Do not worry about memorising this table. Every row has its own lesson later, with a visual of how it works inside.

Your first algorithm

Finding the largest value is a classic first algorithm. It is precise (no guessing), it always finishes, and it is correct for every non-empty input.

1static int Max(int[] values)2{3    if (values.Length == 0)4        throw new ArgumentException("Need at least one value.");5 6    int best = values[0];               // assume the first is the largest7    for (int i = 1; i < values.Length; i++)8    {9        if (values[i] > best)           // found a bigger one?10            best = values[i];11    }12    return best;13}14 15int[] loads = { 12, 45, 7, 88, 23 };16Console.WriteLine(Max(loads));

88

A good algorithm description answers four questions: what is the input, what is the output, what are the steps, and how do we know it is correct (here: after each step, best is the largest value seen so far).

How we judge an algorithm

1. Correct: it gives the right answer for every valid input, including edge cases (empty input, one element, duplicates, negative numbers).
2. Time: how the number of steps grows as the input grows. This is Big-O, the next lesson.
3. Memory: how much extra memory it needs (space complexity).
4. Simple: easy to read, test and change. A clever algorithm nobody understands is a risk.

How this course is organised

1static int FirstLongerThan(double[] lengths, double limit)2{3    for (int i = 0; i < lengths.Length; i++)4    {5        if (lengths[i] > limit)6            return i;          // stop at the first match7    }8    return -1;                 // checked everything, none found9}10 11double[] beams = { 6.5, 9.0, 14.2, 3.1, 12.8 };12Console.WriteLine(FirstLongerThan(beams, 12));13Console.WriteLine(FirstLongerThan(beams, 20));

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