Introduction

In my journey through the world of coding interviews, I encountered a recurring obstacle: the difficulty of coming up with critical test cases that are a significant representation of the problem statement. The realization that robust solutions heavily depend on these critical test cases became a turning point in my approach to coding challenges. This article aims to share my journey and the strategies I developed to master the art of identifying critical test cases, hoping to help others overcome similar challenges.

The Gap

My struggle with coding problems at first seemed straightforward: I could come up with solutions that were good enough for the 2-3 examples provided in the problem statement but fell short when faced with additional, unseen test cases. This pattern made me realize there was a gap in my ability to identify edge cases, which motivated me to search for a solution.

Identifying the problem

I first assumed that my struggle came from not fully understanding the problem statements. However, even after carefully rereading them, it became clear that the issue was not just a misunderstanding but a lack of strategy for anticipating the edge cases.

Understanding the problem is deeply crucial, but during my research for a strategy, I realized there’s also a skill in anticipating the edge cases that could cause your algorithm to fail. This skill improves over time with practice and with a systematic approach to considering various aspects of the problem.

In other words, it’s not just about understanding the problem correctly; it’s also about methodically questioning and challenging your assumptions about the input and behavior of your solution under different conditions.

The Turning Point: Structured Problem Analysis

Adopting a systematic approach to problem analysis was transformative. I developed a three-step process that worked for me. This method involved:

1. Understanding requirements: Understanding requirements involves carefully reading the problem statement to grasp all the requirements while mentally noting any unique information. It's all in the details. Ask yourself questions about those details. For example, what does it mean that the array is sorted? or if the statement says the string may contain leading or trailing spaces or multiple spaces between two words, how does that affect your solution?

2. Identifying constraints and conditions: Paying attention to any special conditions mentioned. For example, how does the fact that the the string only contains English letters (upper-case and lower-case), digits and spaces affect my optimal solution?

3. Challenging your assumptions: Actively questioning assumptions about the inputs and outputs.

Common Special Cases to Consider

Through my journey, I learned that while no list of special cases fits every problem, certain common considerations apply to many scenarios, including:

• Empty Inputs: Always consider how your algorithm handles cases where the input is empty.

• Single-Element Inputs: Particularly for problems involving collections or strings. How does your solution behave with a single element?

• Maximum and Minimum Values: Consider the boundaries of the problem's constraints. How does your solution handle the largest or smallest possible inputs?

• Negative Values: For numerical problems, consider how negative inputs affect your algorithm.

• Duplicate Values: In problems where uniqueness isn't guaranteed, how do duplicates affect the outcome?

• Data Type Limits: Be aware of potential overflow or underflow issues with numerical data types.

• Null or Invalid Inputs: Consider how your solution should gracefully handle or report errors for invalid input.

Tips to Improve

Improvement in identifying critical test cases comes with time and practice. Here are some tips I found helpful during my journey:

1. Practice with intention: When practicing problems, take time after each solution to reflect on the edge cases you might have missed. Try to understand why you missed them and how you could have identified them earlier.

2. Learn from others: Review solutions and discussions for the same problems on platforms like LeetCode or CodeWars. Pay special attention to the test cases others discuss, especially if they reveal a flaw in your original solution.

3. Systematic testing: Before running your code, write down a list of test cases that cover the broad range of inputs and edge cases. Use this as a checklist to verify your solutions manually.

4. Build a checklist: Based on your practice and learning, maintain a personal checklist of common edge cases and special conditions. Refer to this list when testing your solutions.

Conclusion: Incremental Improvement and Intuition

My journey taught me that solving coding challenges and mastering critical test cases is a process of incremental improvement and learning from both successes and mistakes. Over time, this process has improved my intuition but it is a continuous learning process. Keep practicing and find what strategy works best for you.

I encourage you to share your experiences and strategies for identifying critical test cases and solving coding challenges below. Let's learn from each other and continue to grow on our coding journey.