The first goal of LeetCode practice is to learn how to solve problems associated with one concept. A LeetCode tag identifies each concept, and each problem has one or more tags. In the beginning, you don’t have to worry about learning concepts more granular than a tag, determining what concept an unknown problem is looking for, or solving a problem within a time limit. Those are all worthwhile skills to learn, but they are better left for later.

Although focusing on one tag is a narrow goal, let’s narrow it down a bit more. The hash table tag currently has 449 problems. To get started, we could solve the first easy problem, read a textbook chapter about hash tables, or check if one of LeetCode’s Explore cards covers hash tables. Instead, I suggest approaching the goal by starting with a model problem.

Serious study of algorithms and data structures often begins when you take a course, and such courses rely on practice problems. (Programming is a skill that you can’t learn just by reading about it). The model problem approach combines problem-based learning with the strengths of the LeetCode platform. The idea is to pick a concept, then find one or more problems that apply that concept in a way that you find understandable. When you need to apply the concept to a new problem, you can then draw on your experience with the model problems.

For example, let’s say you’re starting one of the 449 hash table problems. One approach would be to think about what you know about hash tables — you can insert and retrieve data in (average) constant time, you can store key/value pairs, each key must be unique — and map them to aspects of the problem. With the model problem approach, you instead think about a specific hash table problem that you have learned well, and you map parts of that problem to the new problem. Rather than concepts or pseudocode, you can map blocks of actual code. When you learned the model problem, you practiced correct syntax and typical usage patterns, so you have examples in your head of how hash tables help solve a specific problem. You can apply this practical knowledge to the new problem, rather than having to first translate hash table theory into practice.

This year, I’m publishing a series of tips for effective LeetCode practice. To read the tips in order, start with A Project for 2023

If you believe in the goal of preparing for coding interviews and you agree that LeetCode is a good way to pursue that goal, you may feel like getting on the site and building a daily streak. But it’s important to pick the right priority to focus on during this daily practice. While you can get some benefit out of simply opening LeetCode’s daily challenge problem and trying to solve it every day, there’s something missing from this type of practice. This year’s tips will fill in the gaps in the familiar “practice, practice, practice” approach.

Companies don’t use algorithmic coding interviews to test you on every conceivable computer science or software engineering topic. They focus on a relatively small set of concepts. You can find these concepts in the list of tags on the LeetCode problem page. Ordered by how often they appear in the LeetCode problem set, the first 10 concepts are Array, String, Hash Table, Dynamic Programming, Math, Sorting, Greedy, Depth-First Search, Database, and Breadth-First Search.

With this list of concepts in mind, we can target a more specific practice goal. Rather than practicing the skill of “solving LeetCode problems,” we can instead practice the skill of “solving Dynamic Programming problems” or “solving Depth-First Search problems.” That’s not to say that this skill will give you what you need to solve any problem, since you won’t always know which concept you need to use. But if you suspect that you’re looking at a Depth-First Search problem, it won’t do you much good unless you know how to implement Depth-First Search.

With that in mind, our first set of LeetCode tips will look at a process for learning the LeetCode algorithms, data structures, and techniques found in the tag list. We can ignore, for now, the general problem of how to solve a random LeetCode problem. Instead, we’ll focus on choosing a LeetCode tag and learning how to solve problems associated with that tag. If we can do that with one tag, we can do it with two tags, then three tags, and so on. Eventually we’ll reach the point where if we know which concept a problem requires, and if the problem has a reasonable difficulty level (i.e., Easy or Medium), we’ll have a good chance of solving it. No flashes of insight required.

This year, I’m publishing a series of tips for effective LeetCode practice. To read the tips in order, start with A Project for 2023

To help make the upcoming tips less abstract, I’m going to start with a sample problem that I’ll refer to when needed: LeetCode problem 704, Binary Search. I chose binary search because it has a short implementation that uses only basic language features, but even experts have trouble getting it right.

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We’re going to be covering LeetCode tips in the coming year. But before we get to the tips, I’d like to discuss why I chose LeetCode as a study topic, so you can decide if this year’s project is right for you.

I chose LeetCode because:

• It focuses on coding interviews: There are several reasons you might want to study algorithmic coding problems. But for this year’s project, we’re going to focus on one: Preparing for a coding interview. We won’t ignore the other reasons entirely, but the focus will be on the practical goal of getting better at the coding interview process. This aligns with LeetCode’s strengths, as compared to a competitive programming site like Codeforces or a general textbook like Introduction to Algorithms.

• It has an active community: There are other sites for building coding interview skills. But LeetCode’s popularity gives it some advantages compared to other sites: It has an active discussion section for every problem, two weekly contests generate a regular supply of fresh problems, and the LeetCode company receives enough income to keep the site up to date. There are many programmers with the goal of preparing for interviews, and we might as well go where most of them are.

• It supports regular practice: The way to get better at coding interview problems is to write code and see how it performs on tests. This matches the core LeetCode practice loop: Read a problem, design and implement a solution, run it on test data, and try again (or move on to the next problem).

The tips we’ll be covering this year promote two goals: 1) Practicing coding interview problems, and 2) Understanding the solutions to these problems. LeetCode has a similar structure. The online judge supports practice. And to help with understanding the solution, each problem gets a throughout analysis by LeetCode in the official solution and by community members in the discussion forums.

While working on my LeetCode project last year, I started a list of general practice notes. Not notes on specific problems, though those are essential, but notes on the LeetCode practice process in general. My plan for this year is to turn those into a short LeetCode practice tip each week.

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