The Split Message Based on Limit coding problem is a challenging string task where you must take a long message and split it into several parts to fit within a specific character limit. However, there's a catch: each part must end with a suffix like <1/10>, <2/10>, etc. This suffix counts toward the character limit. Since the length of the suffix depends on the total number of parts (e.g., <1/9> is shorter than <1/10>), the problem becomes non-trivial because the total number of parts is initially unknown.
This "Hard" problem is popular at companies like Databricks and Uber because it requires a combination of Binary Search, Enumeration, and careful String manipulation. It tests whether a candidate can handle interdependent variables (message length per part and total parts). It's a great test of how you handle complex constraints and your ability to optimize a search space.
The most common Algorithmic pattern used is Enumeration or Binary Search on the total number of parts. Since the total number of parts can't be huge (it's bounded by the message length), we can try possible values for the total number of parts, . For a fixed , we calculate the total capacity available for the message across all parts after accounting for the suffixes. The first that can accommodate the entire message is our answer.
Suppose your message is "Hello World" and the limit is 10.
If we try 2 parts ():
Part 1 suffix is <1/2> (5 chars). Remaining for message: chars.
Part 2 suffix is <2/2> (5 chars). Remaining for message: chars.
Total message capacity = chars. "Hello World" is 11 chars. So is not enough.
If we try 3 parts ():
Suffixes are <1/3>, <2/3>, <3/3> (all 5 chars).
Total capacity = . 15 is enough for 11 chars!
The message is then split into "Hello", " Worl", and "d".
<1/9> is 5 characters while <1/10> is 6 characters.When a variable depends on another variable , and is also influenced by , try fixing one variable and checking the feasibility of the other. This Split Message Based on Limit interview question is a classic example of where enumerating one variable simplifies the entire problem.