For problem statement at 1000-1999/1300-1399/1320-1329/1320/problemC.txt this is a correct solution, but verifier at 1000-1999/1300-1399/1320-1329/1320/verifierC.go ends with candidate execution failed: exit status 2
exit status 1 can you fix the verifier? ```go
package main
import (
"bufio"
"fmt"
"math"
"os"
"sort"
)
func main() {
reader := bufio.NewReader(os.Stdin)
var n, m, p int
fmt.Fscan(reader, &n, &m, &p)
type weapon struct {
a, ca int
}
type armor struct {
b, cb int
}
type monster struct {
x, y, z int
}
weapons := make([]weapon, n)
for i := 0; i < n; i++ {
fmt.Fscan(reader, &weapons[i].a, &weapons[i].ca)
}
armors := make([]armor, m)
for i := 0; i < m; i++ {
fmt.Fscan(reader, &armors[i].b, &armors[i].cb)
}
monsters := make([]monster, p)
for i := 0; i < p; i++ {
fmt.Fscan(reader, &monsters[i].x, &monsters[i].y, &monsters[i].z)
}
// Sort weapons by attack modifier
sort.Slice(weapons, func(i, j int) bool {
return weapons[i].a < weapons[j].a
})
// Sort armors by defense modifier
sort.Slice(armors, func(i, j int) bool {
return armors[i].b < armors[j].b
})
// Sort monsters by defense (x) value
sort.Slice(monsters, func(i, j int) bool {
return monsters[i].x < monsters[j].x
})
// For armors, we need a segment tree that supports:
// - point update: add value to a position
// - range max query
// But we want: for each weapon, we add monsters it can defeat,
// and query the best armor choice.
// For each armor index j, the segment tree stores:
// (sum of z_k for monsters defeated so far with b_j > y_k) - cb_j
// We want to maximize this over all j.
// We process weapons in increasing order of attack.
// For each weapon, we add new monsters that this weapon can defeat (a_i > x_k).
// When we add a monster with attack y_k, we need to add z_k to all armor indices j
// where b_j > y_k. Since armors are sorted, this is a suffix update.
// Segment tree with lazy propagation for range add and range max query.
size := m
tree := make([]int64, 4*size)
lazy := make([]int64, 4*size)
for i := range tree {
tree[i] = math.MinInt64
}
var build func(node, l, r int)
build = func(node, l, r int) {
if l == r {
tree[node] = int64(-armors[l].cb)
return
}
mid := (l + r) / 2
build(2*node, l, mid)
build(2*node+1, mid+1, r)
tree[node] = max64(tree[2*node], tree[2*node+1])
}
var pushDown func(node int)
pushDown = func(node int) {
if lazy[node] != 0 {
for _, child := range []int{2 * node, 2*node + 1} {
tree[child] += lazy[node]
lazy[child] += lazy[node]
}
lazy[node] = 0
}
}
var update func(node, l, r, ql, qr int, val int64)
update = func(node, l, r, ql, qr int, val int64) {
if ql > qr || l > qr || r < ql {
return
}
if ql <= l && r <= qr {
tree[node] += val
lazy[node] += val
return
}
pushDown(node)
mid := (l + r) / 2
update(2*node, l, mid, ql, qr, val)
update(2*node+1, mid+1, r, ql, qr, val)
tree[node] = max64(tree[2*node], tree[2*node+1])
}
build(1, 0, m-1)
ans := int64(math.MinInt64)
mi := 0 // monster index
// For each weapon in sorted order
// We also want minimum cost weapon for each attack value
// Actually, we should deduplicate weapons: for same attack, keep min cost
// But actually we iterate all weapons and just check each one.
// Better: for same attack value, only the cheapest matters
bestWeaponCost := make(map[int]int)
for _, w := range weapons {
if c, ok := bestWeaponCost[w.a]; !ok || w.ca < c {
bestWeaponCost[w.a] = w.ca
}
}
type wp struct{ a, ca int }
uniqueWeapons := make([]wp, 0, len(bestWeaponCost))
for a, ca := range bestWeaponCost {
uniqueWeapons = append(uniqueWeapons, wp{a, ca})
}
sort.Slice(uniqueWeapons, func(i, j int) bool { return uniqueWeapons[i].a < uniqueWeapons[j].a })
for _, w := range uniqueWeapons {
for mi < p && monsters[mi].x < w.a {
mon := monsters[mi]
// Add mon.z to all armors with b > mon.y
idx := sort.Search(m, func(i int) bool { return armors[i].b > mon.y })
if idx < m {
update(1, 0, m-1, idx, m-1, int64(mon.z))
}
mi++
}
val := tree[1] - int64(w.ca)
if val > ans {
ans = val
}
}
fmt.Println(ans)
}
func max64(a, b int64) int64 {
if a > b {
return a
}
return b
}
```