
In this problem, we are given a scenario where a student's attendance is recorded in a string format, with each character representing one of three statuses: Absent ('A'), Late ('L'), and Present ('P'). For a student to be considered for an attendance award, two criteria must be satisfied: the student must have less than two days of absence and must not be late for three consecutive days. Given an integer n, which indicates the length of the attendance record, our task is to compute how many possible attendance records of that length would make the student eligible for the award. Due to potentially large outputs, results should be returned modulo 10^9 + 7.
Input:
Output:
Explanation:
Input:
Output:
Input:
Output:
1 <= n <= 105Understanding this problem requires analyzing how combinations of 'A', 'L', and 'P' can be arranged to satisfy the given criteria for eligibility:
n.'A's.'L's.The nuances in such sequence generation involve significant combinatorial calculations, especially as n becomes large. Here's the approach:
n can be derived using the counts from shorter lengths. This typically involves adding a character to shorter valid sequences while maintaining the award criteria.n increases, and to avoid overflow as well as adhere to problem constraints, we use modulo 10^9 + 7 at every step of our computation.n: These are straightforward and serve as base cases for building up to larger n.AAA, AAAA (or more continous 'A's) and extensive sequences of 'L': Incorporating mechanisms to skip such combinations saves computation.By implementing dynamic programming efficiently, these observations can be executed with significant optimizations, leading to feasible solutions even for large values of n, up to the upper constraint of 105.
The given C++ code defines a solution to the problem of counting valid sequences of student attendance records based on set conditions. The records are determined valid if they contain no more than one 'A' (absence) and more than two continuous 'L' (lates).
Here's a breakdown of the approach and methodology in the code:
Initialization: Establishes a 2D vector currentState to keep track of the number of valid sequences for various states pertaining to absences and lates. Similarly, another 2D vector nextState stores the count of sequences for the next day.
Dynamic Programming Approach:
length), iterate through all combinations of absences (0 or 1) and lates (0 to 2).nextState based on transitions from 'P' (present), by adding sequences that end with the corresponding absences and lates without exceeding limits.Transition and State Updates:
nextState values to currentState, and reset nextState for fresh calculations for the next day (length increment).Result Calculation: Sum up all valid sequences from currentState after processing up to the desired sequence length.
Modulo Operation: Apply a modulo operation with MODULO = 1000000007 during calculations to prevent overflow and ensure results fit within standard integer sizes.
Return Result: The final result, stored in the variable result, is returned from the function. It represents the count of all valid attendance sequences of the specified length. The function is designed to be efficient and robust enough to handle different input sizes, providing correct count within computational limits.
By using dynamic programming, the code efficiently calculates the number of valid sequences, ensuring quick evaluation as it reuses prior results reducing computing time significantly.
0 Comments
Be the first to comment and share your perspective with the community.