Hasan loves playing games and has recently discovered a game called TopScore. In this soccer-like game there are $p$ players doing penalty shoot-outs. Winner is the one who scores the most. In case of ties, one of the top-scorers will be declared as the winner randomly with equal probability.

They have just finished the game and now are waiting for the result. But there's a tiny problem! The judges have lost the paper of scores! Fortunately they have calculated sum of the scores before they get lost and also for some of the players they have remembered a lower bound on how much they scored. However, the information about the bounds is private, so Hasan only got to know his bound.

According to the available data, he knows that his score is at least $r$ and sum of the scores is $s$.

Thus the final state of the game can be represented in form of sequence of $p$ integers $a_1, a_2, \dots, a_p$ ($0 \le a_i$) — player's scores. Hasan is player number $1$, so $a_1 \ge r$. Also $a_1 + a_2 + \dots + a_p = s$. Two states are considered different if there exists some position $i$ such that the value of $a_i$ differs in these states. 

Once again, Hasan doesn't know the exact scores (he doesn't know his exact score as well). So he considers each of the final states to be equally probable to achieve.

Help Hasan find the probability of him winning.

It can be shown that it is in the form of $\frac{P}{Q}$ where $P$ and $Q$ are non-negative integers and $Q \ne 0$, $P \le Q$. Report the value of $P \cdot Q^{-1} \pmod {998244353}$.


-----Input-----

The only line contains three integers $p$, $s$ and $r$ ($1 \le p \le 100$, $0 \le r \le s \le 5000$) — the number of players, the sum of scores of all players and Hasan's score, respectively.


-----Output-----

Print a single integer — the probability of Hasan winning.

It can be shown that it is in the form of $\frac{P}{Q}$ where $P$ and $Q$ are non-negative integers and $Q \ne 0$, $P \le Q$. Report the value of $P \cdot Q^{-1} \pmod {998244353}$.


-----Examples-----
Input
2 6 3

Output
124780545

Input
5 20 11

Output
1

Input
10 30 10

Output
85932500



-----Note-----

In the first example Hasan can score $3$, $4$, $5$ or $6$ goals. If he scores $4$ goals or more than he scores strictly more than his only opponent. If he scores $3$ then his opponent also scores $3$ and Hasan has a probability of $\frac 1 2$ to win the game. Thus, overall he has the probability of $\frac 7 8$ to win.

In the second example even Hasan's lower bound on goal implies him scoring more than any of his opponents. Thus, the resulting probability is $1$.

Difficulty: VERY_HARD
Tags: Dynamic programming

Combinatorics

Mathematics

Probability
Skill types: Dynamic programming

Starter code:

Solutions:
base = 998244353

def power(x, y):
	if y == 0:
		return 1
	t = power(x, y // 2)
	t = t * t % base
	if y % 2:
		t = t * x % base
	return t

def inverse(x):
	return power(x, base - 2)
f = [1]
iv = [1]
for i in range(1, 5555):
	f.append(f[i - 1] * i % base)
	iv.append(inverse(f[i]))

def C(n, k):
	return f[n] * iv[k] * iv[n - k] % base

def candy(n, k):
	return C(n + k - 1, k - 1)

def count_game(k, n, x):
	if k == 0:
		if n == 0:
			return 1
		else:
			return 0
	ans = 0
	for i in range(0, k + 1):
		t = n - x * i
		if t < 0:
			break
		if i % 2:
			ans = (ans - C(k, i) * candy(t, k)) % base
		else:
			ans = (ans + C(k, i) * candy(t, k)) % base
	return ans
(p, s, r) = list(map(int, input().split()))
gamesize = count_game(p, s - r, int(1e+18))
gamesize = inverse(gamesize)
ans = 0
for q in range(r, s + 1):
	for i in range(0, p):
		t = s - (i + 1) * q
		if t < 0:
			break
		ans = (ans + C(p - 1, i) * count_game(p - i - 1, t, q) * gamesize * inverse(i + 1)) % base
print(ans)


def divisors(M):
	d = []
	i = 1
	while M >= i ** 2:
		if M % i == 0:
			d.append(i)
			if i ** 2 != M:
				d.append(M // i)
		i = i + 1
	return d

def popcount(x):
	x = x - (x >> 1 & 1431655765)
	x = (x & 858993459) + (x >> 2 & 858993459)
	x = x + (x >> 4) & 252645135
	x = x + (x >> 8)
	x = x + (x >> 16)
	return x & 127

def eratosthenes(n):
	res = [0 for i in range(n + 1)]
	prime = set([])
	for i in range(2, n + 1):
		if not res[i]:
			prime.add(i)
			for j in range(1, n // i + 1):
				res[i * j] = 1
	return prime

def factorization(n):
	res = []
	for p in prime:
		if n % p == 0:
			while n % p == 0:
				n //= p
			res.append(p)
	if n != 1:
		res.append(n)
	return res

def euler_phi(n):
	res = n
	for x in range(2, n + 1):
		if x ** 2 > n:
			break
		if n % x == 0:
			res = res // x * (x - 1)
			while n % x == 0:
				n //= x
	if n != 1:
		res = res // n * (n - 1)
	return res

def ind(b, n):
	res = 0
	while n % b == 0:
		res += 1
		n //= b
	return res

def isPrimeMR(n):
	if n == 1:
		return 0
	d = n - 1
	d = d // (d & -d)
	L = [2, 3, 5, 7, 11, 13, 17]
	for a in L:
		t = d
		y = pow(a, t, n)
		if y == 1:
			continue
		while y != n - 1:
			y = y * y % n
			if y == 1 or t == n - 1:
				return 0
			t <<= 1
	return 1

def findFactorRho(n):
	from math import gcd
	m = 1 << n.bit_length() // 8
	for c in range(1, 99):
		f = lambda x: (x * x + c) % n
		(y, r, q, g) = (2, 1, 1, 1)
		while g == 1:
			x = y
			for i in range(r):
				y = f(y)
			k = 0
			while k < r and g == 1:
				ys = y
				for i in range(min(m, r - k)):
					y = f(y)
					q = q * abs(x - y) % n
				g = gcd(q, n)
				k += m
			r <<= 1
		if g == n:
			g = 1
			while g == 1:
				ys = f(ys)
				g = gcd(abs(x - ys), n)
		if g < n:
			if isPrimeMR(g):
				return g
			elif isPrimeMR(n // g):
				return n // g
			return findFactorRho(g)

def primeFactor(n):
	i = 2
	ret = {}
	rhoFlg = 0
	while i * i <= n:
		k = 0
		while n % i == 0:
			n //= i
			k += 1
		if k:
			ret[i] = k
		i += 1 + i % 2
		if i == 101 and n >= 2 ** 20:
			while n > 1:
				if isPrimeMR(n):
					(ret[n], n) = (1, 1)
				else:
					rhoFlg = 1
					j = findFactorRho(n)
					k = 0
					while n % j == 0:
						n //= j
						k += 1
					ret[j] = k
	if n > 1:
		ret[n] = 1
	if rhoFlg:
		ret = {x: ret[x] for x in sorted(ret)}
	return ret

def divisors(n):
	res = [1]
	prime = primeFactor(n)
	for p in prime:
		newres = []
		for d in res:
			for j in range(prime[p] + 1):
				newres.append(d * p ** j)
		res = newres
	res.sort()
	return res

def xorfactorial(num):
	if num == 0:
		return 0
	elif num == 1:
		return 1
	elif num == 2:
		return 3
	elif num == 3:
		return 0
	else:
		x = baseorder(num)
		return 2 ** x * ((num - 2 ** x + 1) % 2) + function(num - 2 ** x)

def xorconv(n, X, Y):
	if n == 0:
		res = [X[0] * Y[0] % mod]
		return res
	x = [X[i] + X[i + 2 ** (n - 1)] for i in range(2 ** (n - 1))]
	y = [Y[i] + Y[i + 2 ** (n - 1)] for i in range(2 ** (n - 1))]
	z = [X[i] - X[i + 2 ** (n - 1)] for i in range(2 ** (n - 1))]
	w = [Y[i] - Y[i + 2 ** (n - 1)] for i in range(2 ** (n - 1))]
	res1 = xorconv(n - 1, x, y)
	res2 = xorconv(n - 1, z, w)
	former = [(res1[i] + res2[i]) * inv for i in range(2 ** (n - 1))]
	latter = [(res1[i] - res2[i]) * inv for i in range(2 ** (n - 1))]
	former = list(map(lambda x: x % mod, former))
	latter = list(map(lambda x: x % mod, latter))
	return former + latter

def merge_sort(A, B):
	(pos_A, pos_B) = (0, 0)
	(n, m) = (len(A), len(B))
	res = []
	while pos_A < n and pos_B < m:
		(a, b) = (A[pos_A], B[pos_B])
		if a < b:
			res.append(a)
			pos_A += 1
		else:
			res.append(b)
			pos_B += 1
	res += A[pos_A:]
	res += B[pos_B:]
	return res

class UnionFindVerSize:

	def __init__(self, N):
		self._parent = [n for n in range(0, N)]
		self._size = [1] * N
		self.group = N

	def find_root(self, x):
		if self._parent[x] == x:
			return x
		self._parent[x] = self.find_root(self._parent[x])
		stack = [x]
		while self._parent[stack[-1]] != stack[-1]:
			stack.append(self._parent[stack[-1]])
		for v in stack:
			self._parent[v] = stack[-1]
		return self._parent[x]

	def unite(self, x, y):
		gx = self.find_root(x)
		gy = self.find_root(y)
		if gx == gy:
			return
		self.group -= 1
		if self._size[gx] < self._size[gy]:
			self._parent[gx] = gy
			self._size[gy] += self._size[gx]
		else:
			self._parent[gy] = gx
			self._size[gx] += self._size[gy]

	def get_size(self, x):
		return self._size[self.find_root(x)]

	def is_same_group(self, x, y):
		return self.find_root(x) == self.find_root(y)

class WeightedUnionFind:

	def __init__(self, N):
		self.parent = [i for i in range(N)]
		self.size = [1 for i in range(N)]
		self.val = [0 for i in range(N)]
		self.flag = True
		self.edge = [[] for i in range(N)]

	def dfs(self, v, pv):
		stack = [(v, pv)]
		new_parent = self.parent[pv]
		while stack:
			(v, pv) = stack.pop()
			self.parent[v] = new_parent
			for (nv, w) in self.edge[v]:
				if nv != pv:
					self.val[nv] = self.val[v] + w
					stack.append((nv, v))

	def unite(self, x, y, w):
		if not self.flag:
			return
		if self.parent[x] == self.parent[y]:
			self.flag = self.val[x] - self.val[y] == w
			return
		if self.size[self.parent[x]] > self.size[self.parent[y]]:
			self.edge[x].append((y, -w))
			self.edge[y].append((x, w))
			self.size[x] += self.size[y]
			self.val[y] = self.val[x] - w
			self.dfs(y, x)
		else:
			self.edge[x].append((y, -w))
			self.edge[y].append((x, w))
			self.size[y] += self.size[x]
			self.val[x] = self.val[y] + w
			self.dfs(x, y)

class Dijkstra:

	class Edge:

		def __init__(self, _to, _cost):
			self.to = _to
			self.cost = _cost

	def __init__(self, V):
		self.G = [[] for i in range(V)]
		self._E = 0
		self._V = V

	@property
	def E(self):
		return self._E

	@property
	def V(self):
		return self._V

	def add_edge(self, _from, _to, _cost):
		self.G[_from].append(self.Edge(_to, _cost))
		self._E += 1

	def shortest_path(self, s):
		import heapq
		que = []
		d = [10 ** 15] * self.V
		d[s] = 0
		heapq.heappush(que, (0, s))
		while len(que) != 0:
			(cost, v) = heapq.heappop(que)
			if d[v] < cost:
				continue
			for i in range(len(self.G[v])):
				e = self.G[v][i]
				if d[e.to] > d[v] + e.cost:
					d[e.to] = d[v] + e.cost
					heapq.heappush(que, (d[e.to], e.to))
		return d

def Z_algorithm(s):
	N = len(s)
	Z_alg = [0] * N
	Z_alg[0] = N
	i = 1
	j = 0
	while i < N:
		while i + j < N and s[j] == s[i + j]:
			j += 1
		Z_alg[i] = j
		if j == 0:
			i += 1
			continue
		k = 1
		while i + k < N and k + Z_alg[k] < j:
			Z_alg[i + k] = Z_alg[k]
			k += 1
		i += k
		j -= k
	return Z_alg

class BIT:

	def __init__(self, n, mod=None):
		self.BIT = [0] * (n + 1)
		self.num = n
		self.mod = mod

	def query(self, idx):
		res_sum = 0
		mod = self.mod
		while idx > 0:
			res_sum += self.BIT[idx]
			if mod:
				res_sum %= mod
			idx -= idx & -idx
		return res_sum

	def update(self, idx, x):
		mod = self.mod
		while idx <= self.num:
			self.BIT[idx] += x
			self.BIT[idx] %= mod
			idx += idx & -idx
		return

class dancinglink:

	def __init__(self, n, debug=False):
		self.n = n
		self.debug = debug
		self._left = [i - 1 for i in range(n)]
		self._right = [i + 1 for i in range(n)]
		self.exist = [True for i in range(n)]

	def pop(self, k):
		if self.debug:
			assert self.exist[k]
		L = self._left[k]
		R = self._right[k]
		if L != -1:
			if R != self.n:
				(self._right[L], self._left[R]) = (R, L)
			else:
				self._right[L] = self.n
		elif R != self.n:
			self._left[R] = -1
		self.exist[k] = False

	def left(self, idx, k=1):
		if self.debug:
			assert self.exist[idx]
		res = idx
		while k:
			res = self._left[res]
			if res == -1:
				break
			k -= 1
		return res

	def right(self, idx, k=1):
		if self.debug:
			assert self.exist[idx]
		res = idx
		while k:
			res = self._right[res]
			if res == self.n:
				break
			k -= 1
		return res

class SparseTable:

	def __init__(self, A, merge_func, ide_ele):
		N = len(A)
		n = N.bit_length()
		self.table = [[ide_ele for i in range(n)] for i in range(N)]
		self.merge_func = merge_func
		for i in range(N):
			self.table[i][0] = A[i]
		for j in range(1, n):
			for i in range(0, N - 2 ** j + 1):
				f = self.table[i][j - 1]
				s = self.table[i + 2 ** (j - 1)][j - 1]
				self.table[i][j] = self.merge_func(f, s)

	def query(self, s, t):
		b = t - s + 1
		m = b.bit_length() - 1
		return self.merge_func(self.table[s][m], self.table[t - 2 ** m + 1][m])

class BinaryTrie:

	class node:

		def __init__(self, val):
			self.left = None
			self.right = None
			self.max = val

	def __init__(self):
		self.root = self.node(-10 ** 15)

	def append(self, key, val):
		pos = self.root
		for i in range(29, -1, -1):
			pos.max = max(pos.max, val)
			if key >> i & 1:
				if pos.right is None:
					pos.right = self.node(val)
					pos = pos.right
				else:
					pos = pos.right
			elif pos.left is None:
				pos.left = self.node(val)
				pos = pos.left
			else:
				pos = pos.left
		pos.max = max(pos.max, val)

	def search(self, M, xor):
		res = -10 ** 15
		pos = self.root
		for i in range(29, -1, -1):
			if pos is None:
				break
			if M >> i & 1:
				if xor >> i & 1:
					if pos.right:
						res = max(res, pos.right.max)
					pos = pos.left
				else:
					if pos.left:
						res = max(res, pos.left.max)
					pos = pos.right
			elif xor >> i & 1:
				pos = pos.right
			else:
				pos = pos.left
		if pos:
			res = max(res, pos.max)
		return res

def solveequation(edge, ans, n, m):
	x = [0] * m
	used = [False] * n
	for v in range(n):
		if used[v]:
			continue
		y = dfs(v)
		if y != 0:
			return False
	return x

	def dfs(v):
		used[v] = True
		r = ans[v]
		for (to, dire, id) in edge[v]:
			if used[to]:
				continue
			y = dfs(to)
			if dire == -1:
				x[id] = y
			else:
				x[id] = -y
			r += y
		return r

class Matrix:
	mod = 10 ** 9 + 7

	def set_mod(m):
		Matrix.mod = m

	def __init__(self, L):
		self.row = len(L)
		self.column = len(L[0])
		self._matrix = L
		for i in range(self.row):
			for j in range(self.column):
				self._matrix[i][j] %= Matrix.mod

	def __getitem__(self, item):
		if type(item) == int:
			raise IndexError('you must specific row and column')
		elif len(item) != 2:
			raise IndexError('you must specific row and column')
		(i, j) = item
		return self._matrix[i][j]

	def __setitem__(self, item, val):
		if type(item) == int:
			raise IndexError('you must specific row and column')
		elif len(item) != 2:
			raise IndexError('you must specific row and column')
		(i, j) = item
		self._matrix[i][j] = val

	def __add__(self, other):
		if (self.row, self.column) != (other.row, other.column):
			raise SizeError('sizes of matrixes are different')
		res = [[0 for j in range(self.column)] for i in range(self.row)]
		for i in range(self.row):
			for j in range(self.column):
				res[i][j] = self._matrix[i][j] + other._matrix[i][j]
				res[i][j] %= Matrix.mod
		return Matrix(res)

	def __sub__(self, other):
		if (self.row, self.column) != (other.row, other.column):
			raise SizeError('sizes of matrixes are different')
		res = [[0 for j in range(self.column)] for i in range(self.row)]
		for i in range(self.row):
			for j in range(self.column):
				res[i][j] = self._matrix[i][j] - other._matrix[i][j]
				res[i][j] %= Matrix.mod
		return Matrix(res)

	def __mul__(self, other):
		if type(other) != int:
			if self.column != other.row:
				raise SizeError('sizes of matrixes are different')
			res = [[0 for j in range(other.column)] for i in range(self.row)]
			for i in range(self.row):
				for j in range(other.column):
					temp = 0
					for k in range(self.column):
						temp += self._matrix[i][k] * other._matrix[k][j]
					res[i][j] = temp % Matrix.mod
			return Matrix(res)
		else:
			n = other
			res = [[n * self._matrix[i][j] % Matrix.mod for j in range(self.column)] for i in range(self.row)]
			return Matrix(res)

	def __pow__(self, m):
		if self.column != self.row:
			raise MatrixPowError('the size of row must be the same as that of column')
		n = self.row
		res = Matrix([[int(i == j) for i in range(n)] for j in range(n)])
		while m:
			if m % 2 == 1:
				res = res * self
			self = self * self
			m //= 2
		return res

	def __str__(self):
		res = []
		for i in range(self.row):
			for j in range(self.column):
				res.append(str(self._matrix[i][j]))
				res.append(' ')
			res.append('\n')
		res = res[:len(res) - 1]
		return ''.join(res)

class SegmentTree:

	def __init__(self, init_val, segfunc, ide_ele):
		n = len(init_val)
		self.segfunc = segfunc
		self.ide_ele = ide_ele
		self.num = 1 << (n - 1).bit_length()
		self.tree = [ide_ele] * 2 * self.num
		for i in range(n):
			self.tree[self.num + i] = init_val[i]
		for i in range(self.num - 1, 0, -1):
			self.tree[i] = self.segfunc(self.tree[2 * i], self.tree[2 * i + 1])

	def update(self, k, x):
		k += self.num
		self.tree[k] = x
		while k > 1:
			self.tree[k >> 1] = self.segfunc(self.tree[k], self.tree[k ^ 1])
			k >>= 1

	def query(self, l, r):
		res = self.ide_ele
		l += self.num
		r += self.num
		while l < r:
			if l & 1:
				res = self.segfunc(res, self.tree[l])
				l += 1
			if r & 1:
				res = self.segfunc(res, self.tree[r - 1])
			l >>= 1
			r >>= 1
		return res

	def bisect_l(self, l, r, x):
		l += self.num
		r += self.num
		Lmin = -1
		Rmin = -1
		while l < r:
			if l & 1:
				if self.tree[l] <= x and Lmin == -1:
					Lmin = l
				l += 1
			if r & 1:
				if self.tree[r - 1] <= x:
					Rmin = r - 1
			l >>= 1
			r >>= 1
		if Lmin != -1:
			pos = Lmin
			while pos < self.num:
				if self.tree[2 * pos] <= x:
					pos = 2 * pos
				else:
					pos = 2 * pos + 1
			return pos - self.num
		elif Rmin != -1:
			pos = Rmin
			while pos < self.num:
				if self.tree[2 * pos] <= x:
					pos = 2 * pos
				else:
					pos = 2 * pos + 1
			return pos - self.num
		else:
			return -1

def cmb(n, r, mod):
	if r < 0 or r > n:
		return 0
	r = min(r, n - r)
	return g1[n] * g2[r] % mod * g2[n - r] % mod
mod = 998244353
N = 6000
g1 = [1] * (N + 1)
g2 = [1] * (N + 1)
inverse = [1] * (N + 1)
for i in range(2, N + 1):
	g1[i] = g1[i - 1] * i % mod
	inverse[i] = -inverse[mod % i] * (mod // i) % mod
	g2[i] = g2[i - 1] * inverse[i] % mod
inverse[0] = 0
import sys, random, bisect
from collections import deque, defaultdict
from heapq import heapify, heappop, heappush
from itertools import permutations
from math import log, gcd
input = lambda : sys.stdin.readline().rstrip()
mi = lambda : map(int, input().split())
li = lambda : list(mi())
(p, s, r) = mi()
S = s
res = 0
for x in range(r, s + 1):
	for n in range(1, p):
		tmp = 0
		for i in range(p - n + 1):
			if s - (n + i) * x + p - n - 1 >= p - n - 1:
				if i % 2:
					tmp -= g1[s - (n + i) * x + p - n - 1] * g2[i] % mod * g2[p - n - i] % mod * g2[s - (n + i) * x] % mod
				else:
					tmp += g1[s - (n + i) * x + p - n - 1] * g2[i] % mod * g2[p - n - i] % mod * g2[s - (n + i) * x] % mod
				tmp %= mod
		res += tmp * inverse[n] % mod * cmb(p - 1, n - 1, mod) % mod * (p - n) % mod
		res %= mod
	if x * p == s:
		res += inverse[p]
		res %= mod
all_case = cmb(s - r + p - 1, p - 1, mod)
res *= pow(all_case, mod - 2, mod)
print(res % mod)