Problem:
Score : 100 points

Problem Statement

You are given a grid of N rows and M columns. The square at the i-th row and j-th column will be denoted as (i,j).
A nonnegative integer A_{i,j} is written for each square (i,j).

You choose some of the squares so that each row and column contains at most K chosen squares.
Under this constraint, calculate the maximum value of the sum of the integers written on the chosen squares.
Additionally, calculate a way to choose squares that acheives the maximum.

Constraints

1 \leq N \leq 50

1 \leq K \leq N

0 \leq A_{i,j} \leq 10^9

All values in Input are integer.

Input

Input is given from Standard Input in the following format:

N K
A_{1,1} A_{1,2} \cdots A_{1,N}
A_{2,1} A_{2,2} \cdots A_{2,N}
\vdots
A_{N,1} A_{N,2} \cdots A_{N,N}

Output

On the first line, print the maximum value of the sum of the integers written on the chosen squares.

On the next N lines, print a way that achieves the maximum.

Precisely, output the strings t_1,t_2,\cdots,t_N, that satisfies t_{i,j}=X if you choose (i,j) and t_{i,j}=. otherwise.

You may print any way to choose squares that maximizes the sum.

Sample Input 1

3 1
5 3 2
1 4 8
7 6 9

Sample Output 1

19
X..
..X
.X.

Sample Input 2

3 2
10 10 1
10 10 1
1 1 10

Sample Output 2

50
XX.
XX.
..X

Solution in Rust (1.42.0) (judge verdict: Wrong Answer)

mod internal_type_traits {
    use std::{
        fmt,
        iter::{Product, Sum},
        ops::{
            Add, AddAssign, BitAnd, BitAndAssign, BitOr, BitOrAssign, BitXor, BitXorAssign, Div,
            DivAssign, Mul, MulAssign, Not, Rem, RemAssign, Shl, ShlAssign, Shr, ShrAssign, Sub,
            SubAssign,
        },
    };
    
    // Skipped:
    //
    // - `is_signed_int_t<T>`   (probably won't be used directly in `modint.rs`)
    // - `is_unsigned_int_t<T>` (probably won't be used directly in `modint.rs`)
    // - `to_unsigned_t<T>`     (not used in `fenwicktree.rs`)
    
    /// Corresponds to `std::is_integral` in C++.
    // We will remove unnecessary bounds later.
    //
    // Maybe we should rename this to `PrimitiveInteger` or something, as it probably won't be used in the
    // same way as the original ACL.
    pub trait Integral:
        'static
        + Send
        + Sync
        + Copy
        + Ord
        + Not<Output = Self>
        + Add<Output = Self>
        + Sub<Output = Self>
        + Mul<Output = Self>
        + Div<Output = Self>
        + Rem<Output = Self>
        + AddAssign
        + SubAssign
        + MulAssign
        + DivAssign
        + RemAssign
        + Sum
        + Product
        + BitOr<Output = Self>
        + BitAnd<Output = Self>
        + BitXor<Output = Self>
        + BitOrAssign
        + BitAndAssign
        + BitXorAssign
        + Shl<Output = Self>
        + Shr<Output = Self>
        + ShlAssign
        + ShrAssign
        + fmt::Display
        + fmt::Debug
        + fmt::Binary
        + fmt::Octal
    {
        fn zero() -> Self;
        fn one() -> Self;
        fn min_value() -> Self;
        fn max_value() -> Self;
    }
    
    macro_rules! impl_integral {
        ($($ty:ty),*) => {
            $(
                impl Integral for $ty {
                    #[inline]
                    fn zero() -> Self {
                        0
                    }
    
                    #[inline]
                    fn one() -> Self {
                        1
                    }
    
                    #[inline]
                    fn min_value() -> Self {
                        Self::min_value()
                    }
    
                    #[inline]
                    fn max_value() -> Self {
                        Self::max_value()
                    }
                }
            )*
        };
    }
    
    impl_integral!(i8, i16, i32, i64, i128, isize, u8, u16, u32, u64, u128, usize);

}

mod mincostflow {
    use crate::internal_type_traits::Integral;

    pub struct MinCostFlowEdge<T> {
        pub from: usize,
        pub to: usize,
        pub cap: T,
        pub flow: T,
        pub cost: T,
    }
    
    pub struct MinCostFlowGraph<T> {
        pos: Vec<(usize, usize)>,
        g: Vec<Vec<_Edge<T>>>,
        cost_sum: T,
    }
    
    impl<T> MinCostFlowGraph<T>
    where
        T: Integral + std::ops::Neg<Output = T>,
    {
        pub fn new(n: usize) -> Self {
            Self {
                pos: vec![],
                g: (0..n).map(|_| vec![]).collect(),
                cost_sum: T::zero(),
            }
        }
    
        pub fn get_edge(&self, i: usize) -> MinCostFlowEdge<T> {
            assert!(i < self.pos.len());
            let e = &self.g[self.pos[i].0][self.pos[i].1];
            let re = &self.g[e.to][e.rev];
            MinCostFlowEdge {
                from: self.pos[i].0,
                to: e.to,
                cap: e.cap + re.cap,
                flow: re.cap,
                cost: e.cost,
            }
        }
    
        pub fn edges(&self) -> Vec<MinCostFlowEdge<T>> {
            let m = self.pos.len();
            let mut result = vec![];
            for i in 0..m {
                result.push(self.get_edge(i));
            }
            result
        }
    
        pub fn add_edge(&mut self, from: usize, to: usize, cap: T, cost: T) -> usize {
            assert!(from < self.g.len());
            assert!(to < self.g.len());
            assert_ne!(from, to);
            assert!(cap >= T::zero());
            assert!(cost >= T::zero());
    
            self.pos.push((from, self.g[from].len()));
            self.cost_sum += cost;
    
            let rev = self.g[to].len();
            self.g[from].push(_Edge { to, rev, cap, cost });
    
            let rev = self.g[from].len() - 1;
            self.g[to].push(_Edge {
                to: from,
                rev,
                cap: T::zero(),
                cost: -cost,
            });
    
            self.pos.len() - 1
        }
    
        /// Returns (maximum flow, cost)
        pub fn flow(&mut self, source: usize, sink: usize, flow_limit: T) -> (T, T) {
            self.slope(source, sink, flow_limit).pop().unwrap()
        }
    
        pub fn slope(&mut self, source: usize, sink: usize, flow_limit: T) -> Vec<(T, T)> {
            let n = self.g.len();
            assert!(source < n);
            assert!(sink < n);
            assert_ne!(source, sink);
    
            let mut dual = vec![T::zero(); n];
            let mut prev_v = vec![0; n];
            let mut prev_e = vec![0; n];
            let mut flow = T::zero();
            let mut cost = T::zero();
            let mut prev_cost: Option<T> = None;
            let mut result = vec![(flow, cost)];
            while flow < flow_limit {
                if !self.refine_dual(source, sink, &mut dual, &mut prev_v, &mut prev_e) {
                    break;
                }
    
                let mut c = flow_limit - flow;
                let mut v = sink;
                while v != source {
                    c = std::cmp::min(c, self.g[prev_v[v]][prev_e[v]].cap);
                    v = prev_v[v];
                }
    
                let mut v = sink;
                while v != source {
                    self.g[prev_v[v]][prev_e[v]].cap -= c;
                    let rev = self.g[prev_v[v]][prev_e[v]].rev;
                    self.g[v][rev].cap += c;
                    v = prev_v[v];
                }
    
                let d = -dual[source];
                flow += c;
                cost += d * c;
                if prev_cost == Some(d) {
                    assert!(result.pop().is_some());
                }
                result.push((flow, cost));
                prev_cost = Some(cost);
            }
            result
        }
    
        fn refine_dual(
            &self,
            source: usize,
            sink: usize,
            dual: &mut [T],
            pv: &mut [usize],
            pe: &mut [usize],
        ) -> bool {
            let n = self.g.len();
            let mut dist = vec![self.cost_sum; n];
            let mut vis = vec![false; n];
    
            let mut que = std::collections::BinaryHeap::new();
            dist[source] = T::zero();
            que.push((std::cmp::Reverse(T::zero()), source));
            while let Some((_, v)) = que.pop() {
                if vis[v] {
                    continue;
                }
                vis[v] = true;
                if v == sink {
                    break;
                }
    
                for (i, e) in self.g[v].iter().enumerate() {
                    if vis[e.to] || e.cap == T::zero() {
                        continue;
                    }
    
                    let cost = e.cost - dual[e.to] + dual[v];
                    if dist[e.to] - dist[v] > cost {
                        dist[e.to] = dist[v] + cost;
                        pv[e.to] = v;
                        pe[e.to] = i;
                        que.push((std::cmp::Reverse(dist[e.to]), e.to));
                    }
                }
            }
    
            if !vis[sink] {
                return false;
            }
    
            for v in 0..n {
                if !vis[v] {
                    continue;
                }
                dual[v] -= dist[sink] - dist[v];
            }
            true
        }
    }
    
    struct _Edge<T> {
        to: usize,
        rev: usize,
        cap: T,
        cost: T,
    }
}

use mincostflow::MinCostFlowGraph;
use std::io::Read;

const MAX: i64 = 1_000_000_000;

fn main() {
    let mut buf = String::new();
    std::io::stdin().read_to_string(&mut buf).unwrap();
    let mut input = buf.split_whitespace();

    let n = input.next().unwrap().parse().unwrap();
    let k = input.next().unwrap().parse().unwrap();
    let a: Vec<Vec<i64>> = (0..n)
        .map(|_| input.by_ref().take(n).map(|s| s.parse().unwrap()).collect())
        .collect();

    let mut graph = construct_graph(n, k, &a);
    let max_flow = graph
        .slope(100, 101, i64::max_value())
        .iter()
        .max_by_key(|(max_flow, min_cost)| max_flow * MAX - min_cost)
        .unwrap()
        .0;

    let mut graph = construct_graph(n, k, &a);
    let (max_flow, min_cost) = graph.flow(100, 101, max_flow);
    let ans = max_flow * MAX - min_cost;

    println!("{}", ans);
    (0..n)
        .map(|i| {
            (0..n)
                .map(|j| match graph.get_edge(i * n + j).flow {
                    1 => 'X',
                    _ => '.',
                })
                .collect()
        })
        .for_each(|s: String| println!("{}", s));
}

fn construct_graph(n: usize, k: i64, a: &[Vec<i64>]) -> MinCostFlowGraph<i64> {
    let mut graph = MinCostFlowGraph::new(102);
    for i in 0..n {
        for j in 0..n {
            graph.add_edge(i, 50 + j, 1, MAX - a[i][j]);
        }
    }
    for i in 0..n {
        graph.add_edge(100, i, k, 0);
        graph.add_edge(50 + i, 101, k, 0);
    }
    graph
}