仔细审查题目描述中的所有约束条件,包括输入数据范围、输出格式限制以及特殊规则。例如,某些题目可能要求结果取模1e9+7,忽略这一要求会导致答案错误。使用注释标记关键约束,如:
// Constraints:
// 1 ≤ N ≤ 1e5
// Output must be in lowercase
建立常见输入规模与对应算法复杂度的映射表:
将功能拆分为可测试单元,例如:
vector parseInput() {
int n;
cin >> n;
vector data(n);
for (auto& x : data) cin >> x;
return data;
}
void validateOutput(int result) {
assert(result >= 0 && "Negative output");
}
掌握进阶STL用法提高效率:
auto cmp = [](pair a, pair b) {
return a.second > b.second; // 最小堆
};
priority_queue, vector>, decltype(cmp)> pq(cmp);
创建系统化的测试方案:
assert(maxSubarray({-1,-2,-3}) == -1);
建立分级调试输出机制:
#define LOG_LEVEL 3
#if LOG_LEVEL >= 1
cerr << "[INFO] " << variable << endl;
#endif
#if LOG_LEVEL >= 3
cerr << "[DETAIL] " << matrix.size() << endl;
#endif
针对不同语言优化IO:
inline int read() {
int x = 0;
char c = getchar();
while (c < '0' || c > '9') c = getchar();
while (c >= '0' && c <= '9') x = x*10 + c-'0', c = getchar();
return x;
}
建立常用记忆化模板:
template
auto memoize(function f) {
map cache;
return [f, cache](T x) mutable -> U {
if (!cache.count(x)) cache[x] = f(x);
return cache[x];
};
}
auto fib = memoize([](int64_t n) {
return n <= 1 ? n : fib(n-1) + fib(n-2);
});
识别可简化的数学模式:
vector> matrixMultiply(vector> a, vector> b) {
int n = a.size();
vector> res(n, vector(n));
for (int i = 0; i < n; ++i)
for (int j = 0; j < n; ++j)
for (int k = 0; k < n; ++k)
res[i][j] = (res[i][j] + a[i][k] * b[k][j]) % MOD;
return res;
}
维护分类代码片段库:
struct DSU {
vector parent, size;
DSU(int n) : parent(n), size(n,1) {
iota(parent.begin(), parent.end(), 0);
}
int find(int x) {
return parent[x] == x ? x : parent[x] = find(parent[x]);
}
bool unite(int x, int y) {
x = find(x), y = find(y);
if (x == y) return false;
if (size[x] < size[y]) swap(x,y);
parent[y] = x;
size[x] += size[y];
return true;
}
};