Welcome to our new coding practice lesson! We have an intriguing problem centered around data from a social networking app. The challenge involves processing logs from this app and extracting valuable information from them. This task will leverage your skills in string manipulation, working with timestamps, and task subdivision. Let's get started!
Imagine a social networking application that allows users to form groups. Each group has a unique ID ranging from 1 to n
, where n
is the total number of groups. The app keeps track of group creation and deletion events, logging all these actions in a string.
The task before us is to create a TypeScript function named analyzeLogs
. This function will take as input a string of logs and output an array of strings representing the groups with the longest lifetime. Each string in the array contains two items separated by a space: the group ID and the group's lifetime. By "lifetime," we mean the duration from when the group was created until its deletion. If a group has been created and deleted multiple times, the lifetime is the total sum of those durations. For example, if we have a log string as follows: "1 create 09:00, 2 create 10:00, 1 delete 12:00, 3 create 13:00, 2 delete 15:00, 3 delete 16:00"
, the function will return: ["2 05:00"]
.
If multiple groups have the same longest lifetime, the function should return all such groups in ascending order of their IDs. Let's say we have the log string "1 create 08:00, 2 create 09:00, 1 delete 10:00, 2 delete 11:00, 3 create 12:00, 3 delete 13:00"
. In this case, both group 1 and group 2 have the same lifetime of 02:00. The function should return since both have the longest lifetime, and group 1 comes before group 2.
