Challenge 3 - Match a person with Levenshtein Distance

Deadline: yyyy-MM-dd HH:mm:ss SSS

Description

You are tasked by the business owners on the Marketing team to improve the matching process of a Lead in the system. Currently, a person (lead) is found in the system and considered a "match" if the input (search criteria) First and Last Name is equal to the system's First and Last Name.

We need to relax our matching logic slightly and implement fuzzy (approximate) string matching on the first name and last name.

We will be using the Levenshtein Distance to implement this.

Requirements

Read the file, leads.csv which is located at the project root and use as your data store.
The application should accept a first name and last name (or a data structure representing each) as INPUT.
The INPUT will be compared against the Leads in the data store (leads.csv) using Levenshtein Distance.
The best match's row ID will be returned with the First Name and the Last Name of the respective match (again, feel free to return 3 values if your language supports it; or a data structure representing the 3 values).

Matching

The Marketing team has come up with the following match requirements using this fuzzy matching algorithm.

It is possible that there could be multiple matches that meet the below criteria. You should return the best match (lowest Levenshtein Distance). If there are 2+ matches with the same distance, then simply return one of them.

The Levenshtein Distance for First Name should be no larger than 3.
The Levenshtein Distance for Last Name should be no larger than 1.
The total Levenshtein Distance between First AND Last name should be no larger than 3.
The required Levenshtein Distance for Last Nameshould be configurable so that the business can increase/decrease the tolerance as needed. A change to this configuration should reflect immediately and without restarting the application. How you implement this is up to you. NOTE if the Last Name tolerance is configurable, you will need to update the Total's tolerance appropriately.
Case sensitivity should be ignored and should not contribute to the Levenshtein Distance (ie. e == E).

Assumptions

leads.csv is normalized to UPPERCASE
There WILL NOT be any surprises in the data, such as First/Last Name in the FirstName column and a null LastName column.
The only possible characters within leads.csv are A-Z or ', plus 0-9 for the row ID.

Additional Instructions

Use a language of your choice.
NO 3rd party libraries or frameworks.
Include your solution in a subdirectory that is named appropriately to determine who submitted it.
Feel free to add names to leads.csv. The initial data in the file is meant to provide some examples of input data.
After submissions are in, a more extensive input file will be created and used for the testing/benchmarking.