diff --git a/codes/rust/Cargo.toml b/codes/rust/Cargo.toml
index 206578d22..358ab3421 100644
--- a/codes/rust/Cargo.toml
+++ b/codes/rust/Cargo.toml
@@ -249,5 +249,50 @@ path = "chapter_graph/graph_bfs.rs"
 name = "graph_dfs"
 path = "chapter_graph/graph_dfs.rs"
 
+# Run Command: cargo run --bin coin_change
+[[bin]]
+name = "coin_change"
+path = "chapter_dynamic_programming/coin_change.rs"
+
+# Run Command: cargo run --bin coin_change_ii
+[[bin]]
+name = "coin_change_ii"
+path = "chapter_dynamic_programming/coin_change_ii.rs"
+
+# Run Command: cargo run --bin unbounded_knapsack
+[[bin]]
+name = "unbounded_knapsack"
+path = "chapter_dynamic_programming/unbounded_knapsack.rs"
+
+# Run Command: cargo run --bin knapsack
+[[bin]]
+name = "knapsack"
+path = "chapter_dynamic_programming/knapsack.rs"
+
+# Run Command: cargo run --bin min_path_sum
+[[bin]]
+name = "min_path_sum"
+path = "chapter_dynamic_programming/min_path_sum.rs"
+
+# Run Command: cargo run --bin edit_distance
+[[bin]]
+name = "edit_distance"
+path = "chapter_dynamic_programming/edit_distance.rs"
+
+# Run Command: cargo run --bin n_queens
+[[bin]]
+name = "n_queens"
+path = "chapter_backtracking/n_queens.rs"
+
+# Run Command: cargo run --bin permutations_i
+[[bin]]
+name = "permutations_i"
+path = "chapter_backtracking/permutations_i.rs"
+
+# Run Command: cargo run --bin permutations_ii
+[[bin]]
+name = "permutations_ii"
+path = "chapter_backtracking/permutations_ii.rs"
+
 [dependencies]
 rand = "0.8.5"
diff --git a/codes/rust/chapter_backtracking/n_queens.rs b/codes/rust/chapter_backtracking/n_queens.rs
new file mode 100644
index 000000000..ffa5b890f
--- /dev/null
+++ b/codes/rust/chapter_backtracking/n_queens.rs
@@ -0,0 +1,72 @@
+/*
+ * File: n_queens.rs
+ * Created Time: 2023-07-15
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 回溯算法：N 皇后 */
+fn backtrack(row: usize, n: usize, state: &mut Vec<Vec<String>>, res: &mut Vec<Vec<Vec<String>>>,
+    cols: &mut [bool], diags1: &mut [bool], diags2: &mut [bool]) {
+    // 当放置完所有行时，记录解
+    if row == n {
+        let mut copy_state: Vec<Vec<String>> = Vec::new();
+        for s_row in state.clone() {
+            copy_state.push(s_row);
+        }
+        res.push(copy_state);
+        return;
+    }
+    // 遍历所有列
+    for col in 0..n {
+        // 计算该格子对应的主对角线和副对角线
+        let diag1 = row + n - 1 - col;
+        let diag2 = row + col;
+        // 剪枝：不允许该格子所在列、主对角线、副对角线存在皇后
+        if !cols[col] && !diags1[diag1] && !diags2[diag2] {
+            // 尝试：将皇后放置在该格子
+            state.get_mut(row).unwrap()[col] = "Q".into();
+            (cols[col], diags1[diag1], diags2[diag2]) = (true, true, true);
+            // 放置下一行
+            backtrack(row + 1, n, state, res, cols, diags1, diags2);
+            // 回退：将该格子恢复为空位
+            state.get_mut(row).unwrap()[col] = "#".into();
+            (cols[col], diags1[diag1], diags2[diag2]) = (false, false, false);
+        }
+    }
+}
+
+/* 求解 N 皇后 */
+fn n_queens(n: usize) -> Vec<Vec<Vec<String>>> {
+    // 初始化 n*n 大小的棋盘，其中 'Q' 代表皇后，'#' 代表空位
+    let mut state: Vec<Vec<String>> = Vec::new();
+    for _ in 0..n {
+        let mut row: Vec<String> = Vec::new();
+        for _ in 0..n {
+            row.push("#".into());
+        }
+        state.push(row);
+    }
+    let mut cols = vec![false; n]; // 记录列是否有皇后
+    let mut diags1 = vec![false; 2 * n - 1]; // 记录主对角线是否有皇后
+    let mut diags2 = vec![false; 2 * n - 1]; // 记录副对角线是否有皇后
+    let mut res: Vec<Vec<Vec<String>>> = Vec::new();
+
+    backtrack(0, n, &mut state, &mut res, &mut cols, &mut diags1, &mut diags2);
+
+    res
+}
+
+/* Driver Code */
+pub fn main() {
+    let n: usize = 4;
+    let res = n_queens(n);
+
+    println!("输入棋盘长宽为 {n}");
+    println!("皇后放置方案共有 {} 种", res.len());
+    for state in res.iter() {
+        println!("--------------------");
+        for row in state.iter() {
+            println!("{:?}", row);
+        }
+    }
+}
diff --git a/codes/rust/chapter_backtracking/permutations_i.rs b/codes/rust/chapter_backtracking/permutations_i.rs
new file mode 100644
index 000000000..3c41a458c
--- /dev/null
+++ b/codes/rust/chapter_backtracking/permutations_i.rs
@@ -0,0 +1,46 @@
+/*
+ * File: permutations_i.rs
+ * Created Time: 2023-07-15
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 回溯算法：全排列 I */
+fn backtrack(mut state: Vec<i32>, choices: &[i32], selected: &mut [bool], res: &mut Vec<Vec<i32>>) {
+    // 当状态长度等于元素数量时，记录解
+    if state.len() == choices.len() {
+        res.push(state);
+        return;
+    }
+    // 遍历所有选择
+    for i in 0..choices.len() {
+        let choice = choices[i];
+        // 剪枝：不允许重复选择元素 且 不允许重复选择相等元素
+        if !selected[i] {
+            // 尝试：做出选择，更新状态
+            selected[i] = true;
+            state.push(choice);
+            // 进行下一轮选择
+            backtrack(state.clone(), choices, selected, res);
+            // 回退：撤销选择，恢复到之前的状态
+            selected[i] = false;
+            state.remove(state.len() - 1);
+        }
+    }
+}
+
+/* 全排列 I */
+fn permutations_i(nums: &mut [i32]) -> Vec<Vec<i32>> {
+    let mut res = Vec::new(); // 状态（子集）
+    backtrack(Vec::new(), nums, &mut vec![false; nums.len()], &mut res);
+    res
+}
+
+/* Driver Code */
+pub fn main() {
+    let mut nums = [ 1, 2, 3 ];
+
+    let res = permutations_i(&mut nums);
+
+    println!("输入数组 nums = {:?}", &nums);
+    println!("所有排列 res = {:?}", &res);
+}
diff --git a/codes/rust/chapter_backtracking/permutations_ii.rs b/codes/rust/chapter_backtracking/permutations_ii.rs
new file mode 100644
index 000000000..a93fe2e1f
--- /dev/null
+++ b/codes/rust/chapter_backtracking/permutations_ii.rs
@@ -0,0 +1,50 @@
+/*
+ * File: permutations_ii.rs
+ * Created Time: 2023-07-15
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+use std::collections::HashSet;
+
+/* 回溯算法：全排列 II */
+fn backtrack(mut state: Vec<i32>, choices: &[i32], selected: &mut [bool], res: &mut Vec<Vec<i32>>) {
+    // 当状态长度等于元素数量时，记录解
+    if state.len() == choices.len() {
+        res.push(state);
+        return;
+    }
+    // 遍历所有选择
+    let mut duplicated = HashSet::<i32>::new();
+    for i in 0..choices.len() {
+        let choice = choices[i];
+        // 剪枝：不允许重复选择元素 且 不允许重复选择相等元素
+        if !selected[i] && !duplicated.contains(&choice) {
+            // 尝试：做出选择，更新状态
+            duplicated.insert(choice); // 记录选择过的元素值
+            selected[i] = true;
+            state.push(choice);
+            // 进行下一轮选择
+            backtrack(state.clone(), choices, selected, res);
+            // 回退：撤销选择，恢复到之前的状态
+            selected[i] = false;
+            state.remove(state.len() - 1);
+        }
+    }
+}
+
+/* 全排列 II */
+fn permutations_ii(nums: &mut [i32]) -> Vec<Vec<i32>> {
+    let mut res = Vec::new();
+    backtrack(Vec::new(), nums, &mut vec![false; nums.len()], &mut res);
+    res
+}
+
+/* Driver Code */
+pub fn main() {
+    let mut nums = [ 1, 2, 2 ];
+
+    let res = permutations_ii(&mut nums);
+
+    println!("输入数组 nums = {:?}", &nums);
+    println!("所有排列 res = {:?}", &res);
+}
diff --git a/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs.rs b/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs.rs
index 7f33cb43a..c5e9b1ac1 100644
--- a/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs.rs
+++ b/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs.rs
@@ -7,7 +7,7 @@
 /* 搜索 */
 fn dfs(i: usize) -> i32 {
     // 已知 dp[1] 和 dp[2] ，返回之
-    if i == 1 || i == 2 { return i as i32 };
+    if i == 1 || i == 2 { return i as i32; }
     // dp[i] = dp[i-1] + dp[i-2]
     let count = dfs(i - 1) + dfs(i - 2);
     count
diff --git a/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs_mem.rs b/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs_mem.rs
index b7ef74a12..cb02c623a 100644
--- a/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs_mem.rs
+++ b/codes/rust/chapter_dynamic_programming/climbing_stairs_dfs_mem.rs
@@ -7,9 +7,9 @@
 /* 记忆化搜索 */
 fn dfs(i: usize, mem: &mut [i32]) -> i32 {
     // 已知 dp[1] 和 dp[2] ，返回之
-    if i == 1 || i == 2 { return i as i32};
+    if i == 1 || i == 2 { return i as i32; }
     // 若存在记录 dp[i] ，则直接返回之
-    if mem[i] != -1 { return mem[i] };
+    if mem[i] != -1 { return mem[i]; }
     // dp[i] = dp[i-1] + dp[i-2]
     let count = dfs(i - 1, mem) + dfs(i - 2, mem);
     // 记录 dp[i]
diff --git a/codes/rust/chapter_dynamic_programming/climbing_stairs_dp.rs b/codes/rust/chapter_dynamic_programming/climbing_stairs_dp.rs
index 2fdee62ea..75bbe79df 100644
--- a/codes/rust/chapter_dynamic_programming/climbing_stairs_dp.rs
+++ b/codes/rust/chapter_dynamic_programming/climbing_stairs_dp.rs
@@ -7,7 +7,7 @@
 /* 爬楼梯：动态规划 */
 fn climbing_stairs_dp(n: usize) -> i32 {
     // 已知 dp[1] 和 dp[2] ，返回之
-    if n == 1 || n == 2 { return n as i32 };
+    if n == 1 || n == 2 { return n as i32; }
     // 初始化 dp 表，用于存储子问题的解
     let mut dp = vec![-1; n + 1];
     // 初始状态：预设最小子问题的解
@@ -22,7 +22,7 @@ fn climbing_stairs_dp(n: usize) -> i32 {
 
 /* 爬楼梯：状态压缩后的动态规划 */
 fn climbing_stairs_dp_comp(n: usize) -> i32 {
-    if n == 1 || n == 2 { return n as i32 };
+    if n == 1 || n == 2 { return n as i32; }
     let (mut a, mut b) = (1, 2);
     for _ in 3..=n {
         let tmp = b;
diff --git a/codes/rust/chapter_dynamic_programming/coin_change.rs b/codes/rust/chapter_dynamic_programming/coin_change.rs
new file mode 100644
index 000000000..4a976887d
--- /dev/null
+++ b/codes/rust/chapter_dynamic_programming/coin_change.rs
@@ -0,0 +1,67 @@
+/*
+ * File: coin_change.rs
+ * Created Time: 2023-07-09
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 零钱兑换：动态规划 */
+fn coin_change_dp(coins: &[i32], amt: usize) -> i32 {
+    let n = coins.len();
+    let max = amt + 1;
+    // 初始化 dp 表
+    let mut dp = vec![vec![0; amt + 1]; n + 1];
+    // 状态转移：首行首列
+    for a in 1..= amt {
+        dp[0][a] = max;
+    }
+    // 状态转移：其余行列
+    for i in 1..=n {
+        for a in 1..=amt {
+            if coins[i - 1] > a as i32 {
+                // 若超过背包容量，则不选硬币 i
+                dp[i][a] = dp[i - 1][a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[i][a] = std::cmp::min(dp[i - 1][a], dp[i][a - coins[i - 1] as usize] + 1);
+            }
+        }
+    }
+    if dp[n][amt] != max { return dp[n][amt] as i32; } else { -1 }
+}
+
+/* 零钱兑换：状态压缩后的动态规划 */
+fn coin_change_dp_comp(coins: &[i32], amt: usize) -> i32 {
+    let n = coins.len();
+    let max = amt + 1;
+    // 初始化 dp 表
+    let mut dp = vec![0; amt + 1];
+    dp.fill(max);
+    dp[0] = 0;
+    // 状态转移
+    for i in 1..=n {
+        for a in 1..=amt {
+            if coins[i - 1] > a as i32 {
+                // 若超过背包容量，则不选硬币 i
+                dp[a] = dp[a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[a] = std::cmp::min(dp[a], dp[a - coins[i - 1] as usize] + 1);
+            }
+        }
+    }
+    if dp[amt] != max { return dp[amt] as i32; } else { -1 }
+}
+
+/* Driver Code */
+pub fn main() {
+    let coins = [ 1, 2, 5 ];
+    let amt: usize = 4;
+
+    // 动态规划
+    let res = coin_change_dp(&coins, amt);
+    println!("凑到目标金额所需的最少硬币数量为 {res}");
+
+    // 状态压缩后的动态规划
+    let res = coin_change_dp_comp(&coins, amt);
+    println!("凑到目标金额所需的最少硬币数量为 {res}");
+}
diff --git a/codes/rust/chapter_dynamic_programming/coin_change_ii.rs b/codes/rust/chapter_dynamic_programming/coin_change_ii.rs
new file mode 100644
index 000000000..6e8090515
--- /dev/null
+++ b/codes/rust/chapter_dynamic_programming/coin_change_ii.rs
@@ -0,0 +1,64 @@
+/*
+ * File: coin_change_ii.rs
+ * Created Time: 2023-07-09
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 零钱兑换 II：动态规划 */
+fn coin_change_ii_dp(coins: &[i32], amt: usize) -> i32 {
+    let n = coins.len();
+    // 初始化 dp 表
+    let mut dp = vec![vec![0; amt + 1]; n + 1];
+    // 初始化首列
+    for i in 0..= n {
+        dp[i][0] = 1;
+    }
+    // 状态转移
+    for i in 1..=n {
+        for a in 1..=amt {
+            if coins[i - 1] > a as i32 {
+                // 若超过背包容量，则不选硬币 i
+                dp[i][a] = dp[i - 1][a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[i][a] = dp[i - 1][a] + dp[i][a - coins[i - 1] as usize];
+            }
+        }
+    }
+    dp[n][amt]
+}
+
+/* 零钱兑换 II：状态压缩后的动态规划 */
+fn coin_change_dp_ii_comp(coins: &[i32], amt: usize) -> i32 {
+    let n = coins.len();
+    // 初始化 dp 表
+    let mut dp = vec![0; amt + 1];
+    dp[0] = 1;
+    // 状态转移
+    for i in 1..=n {
+        for a in 1..=amt {
+            if coins[i - 1] > a as i32 {
+                // 若超过背包容量，则不选硬币 i
+                dp[a] = dp[a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[a] = dp[a] + dp[a - coins[i - 1] as usize];
+            }
+        }
+    }
+    dp[amt]
+}
+
+/* Driver Code */
+pub fn main() {
+    let coins = [ 1, 2, 5 ];
+    let amt: usize = 5;
+
+    // 动态规划
+    let res = coin_change_ii_dp(&coins, amt);
+    println!("凑出目标金额的硬币组合数量为 {res}");
+
+    // 状态压缩后的动态规划
+    let res = coin_change_dp_ii_comp(&coins, amt);
+    println!("凑出目标金额的硬币组合数量为 {res}");
+}
diff --git a/codes/rust/chapter_dynamic_programming/edit_distance.rs b/codes/rust/chapter_dynamic_programming/edit_distance.rs
new file mode 100644
index 000000000..2bef9fa34
--- /dev/null
+++ b/codes/rust/chapter_dynamic_programming/edit_distance.rs
@@ -0,0 +1,130 @@
+/*
+ * File: edit_distance.rs
+ * Created Time: 2023-07-09
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 编辑距离：暴力搜索 */
+fn edit_distance_dfs(s: &str, t: &str, i: usize, j: usize) -> i32 {
+    // 若 s 和 t 都为空，则返回 0
+    if i == 0 && j == 0 { return 0; }
+    // 若 s 为空，则返回 t 长度
+    if i == 0 { return j as i32; }
+    // 若 t 为空，则返回 s 长度
+    if j == 0 {return i as i32; }
+    // 若两字符相等，则直接跳过此两字符
+    if s.chars().nth(i - 1) == t.chars().nth(j - 1) {
+        return edit_distance_dfs(s, t, i - 1, j - 1);
+    }
+    // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+    let insert = edit_distance_dfs(s, t, i, j - 1);
+    let delete = edit_distance_dfs(s, t, i - 1, j);
+    let replace = edit_distance_dfs(s, t, i - 1, j - 1);
+    // 返回最少编辑步数
+    std::cmp::min(std::cmp::min(insert, delete), replace) + 1
+}
+
+/* 编辑距离：记忆化搜索 */
+fn edit_distance_dfs_mem(s: &str, t: &str, mem: &mut Vec<Vec<i32>>, i: usize, j: usize) -> i32 {
+    // 若 s 和 t 都为空，则返回 0
+    if i == 0 && j == 0 { return 0; }
+    // 若 s 为空，则返回 t 长度
+    if i == 0 { return j as i32; }
+    // 若 t 为空，则返回 s 长度
+    if j == 0 {return i as i32; }
+    // 若已有记录，则直接返回之
+    if mem[i][j] != -1 { return mem[i][j]; }
+    // 若两字符相等，则直接跳过此两字符
+    if s.chars().nth(i - 1) == t.chars().nth(j - 1) {
+        return edit_distance_dfs_mem(s, t, mem, i - 1, j - 1);
+    }
+    // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+    let insert = edit_distance_dfs_mem(s, t, mem, i, j - 1);
+    let delete = edit_distance_dfs_mem(s, t, mem, i - 1, j);
+    let replace = edit_distance_dfs_mem(s, t, mem, i - 1, j - 1);
+    // 记录并返回最少编辑步数
+    mem[i][j] = std::cmp::min(std::cmp::min(insert, delete), replace) + 1;
+    mem[i][j]
+}
+
+/* 编辑距离：动态规划 */
+fn edit_distance_dp(s: &str, t: &str) -> i32 {
+    let (n, m) = (s.len(), t.len());
+    let mut dp = vec![vec![0; m + 1]; n + 1];
+    // 状态转移：首行首列
+    for i in 1..= n {
+        dp[i][0] = i as i32;
+    }
+    for j in 1..m {
+        dp[0][j] = j as i32;
+    }
+    // 状态转移：其余行列
+    for i in 1..=n {
+        for j in 1..=m {
+            if s.chars().nth(i - 1) == t.chars().nth(j - 1) {
+                // 若两字符相等，则直接跳过此两字符
+                dp[i][j] = dp[i - 1][j - 1];
+            } else {
+                // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+                dp[i][j] = std::cmp::min(std::cmp::min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
+            }
+        }
+    }
+    dp[n][m]
+}
+
+/* 编辑距离：状态压缩后的动态规划 */
+fn edit_distance_dp_comp(s: &str, t: &str) -> i32 {
+    let (n, m) = (s.len(), t.len());
+    let mut dp = vec![0; m + 1];
+    // 状态转移：首行
+    for j in 1..m {
+        dp[j] = j as i32;
+    }
+    // 状态转移：其余行
+    for i in 1..=n {
+        // 状态转移：首列
+        let mut leftup = dp[0]; // 暂存 dp[i-1, j-1]
+        dp[0] = i as i32;
+        // 状态转移：其余列
+        for j in 1..=m {
+            let temp = dp[j];
+            if s.chars().nth(i - 1) == t.chars().nth(j - 1) {
+                // 若两字符相等，则直接跳过此两字符
+                dp[j] = leftup;
+            } else {
+                // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+                dp[j] = std::cmp::min(std::cmp::min(dp[j - 1], dp[j]), leftup) + 1;
+            }
+            leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
+        }
+    }
+    dp[m]
+}
+
+/* Driver Code */
+pub fn main() {
+    let s = "bag";
+    let t = "pack";
+    let (n, m) = (s.len(), t.len());
+
+    // 暴力搜索
+    let res = edit_distance_dfs(s, t, n, m);
+    println!("将 {s} 更改为 {t} 最少需要编辑 {res} 步");
+
+    // 记忆搜索
+    let mut mem = vec![vec![0; m + 1]; n + 1];
+    for row in mem.iter_mut() {
+        row.fill(-1);
+    }
+    let res = edit_distance_dfs_mem(s, t, &mut mem, n, m);
+    println!("将 {s} 更改为 {t} 最少需要编辑 {res} 步");
+
+    // 动态规划
+    let res = edit_distance_dp(s, t);
+    println!("将 {s} 更改为 {t} 最少需要编辑 {res} 步");
+
+    // 状态压缩后的动态规划
+    let res = edit_distance_dp_comp(s, t);
+    println!("将 {s} 更改为 {t} 最少需要编辑 {res} 步");
+}
diff --git a/codes/rust/chapter_dynamic_programming/knapsack.rs b/codes/rust/chapter_dynamic_programming/knapsack.rs
new file mode 100644
index 000000000..d31c8fc28
--- /dev/null
+++ b/codes/rust/chapter_dynamic_programming/knapsack.rs
@@ -0,0 +1,110 @@
+/*
+ * File: knapsack.rs
+ * Created Time: 2023-07-09
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 0-1 背包：暴力搜索 */
+fn knapsack_dfs(wgt: &[i32], val: &[i32], i: usize, c: usize) -> i32 {
+    // 若已选完所有物品或背包无容量，则返回价值 0
+    if i == 0 || c == 0 {
+        return 0;
+    }
+    // 若超过背包容量，则只能不放入背包
+    if wgt[i - 1] > c as i32 {
+        return knapsack_dfs(wgt, val, i - 1, c);
+    }
+    // 计算不放入和放入物品 i 的最大价值
+    let no = knapsack_dfs(wgt, val, i - 1, c);
+    let yes = knapsack_dfs(wgt, val, i - 1, c - wgt[i - 1] as usize) + val[i - 1];
+    // 返回两种方案中价值更大的那一个
+    std::cmp::max(no, yes)
+}
+
+/* 0-1 背包：记忆化搜索 */
+fn knapsack_dfs_mem(wgt: &[i32], val: &[i32], mem: &mut Vec<Vec<i32>>, i: usize, c: usize) -> i32 {
+    // 若已选完所有物品或背包无容量，则返回价值 0
+    if i == 0 || c == 0 {
+        return 0;
+    }
+    // 若已有记录，则直接返回
+    if mem[i][c] != -1 {
+        return mem[i][c];
+    }
+    // 若超过背包容量，则只能不放入背包
+    if wgt[i - 1] > c as i32 {
+        return knapsack_dfs_mem(wgt, val, mem, i - 1, c);
+    }
+    // 计算不放入和放入物品 i 的最大价值
+    let no = knapsack_dfs_mem(wgt, val, mem, i - 1, c);
+    let yes = knapsack_dfs_mem(wgt, val, mem, i - 1, c - wgt[i - 1] as usize) + val[i - 1];
+    // 记录并返回两种方案中价值更大的那一个
+    mem[i][c] = std::cmp::max(no, yes);
+    mem[i][c]
+}
+
+/* 0-1 背包：动态规划 */
+fn knapsack_dp(wgt: &[i32], val: &[i32], cap: usize) -> i32 {
+    let n = wgt.len();
+    // 初始化 dp 表
+    let mut dp = vec![vec![0; cap + 1]; n + 1];
+    // 状态转移
+    for i in 1..=n {
+        for c in 1..=cap {
+            if wgt[i - 1] > c as i32 {
+                // 若超过背包容量，则不选物品 i
+                dp[i][c] = dp[i - 1][c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[i][c] = std::cmp::max(dp[i - 1][c], dp[i - 1][c - wgt[i - 1] as usize] + val[i - 1]);
+            }
+        }
+    }
+    dp[n][cap]
+}
+
+/* 0-1 背包：状态压缩后的动态规划 */
+fn knapsack_dp_comp(wgt: &[i32], val: &[i32], cap: usize) -> i32 {
+    let n = wgt.len();
+    // 初始化 dp 表
+    let mut dp = vec![0; cap + 1];
+    // 状态转移
+    for i in 1..=n {
+        // 倒序遍历
+        for c in (1..=cap).rev() {
+            if wgt[i - 1] <= c as i32 {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[c] = std::cmp::max(dp[c], dp[c - wgt[i - 1] as usize] + val[i - 1]);
+            }
+        }
+    }
+    dp[cap]
+}
+
+/* Driver Code */
+pub fn main() {
+    let wgt = [ 10, 20, 30, 40, 50 ];
+    let val = [ 50, 120, 150, 210, 240 ];
+    let cap: usize = 50;
+    let n = wgt.len();
+
+    // 暴力搜索
+    let res = knapsack_dfs(&wgt, &val, n, cap);
+    println!("不超过背包容量的最大物品价值为 {res}");
+
+    // 记忆搜索
+    let mut mem = vec![vec![0; cap + 1]; n + 1];
+    for row in mem.iter_mut() {
+        row.fill(-1);
+    }
+    let res = knapsack_dfs_mem(&wgt, &val, &mut mem, n, cap);
+    println!("不超过背包容量的最大物品价值为 {res}");
+
+    // 动态规划
+    let res = knapsack_dp(&wgt, &val, cap);
+    println!("不超过背包容量的最大物品价值为 {res}");
+
+    // 状态压缩后的动态规划
+    let res = knapsack_dp_comp(&wgt, &val, cap);
+    println!("不超过背包容量的最大物品价值为 {res}");
+}
diff --git a/codes/rust/chapter_dynamic_programming/min_cost_climbing_stairs_dp.rs b/codes/rust/chapter_dynamic_programming/min_cost_climbing_stairs_dp.rs
index a92a0b45e..c6b9c029c 100644
--- a/codes/rust/chapter_dynamic_programming/min_cost_climbing_stairs_dp.rs
+++ b/codes/rust/chapter_dynamic_programming/min_cost_climbing_stairs_dp.rs
@@ -9,7 +9,7 @@
 /* 爬楼梯最小代价：动态规划 */
 fn min_cost_climbing_stairs_dp(cost: &[i32]) -> i32 {
     let n = cost.len() - 1;
-    if n == 1 || n == 2 { return cost[n] };
+    if n == 1 || n == 2 { return cost[n]; }
     // 初始化 dp 表，用于存储子问题的解
     let mut dp = vec![-1; n + 1];
     // 初始状态：预设最小子问题的解
diff --git a/codes/rust/chapter_dynamic_programming/min_path_sum.rs b/codes/rust/chapter_dynamic_programming/min_path_sum.rs
new file mode 100644
index 000000000..8dcd36704
--- /dev/null
+++ b/codes/rust/chapter_dynamic_programming/min_path_sum.rs
@@ -0,0 +1,119 @@
+/*
+ * File: min_path_sum.rs
+ * Created Time: 2023-07-09
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 最小路径和：暴力搜索 */
+fn min_path_sum_dfs(grid: &Vec<Vec<i32>>, i: i32, j: i32) -> i32 {
+    // 若为左上角单元格，则终止搜索
+    if i == 0 && j == 0 {
+        return grid[0][0];
+    }
+    // 若行列索引越界，则返回 +∞ 代价
+    if i < 0 || j < 0 {
+        return i32::MAX;
+    }
+    // 计算从左上角到 (i-1, j) 和 (i, j-1) 的最小路径代价
+    let left = min_path_sum_dfs(grid, i - 1, j);
+    let up = min_path_sum_dfs(grid, i, j - 1);
+    // 返回从左上角到 (i, j) 的最小路径代价
+    std::cmp::min(left, up) + grid[i as usize][j as usize]
+}
+
+/* 最小路径和：记忆化搜索 */
+fn min_path_sum_dfs_mem(grid: &Vec<Vec<i32>>, mem: &mut Vec<Vec<i32>>, i: i32, j: i32) -> i32 {
+    // 若为左上角单元格，则终止搜索
+    if i == 0 && j == 0 {
+        return grid[0][0];
+    }
+    // 若行列索引越界，则返回 +∞ 代价
+    if i < 0 || j < 0 {
+        return i32::MAX;
+    }
+    // 若已有记录，则直接返回
+    if mem[i as usize][j as usize] != -1 {
+        return mem[i as usize][j as usize];
+    }
+    // 左边和上边单元格的最小路径代价
+    let left = min_path_sum_dfs_mem(grid, mem, i - 1, j);
+    let up = min_path_sum_dfs_mem(grid, mem, i, j - 1);
+    // 记录并返回左上角到 (i, j) 的最小路径代价
+    mem[i as usize][j as usize] = std::cmp::min(left, up) + grid[i as usize][j as usize];
+    mem[i as usize][j as usize]
+}
+
+/* 最小路径和：动态规划 */
+fn min_path_sum_dp(grid: &Vec<Vec<i32>>) -> i32 {
+    let (n, m) = (grid.len(), grid[0].len());
+    // 初始化 dp 表
+    let mut dp = vec![vec![0; m]; n];
+    dp[0][0] = grid[0][0];
+    // 状态转移：首行
+    for j in 1..m {
+        dp[0][j] = dp[0][j - 1] + grid[0][j];
+    }
+    // 状态转移：首列
+    for i in 1..n {
+        dp[i][0] = dp[i - 1][0] + grid[i][0];
+    }
+    // 状态转移：其余行列
+    for i in 1..n {
+        for j in 1..m {
+            dp[i][j] = std::cmp::min(dp[i][j - 1], dp[i - 1][j]) + grid[i][j];
+        }
+    }
+    dp[n - 1][m - 1]
+}
+
+/* 最小路径和：状态压缩后的动态规划 */
+fn min_path_sum_dp_comp(grid: &Vec<Vec<i32>>) -> i32 {
+    let (n, m) = (grid.len(), grid[0].len());
+    // 初始化 dp 表
+    let mut dp = vec![0; m];
+    // 状态转移：首行
+    dp[0] = grid[0][0];
+    for j in 1..m {
+        dp[j] = dp[j - 1] + grid[0][j];
+    }
+    // 状态转移：其余行
+    for i in 1..n {
+        // 状态转移：首列
+        dp[0] = dp[0] + grid[i][0];
+        // 状态转移：其余列
+        for j in 1..m {
+            dp[j] = std::cmp::min(dp[j - 1], dp[j]) + grid[i][j];
+        }
+    }
+    dp[m - 1]
+}
+
+/* Driver Code */
+pub fn main() {
+    let grid = vec![
+        vec![ 1, 3, 1, 5 ],
+        vec![ 2, 2, 4, 2 ],
+        vec![ 5, 3, 2, 1 ],
+        vec![ 4, 3, 5, 2 ]];
+    let (n, m) = (grid.len(), grid[0].len());
+
+    // 暴力搜索
+    let res = min_path_sum_dfs(&grid, n as i32 - 1, m as i32 - 1);
+    println!("从左上角到右下角的最小路径和为 {res}");
+
+    // 记忆化搜索
+    let mut mem = vec![vec![0; m]; n];
+    for row in mem.iter_mut() {
+        row.fill(-1);
+    }
+    let res = min_path_sum_dfs_mem(&grid, &mut mem, n as i32 - 1, m as i32 - 1);
+    println!("从左上角到右下角的最小路径和为 {res}");
+
+    // 动态规划
+    let res = min_path_sum_dp(&grid);
+    println!("从左上角到右下角的最小路径和为 {res}");
+
+    // 状态压缩后的动态规划
+    let res = min_path_sum_dp_comp(&grid);
+    println!("从左上角到右下角的最小路径和为 {res}");
+}
diff --git a/codes/rust/chapter_dynamic_programming/unbounded_knapsack.rs b/codes/rust/chapter_dynamic_programming/unbounded_knapsack.rs
new file mode 100644
index 000000000..1f92cb056
--- /dev/null
+++ b/codes/rust/chapter_dynamic_programming/unbounded_knapsack.rs
@@ -0,0 +1,60 @@
+/*
+ * File: unbounded_knapsack.rs
+ * Created Time: 2023-07-09
+ * Author: sjinzh (sjinzh@gmail.com)
+ */
+
+/* 完全背包：动态规划 */
+fn unbounded_knapsack_dp(wgt: &[i32], val: &[i32], cap: usize) -> i32 {
+    let n = wgt.len();
+    // 初始化 dp 表
+    let mut dp = vec![vec![0; cap + 1]; n + 1];
+    // 状态转移
+    for i in 1..=n {
+        for c in 1..=cap {
+            if wgt[i - 1] > c as i32 {
+                // 若超过背包容量，则不选物品 i
+                dp[i][c] = dp[i - 1][c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[i][c] = std::cmp::max(dp[i - 1][c], dp[i][c - wgt[i - 1] as usize] + val[i - 1]);
+            }
+        }
+    }
+    return dp[n][cap];
+}
+
+/* 完全背包：状态压缩后的动态规划 */
+fn unbounded_knapsack_dp_comp(wgt: &[i32], val: &[i32], cap: usize) -> i32 {
+    let n = wgt.len();
+    // 初始化 dp 表
+    let mut dp = vec![0; cap + 1];
+    // 状态转移
+    for i in 1..=n {
+        for c in 1..=cap {
+            if wgt[i - 1] > c as i32 {
+                // 若超过背包容量，则不选物品 i
+                dp[c] = dp[c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[c] = std::cmp::max(dp[c], dp[c - wgt[i - 1] as usize] + val[i - 1]);
+            }
+        }
+    }
+    dp[cap]
+}
+
+/* Driver Code */
+pub fn main() {
+    let wgt = [ 1, 2, 3 ];
+    let val = [ 5, 11, 15 ];
+    let cap: usize = 4;
+
+    // 动态规划
+    let res = unbounded_knapsack_dp(&wgt, &val, cap);
+    println!("不超过背包容量的最大物品价值为 {res}");
+
+    // 状态压缩后的动态规划
+    let res = unbounded_knapsack_dp_comp(&wgt, &val, cap);
+    println!("不超过背包容量的最大物品价值为 {res}");
+}
diff --git a/codes/zig/build.zig b/codes/zig/build.zig
index 025107f6e..bff1a25f9 100644
--- a/codes/zig/build.zig
+++ b/codes/zig/build.zig
@@ -143,6 +143,54 @@ pub fn build(b: *std.Build) void {
         // Source File: "chapter_sorting/radix_sort.zig"
         // Run Command: zig build run_radix_sort -Doptimize=ReleaseFast
         .{ .name = "radix_sort", .path = "chapter_sorting/radix_sort.zig" },
+
+        // Source File: "chapter_dynamic_programming/climbing_stairs_backtrack.zig"
+        // Run Command: zig build run_climbing_stairs_backtrack -Doptimize=ReleaseFast
+        .{ .name = "climbing_stairs_backtrack", .path = "chapter_dynamic_programming/climbing_stairs_backtrack.zig" },
+
+        // Source File: "chapter_dynamic_programming/climbing_stairs_constraint_dp.zig"
+        // Run Command: zig build run_climbing_stairs_constraint_dp -Doptimize=ReleaseFast
+        .{ .name = "climbing_stairs_constraint_dp", .path = "chapter_dynamic_programming/climbing_stairs_constraint_dp.zig" },
+
+        // Source File: "chapter_dynamic_programming/climbing_stairs_dfs_mem.zig"
+        // Run Command: zig build run_climbing_stairs_dfs_mem -Doptimize=ReleaseFast
+        .{ .name = "climbing_stairs_dfs_mem", .path = "chapter_dynamic_programming/climbing_stairs_dfs_mem.zig" },
+
+        // Source File: "chapter_dynamic_programming/climbing_stairs_dfs.zig"
+        // Run Command: zig build run_climbing_stairs_dfs -Doptimize=ReleaseFast
+        .{ .name = "climbing_stairs_dfs", .path = "chapter_dynamic_programming/climbing_stairs_dfs.zig" },
+
+        // Source File: "chapter_dynamic_programming/climbing_stairs_dp.zig"
+        // Run Command: zig build run_climbing_stairs_dp -Doptimize=ReleaseFast
+        .{ .name = "climbing_stairs_dp", .path = "chapter_dynamic_programming/climbing_stairs_dp.zig" },
+
+        // Source File: "chapter_dynamic_programming/coin_change_ii.zig"
+        // Run Command: zig build run_coin_change_ii -Doptimize=ReleaseFast
+        .{ .name = "coin_change_ii", .path = "chapter_dynamic_programming/coin_change_ii.zig" },
+
+        // Source File: "chapter_dynamic_programming/coin_change.zig"
+        // Run Command: zig build run_coin_change -Doptimize=ReleaseFast
+        .{ .name = "coin_change", .path = "chapter_dynamic_programming/coin_change.zig" },
+
+        // Source File: "chapter_dynamic_programming/edit_distance.zig"
+        // Run Command: zig build run_edit_distance -Doptimize=ReleaseFast
+        .{ .name = "edit_distance", .path = "chapter_dynamic_programming/edit_distance.zig" },
+
+        // Source File: "chapter_dynamic_programming/knapsack.zig"
+        // Run Command: zig build run_knapsack -Doptimize=ReleaseFast
+        .{ .name = "knapsack", .path = "chapter_dynamic_programming/knapsack.zig" },
+
+        // Source File: "chapter_dynamic_programming/min_cost_climbing_stairs_dp.zig"
+        // Run Command: zig build run_min_cost_climbing_stairs_dp -Doptimize=ReleaseFast
+        .{ .name = "min_cost_climbing_stairs_dp", .path = "chapter_dynamic_programming/min_cost_climbing_stairs_dp.zig" },
+
+        // Source File: "chapter_dynamic_programming/min_path_sum.zig"
+        // Run Command: zig build run_min_path_sum -Doptimize=ReleaseFast
+        .{ .name = "min_path_sum", .path = "chapter_dynamic_programming/min_path_sum.zig" },
+
+        // Source File: "chapter_dynamic_programming/unbounded_knapsack.zig"
+        // Run Command: zig build run_unbounded_knapsack -Doptimize=ReleaseFast
+        .{ .name = "unbounded_knapsack", .path = "chapter_dynamic_programming/unbounded_knapsack.zig" },
     };
 
     inline for (group_name_path) |name_path| {
diff --git a/codes/zig/chapter_dynamic_programming/climbing_stairs_backtrack.zig b/codes/zig/chapter_dynamic_programming/climbing_stairs_backtrack.zig
new file mode 100644
index 000000000..0fc5ef107
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/climbing_stairs_backtrack.zig
@@ -0,0 +1,44 @@
+// File: climbing_stairs_backtrack.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 回溯
+fn backtrack(choices: []i32, state: i32, n: i32, res: std.ArrayList(i32)) void {
+    // 当爬到第 n 阶时，方案数量加 1
+    if (state == n) {
+        res.items[0] = res.items[0] + 1;
+    }
+    // 遍历所有选择
+    for (choices) |choice| {
+        // 剪枝：不允许越过第 n 阶
+        if (state + choice > n) {
+            break;
+        }
+        // 尝试：做出选择，更新状态
+        backtrack(choices, state + choice, n, res);
+        // 回退
+    }
+}
+
+// 爬楼梯：回溯
+fn climbing_stairs_backtrack(n: usize) !i32 {
+    var choices = [_]i32{ 1, 2 }; // 可选择向上爬 1 或 2 阶
+    var state: i32 = 0; // 从第 0 阶开始爬
+    var res = std.ArrayList(i32).init(std.heap.page_allocator);
+    defer res.deinit();
+    try res.append(0); // 使用 res[0] 记录方案数量
+    backtrack(&choices, state, @intCast(n), res);
+    return res.items[0];
+}
+
+// Driver Code
+pub fn main() !void {
+    var n: usize = 9;
+
+    var res = try climbing_stairs_backtrack(n);
+    std.debug.print("爬 {} 阶楼梯共有 {} 种方案\n", .{ n, res });
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/climbing_stairs_constraint_dp.zig b/codes/zig/chapter_dynamic_programming/climbing_stairs_constraint_dp.zig
new file mode 100644
index 000000000..cd4e43ee9
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/climbing_stairs_constraint_dp.zig
@@ -0,0 +1,35 @@
+// File: climbing_stairs_constraint_dp.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 带约束爬楼梯：动态规划
+fn climbing_stairs_constraint_dp(comptime n: usize) i32 {
+    if (n == 1 or n == 2) {
+        return @intCast(n);
+    }
+    // 初始化 dp 表，用于存储子问题的解
+    var dp = [_][3]i32{ [_]i32{ -1, -1, -1 } } ** (n + 1);
+    // 初始状态：预设最小子问题的解
+    dp[1][1] = 1;
+    dp[1][2] = 0;
+    dp[2][1] = 0;
+    dp[2][2] = 1;
+    // 状态转移：从较小子问题逐步求解较大子问题
+    for (3..n + 1) |i| {
+        dp[i][1] = dp[i - 1][2];
+        dp[i][2] = dp[i - 2][1] + dp[i - 2][2];
+    }
+    return dp[n][1] + dp[n][2];
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var n: usize = 9;
+
+    var res = climbing_stairs_constraint_dp(n);
+    std.debug.print("爬 {} 阶楼梯共有 {} 种方案\n", .{ n, res });
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/climbing_stairs_dfs.zig b/codes/zig/chapter_dynamic_programming/climbing_stairs_dfs.zig
new file mode 100644
index 000000000..2126a508f
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/climbing_stairs_dfs.zig
@@ -0,0 +1,31 @@
+// File: climbing_stairs_dfs.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 搜索
+fn dfs(i: usize) i32 {
+    // 已知 dp[1] 和 dp[2] ，返回之
+    if (i == 1 or i == 2) {
+        return @intCast(i);
+    }
+    // dp[i] = dp[i-1] + dp[i-2]
+    var count = dfs(i - 1) + dfs(i - 2);
+    return count;
+}
+
+// 爬楼梯：搜索
+fn climbing_stairs_dfs(comptime n: usize) i32 {
+    return dfs(n);
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var n: usize = 9;
+
+    var res = climbing_stairs_dfs(n);
+    std.debug.print("爬 {} 阶楼梯共有 {} 种方案\n", .{ n, res });
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/climbing_stairs_dfs_mem.zig b/codes/zig/chapter_dynamic_programming/climbing_stairs_dfs_mem.zig
new file mode 100644
index 000000000..e29d1a29d
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/climbing_stairs_dfs_mem.zig
@@ -0,0 +1,39 @@
+// File: climbing_stairs_dfs_mem.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 记忆化搜索
+fn dfs(i: usize, mem: []i32) i32 {
+    // 已知 dp[1] 和 dp[2] ，返回之
+    if (i == 1 or i == 2) {
+        return @intCast(i);
+    }
+    // 若存在记录 dp[i] ，则直接返回之
+    if (mem[i] != -1) {
+        return mem[i];
+    }
+    // dp[i] = dp[i-1] + dp[i-2]
+    var count = dfs(i - 1, mem) + dfs(i - 2, mem);
+    // 记录 dp[i]
+    mem[i] = count;
+    return count;
+}
+
+// 爬楼梯：记忆化搜索
+fn climbing_stairs_dfs_mem(comptime n: usize) i32 {
+    // mem[i] 记录爬到第 i 阶的方案总数，-1 代表无记录
+    var mem = [_]i32{ -1 } ** (n + 1);
+    return dfs(n, &mem);
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var n: usize = 9;
+
+    var res = climbing_stairs_dfs_mem(n);
+    std.debug.print("爬 {} 阶楼梯共有 {} 种方案\n", .{ n, res });
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/climbing_stairs_dp.zig b/codes/zig/chapter_dynamic_programming/climbing_stairs_dp.zig
new file mode 100644
index 000000000..49641273a
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/climbing_stairs_dp.zig
@@ -0,0 +1,51 @@
+// File: climbing_stairs_dp.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 爬楼梯：动态规划
+fn climbing_stairs_dp(comptime n: usize) i32 {
+    // 已知 dp[1] 和 dp[2] ，返回之
+    if (n == 1 or n == 2) {
+        return @intCast(n);
+    }
+    // 初始化 dp 表，用于存储子问题的解
+    var dp = [_]i32{-1} ** (n + 1);
+    // 初始状态：预设最小子问题的解
+    dp[1] = 1;
+    dp[2] = 2;
+    // 状态转移：从较小子问题逐步求解较大子问题
+    for (3..n + 1) |i| {
+        dp[i] = dp[i - 1] + dp[i - 2];
+    }
+    return dp[n];
+}
+
+// 爬楼梯：状态压缩后的动态规划
+fn climbing_stairs_dp_comp(comptime n: usize) i32 {
+    if (n == 1 or n == 2) {
+        return @intCast(n);
+    }
+    var a: i32 = 1;
+    var b: i32 = 2;
+    for (3..n + 1) |_| {
+        var tmp = b;
+        b = a + b;
+        a = tmp;
+    }
+    return b;
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var n: usize = 9;
+
+    var res = climbing_stairs_dp(n);
+    std.debug.print("爬 {} 阶楼梯共有 {} 种方案\n", .{ n, res });
+
+    res = climbing_stairs_dp_comp(n);
+    std.debug.print("爬 {} 阶楼梯共有 {} 种方案\n", .{ n, res });
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/coin_change.zig b/codes/zig/chapter_dynamic_programming/coin_change.zig
new file mode 100644
index 000000000..280237c6d
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/coin_change.zig
@@ -0,0 +1,77 @@
+// File: coin_change.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 零钱兑换：动态规划
+fn coin_change_dp(comptime coins: []i32, comptime amt: usize) i32 {
+    comptime var n = coins.len;
+    comptime var max = amt + 1;
+    // 初始化 dp 表
+    var dp = [_][amt + 1]i32{[_]i32{0} ** (amt + 1)} ** (n + 1);
+    // 状态转移：首行首列
+    for (1..amt + 1) |a| {
+        dp[0][a] = max;
+    }
+    // 状态转移：其余行列
+    for (1..n + 1) |i| {
+        for (1..amt + 1) |a| {
+            if (coins[i - 1] > @as(i32, @intCast(a))) {
+                // 若超过背包容量，则不选硬币 i
+                dp[i][a] = dp[i - 1][a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[i][a] = @min(dp[i - 1][a], dp[i][a - @as(usize, @intCast(coins[i - 1]))] + 1);
+            }
+        }
+    }
+    if (dp[n][amt] != max) {
+        return @intCast(dp[n][amt]);
+    } else {
+        return -1;
+    }
+}
+
+// 零钱兑换：状态压缩后的动态规划
+fn coin_change_dp_comp(comptime coins: []i32, comptime amt: usize) i32 {
+    comptime var n = coins.len;
+    comptime var max = amt + 1;
+    // 初始化 dp 表
+    var dp = [_]i32{0} ** (amt + 1);
+    @memset(&dp, max);
+    dp[0] = 0;
+    // 状态转移
+    for (1..n + 1) |i| {
+        for (1..amt + 1) |a| {
+            if (coins[i - 1] > @as(i32, @intCast(a))) {
+                // 若超过背包容量，则不选硬币 i
+                dp[a] = dp[a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[a] = @min(dp[a], dp[a - @as(usize, @intCast(coins[i - 1]))] + 1);
+            }
+        }
+    }
+    if (dp[amt] != max) {
+        return @intCast(dp[amt]);
+    } else {
+        return -1;
+    }
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var coins = [_]i32{ 1, 2, 5 };
+    comptime var amt: usize = 4;
+
+    // 动态规划
+    var res = coin_change_dp(&coins, amt);
+    std.debug.print("凑到目标金额所需的最少硬币数量为 {}\n", .{res});
+
+    // 状态压缩后的动态规划
+    res = coin_change_dp_comp(&coins, amt);
+    std.debug.print("凑到目标金额所需的最少硬币数量为 {}\n", .{res});
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/coin_change_ii.zig b/codes/zig/chapter_dynamic_programming/coin_change_ii.zig
new file mode 100644
index 000000000..f556db1f0
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/coin_change_ii.zig
@@ -0,0 +1,66 @@
+// File: coin_change_ii.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 零钱兑换 II：动态规划
+fn coin_change_ii_dp(comptime coins: []i32, comptime amt: usize) i32 {
+    comptime var n = coins.len;
+    // 初始化 dp 表
+    var dp = [_][amt + 1]i32{[_]i32{0} ** (amt + 1)} ** (n + 1);
+    // 初始化首列
+    for (0..n + 1) |i| {
+        dp[i][0] = 1;
+    }
+    // 状态转移
+    for (1..n + 1) |i| {
+        for (1..amt + 1) |a| {
+            if (coins[i - 1] > @as(i32, @intCast(a))) {
+                // 若超过背包容量，则不选硬币 i
+                dp[i][a] = dp[i - 1][a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[i][a] = dp[i - 1][a] + dp[i][a - @as(usize, @intCast(coins[i - 1]))];
+            }
+        }
+    }
+    return dp[n][amt];
+}
+
+// 零钱兑换 II：状态压缩后的动态规划
+fn coin_change_dp_ii_comp(comptime coins: []i32, comptime amt: usize) i32 {
+    comptime var n = coins.len;
+    // 初始化 dp 表
+    var dp = [_]i32{0} ** (amt + 1);
+    dp[0] = 1;
+    // 状态转移
+    for (1..n + 1) |i| {
+        for (1..amt + 1) |a| {
+            if (coins[i - 1] > @as(i32, @intCast(a))) {
+                // 若超过背包容量，则不选硬币 i
+                dp[a] = dp[a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[a] = dp[a] + dp[a - @as(usize, @intCast(coins[i - 1]))];
+            }
+        }
+    }
+    return dp[amt];
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var coins = [_]i32{ 1, 2, 5 };
+    comptime var amt: usize = 5;
+
+    // 动态规划
+    var res = coin_change_ii_dp(&coins, amt);
+    std.debug.print("凑出目标金额的硬币组合数量为 {}\n", .{res});
+
+    // 状态压缩后的动态规划
+    res = coin_change_dp_ii_comp(&coins, amt);
+    std.debug.print("凑出目标金额的硬币组合数量为 {}\n", .{res});
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/edit_distance.zig b/codes/zig/chapter_dynamic_programming/edit_distance.zig
new file mode 100644
index 000000000..0adbb95d8
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/edit_distance.zig
@@ -0,0 +1,146 @@
+// File: edit_distance.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 编辑距离：暴力搜索
+fn edit_distance_dfs(comptime s: []const u8, comptime t: []const u8, i: usize, j: usize) i32 {
+    // 若 s 和 t 都为空，则返回 0
+    if (i == 0 and j == 0) {
+        return 0;
+    }
+    // 若 s 为空，则返回 t 长度
+    if (i == 0) {
+        return @intCast(j);
+    }
+    // 若 t 为空，则返回 s 长度
+    if (j == 0) {
+        return @intCast(i);
+    }
+    // 若两字符相等，则直接跳过此两字符
+    if (s[i - 1] == t[j - 1]) {
+        return edit_distance_dfs(s, t, i - 1, j - 1);
+    }
+    // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+    var insert = edit_distance_dfs(s, t, i, j - 1);
+    var delete = edit_distance_dfs(s, t, i - 1, j);
+    var replace = edit_distance_dfs(s, t, i - 1, j - 1);
+    // 返回最少编辑步数
+    return @min(@min(insert, delete), replace) + 1;
+}
+
+// 编辑距离：记忆化搜索
+fn edit_distance_dfs_mem(comptime s: []const u8, comptime t: []const u8, mem: anytype, i: usize, j: usize) i32 {
+    // 若 s 和 t 都为空，则返回 0
+    if (i == 0 and j == 0) {
+        return 0;
+    }
+    // 若 s 为空，则返回 t 长度
+    if (i == 0) {
+        return @intCast(j);
+    }
+    // 若 t 为空，则返回 s 长度
+    if (j == 0) {
+        return @intCast(i);
+    }
+    // 若已有记录，则直接返回之
+    if (mem[i][j] != -1) {
+        return mem[i][j];
+    }
+    // 若两字符相等，则直接跳过此两字符
+    if (s[i - 1] == t[j - 1]) {
+        return edit_distance_dfs_mem(s, t, mem, i - 1, j - 1);
+    }
+    // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+    var insert = edit_distance_dfs_mem(s, t, mem, i, j - 1);
+    var delete = edit_distance_dfs_mem(s, t, mem, i - 1, j);
+    var replace = edit_distance_dfs_mem(s, t, mem, i - 1, j - 1);
+    // 记录并返回最少编辑步数
+    mem[i][j] = @min(@min(insert, delete), replace) + 1;
+    return mem[i][j];
+}
+
+// 编辑距离：动态规划
+fn edit_distance_dp(comptime s: []const u8, comptime t: []const u8) i32 {
+    comptime var n = s.len;
+    comptime var m = t.len;
+    var dp = [_][m + 1]i32{[_]i32{0} ** (m + 1)} ** (n + 1);
+    // 状态转移：首行首列
+    for (1..n + 1) |i| {
+        dp[i][0] = @intCast(i);
+    }
+    for (1..m + 1) |j| {
+        dp[0][j] = @intCast(j);
+    }
+    // 状态转移：其余行列
+    for (1..n + 1) |i| {
+        for (1..m + 1) |j| {
+            if (s[i - 1] == t[j - 1]) {
+                // 若两字符相等，则直接跳过此两字符
+                dp[i][j] = dp[i - 1][j - 1];
+            } else {
+                // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+                dp[i][j] = @min(@min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
+            }
+        }
+    }
+    return dp[n][m];
+}
+
+// 编辑距离：状态压缩后的动态规划
+fn edit_distance_dp_comp(comptime s: []const u8, comptime t: []const u8) i32 {
+    comptime var n = s.len;
+    comptime var m = t.len;
+    var dp = [_]i32{0} ** (m + 1);
+    // 状态转移：首行
+    for (1..m + 1) |j| {
+        dp[j] = @intCast(j);
+    }
+    // 状态转移：其余行
+    for (1..n + 1) |i| {
+        // 状态转移：首列
+        var leftup = dp[0]; // 暂存 dp[i-1, j-1]
+        dp[0] = @intCast(i);
+        // 状态转移：其余列
+        for (1..m + 1) |j| {
+            var temp = dp[j];
+            if (s[i - 1] == t[j - 1]) {
+                // 若两字符相等，则直接跳过此两字符
+                dp[j] = leftup;
+            } else {
+                // 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
+                dp[j] = @min(@min(dp[j - 1], dp[j]), leftup) + 1;
+            }
+            leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
+        }
+    }
+    return dp[m];
+}
+
+// Driver Code
+pub fn main() !void {
+    const s = "bag";
+    const t = "pack";
+    comptime var n = s.len;
+    comptime var m = t.len;
+
+    // 暴力搜索
+    var res = edit_distance_dfs(s, t, n, m);
+    std.debug.print("将 {s} 更改为 {s} 最少需要编辑 {} 步\n", .{ s, t, res });
+
+    // 记忆搜索
+    var mem = [_][m + 1]i32{[_]i32{-1} ** (m + 1)} ** (n + 1);
+    res = edit_distance_dfs_mem(s, t, @constCast(&mem), n, m);
+    std.debug.print("将 {s} 更改为 {s} 最少需要编辑 {} 步\n", .{ s, t, res });
+
+    // 动态规划
+    res = edit_distance_dp(s, t);
+    std.debug.print("将 {s} 更改为 {s} 最少需要编辑 {} 步\n", .{ s, t, res });
+
+    // 状态压缩后的动态规划
+    res = edit_distance_dp_comp(s, t);
+    std.debug.print("将 {s} 更改为 {s} 最少需要编辑 {} 步\n", .{ s, t, res });
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/knapsack.zig b/codes/zig/chapter_dynamic_programming/knapsack.zig
new file mode 100644
index 000000000..e591e4a47
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/knapsack.zig
@@ -0,0 +1,110 @@
+// File: knapsack.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 0-1 背包：暴力搜索
+fn knapsack_dfs(wgt: []i32, val: []i32, i: usize, c: usize) i32 {
+    // 若已选完所有物品或背包无容量，则返回价值 0
+    if (i == 0 or c == 0) {
+        return 0;
+    }
+    // 若超过背包容量，则只能不放入背包
+    if (wgt[i - 1] > c) {
+        return knapsack_dfs(wgt, val, i - 1, c);
+    }
+    // 计算不放入和放入物品 i 的最大价值
+    var no = knapsack_dfs(wgt, val, i - 1, c);
+    var yes = knapsack_dfs(wgt, val, i - 1, c - @as(usize, @intCast(wgt[i - 1]))) + val[i - 1];
+    // 返回两种方案中价值更大的那一个
+    return @max(no, yes);
+}
+
+// 0-1 背包：记忆化搜索
+fn knapsack_dfs_mem(wgt: []i32, val: []i32, mem: anytype, i: usize, c: usize) i32 {
+    // 若已选完所有物品或背包无容量，则返回价值 0
+    if (i == 0 or c == 0) {
+        return 0;
+    }
+    // 若已有记录，则直接返回
+    if (mem[i][c] != -1) {
+        return mem[i][c];
+    }
+    // 若超过背包容量，则只能不放入背包
+    if (wgt[i - 1] > c) {
+        return knapsack_dfs_mem(wgt, val, mem, i - 1, c);
+    }
+    // 计算不放入和放入物品 i 的最大价值
+    var no = knapsack_dfs_mem(wgt, val, mem, i - 1, c);
+    var yes = knapsack_dfs_mem(wgt, val, mem, i - 1, c - @as(usize, @intCast(wgt[i - 1]))) + val[i - 1];
+    // 记录并返回两种方案中价值更大的那一个
+    mem[i][c] = @max(no, yes);
+    return mem[i][c];
+}
+
+// 0-1 背包：动态规划
+fn knapsack_dp(comptime wgt: []i32, val: []i32, comptime cap: usize) i32 {
+    comptime var n = wgt.len;
+    // 初始化 dp 表
+    var dp = [_][cap + 1]i32{[_]i32{0} ** (cap + 1)} ** (n + 1);
+    // 状态转移
+    for (1..n + 1) |i| {
+        for (1..cap + 1) |c| {
+            if (wgt[i - 1] > c) {
+                // 若超过背包容量，则不选物品 i
+                dp[i][c] = dp[i - 1][c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[i][c] = @max(dp[i - 1][c], dp[i - 1][c - @as(usize, @intCast(wgt[i - 1]))] + val[i - 1]);
+            }
+        }
+    }
+    return dp[n][cap];
+}
+
+// 0-1 背包：状态压缩后的动态规划
+fn knapsack_dp_comp(wgt: []i32, val: []i32, comptime cap: usize) i32 {
+    var n = wgt.len;
+    // 初始化 dp 表
+    var dp = [_]i32{0} ** (cap + 1);
+    // 状态转移
+    for (1..n + 1) |i| {
+        // 倒序遍历
+        var c = cap;
+        while (c > 0) : (c -= 1) {
+            if (wgt[i - 1] < c) {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[c] = @max(dp[c], dp[c - @as(usize, @intCast(wgt[i - 1]))] + val[i - 1]);
+            }
+        }
+    }
+    return dp[cap];
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var wgt = [_]i32{ 10, 20, 30, 40, 50 };
+    comptime var val = [_]i32{ 50, 120, 150, 210, 240 };
+    comptime var cap = 50;
+    comptime var n = wgt.len;
+
+    // 暴力搜索
+    var res = knapsack_dfs(&wgt, &val, n, cap);
+    std.debug.print("不超过背包容量的最大物品价值为 {}\n", .{res});
+
+    // 记忆搜索
+    var mem = [_][cap + 1]i32{[_]i32{-1} ** (cap + 1)} ** (n + 1);
+    res = knapsack_dfs_mem(&wgt, &val, @constCast(&mem), n, cap);
+    std.debug.print("不超过背包容量的最大物品价值为 {}\n", .{res});
+
+    // 动态规划
+    res = knapsack_dp(&wgt, &val, cap);
+    std.debug.print("不超过背包容量的最大物品价值为 {}\n", .{res});
+
+    // 状态压缩后的动态规划
+    res = knapsack_dp_comp(&wgt, &val, cap);
+    std.debug.print("不超过背包容量的最大物品价值为 {}\n", .{res});
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/min_cost_climbing_stairs_dp.zig b/codes/zig/chapter_dynamic_programming/min_cost_climbing_stairs_dp.zig
new file mode 100644
index 000000000..29bdb746e
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/min_cost_climbing_stairs_dp.zig
@@ -0,0 +1,54 @@
+// File: min_cost_climbing_stairs_dp.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 爬楼梯最小代价：动态规划
+fn min_cost_climbing_stairs_dp(comptime cost: []i32) i32 {
+    comptime var n = cost.len - 1;
+    if (n == 1 or n == 2) {
+        return cost[n];
+    }
+    // 初始化 dp 表，用于存储子问题的解
+    var dp = [_]i32{-1} ** (n + 1);
+    // 初始状态：预设最小子问题的解
+    dp[1] = cost[1];
+    dp[2] = cost[2];
+    // 状态转移：从较小子问题逐步求解较大子问题
+    for (3..n + 1) |i| {
+        dp[i] = @min(dp[i - 1], dp[i - 2]) + cost[i];
+    }
+    return dp[n];
+}
+
+// 爬楼梯最小代价：状态压缩后的动态规划
+fn min_cost_climbing_stairs_dp_comp(cost: []i32) i32 {
+    var n = cost.len - 1;
+    if (n == 1 or n == 2) {
+        return cost[n];
+    }
+    var a = cost[1];
+    var b = cost[2];
+    // 状态转移：从较小子问题逐步求解较大子问题
+    for (3..n + 1) |i| {
+        var tmp = b;
+        b = @min(a, tmp) + cost[i];
+        a = tmp;
+    }
+    return b;
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var cost = [_]i32{ 0, 1, 10, 1, 1, 1, 10, 1, 1, 10, 1 };
+    std.debug.print("输入楼梯的代价列表为 {any}\n", .{cost});
+
+    var res = min_cost_climbing_stairs_dp(&cost);
+    std.debug.print("输入楼梯的代价列表为 {}\n", .{res});
+
+    res = min_cost_climbing_stairs_dp_comp(&cost);
+    std.debug.print("输入楼梯的代价列表为 {}\n", .{res});
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/min_path_sum.zig b/codes/zig/chapter_dynamic_programming/min_path_sum.zig
new file mode 100644
index 000000000..4efb35fde
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/min_path_sum.zig
@@ -0,0 +1,122 @@
+// File: min_path_sum.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 最小路径和：暴力搜索
+fn min_path_sum_dfs(grid: anytype, i: i32, j: i32) i32 {
+    // 若为左上角单元格，则终止搜索
+    if (i == 0 and j == 0) {
+        return grid[0][0];
+    }
+    // 若行列索引越界，则返回 +∞ 代价
+    if (i < 0 or j < 0) {
+        return std.math.maxInt(i32);
+    }
+    // 计算从左上角到 (i-1, j) 和 (i, j-1) 的最小路径代价
+    var left = min_path_sum_dfs(grid, i - 1, j);
+    var up = min_path_sum_dfs(grid, i, j - 1);
+    // 返回从左上角到 (i, j) 的最小路径代价
+    return @min(left, up) + grid[@as(usize, @intCast(i))][@as(usize, @intCast(j))];
+}
+
+// 最小路径和：记忆化搜索
+fn min_path_sum_dfs_mem(grid: anytype, mem: anytype, i: i32, j: i32) i32 {
+    // 若为左上角单元格，则终止搜索
+    if (i == 0 and j == 0) {
+        return grid[0][0];
+    }
+    // 若行列索引越界，则返回 +∞ 代价
+    if (i < 0 or j < 0) {
+        return std.math.maxInt(i32);
+    }
+    // 若已有记录，则直接返回
+    if (mem[@as(usize, @intCast(i))][@as(usize, @intCast(j))] != -1) {
+        return mem[@as(usize, @intCast(i))][@as(usize, @intCast(j))];
+    }
+    // 计算从左上角到 (i-1, j) 和 (i, j-1) 的最小路径代价
+    var left = min_path_sum_dfs_mem(grid, mem, i - 1, j);
+    var up = min_path_sum_dfs_mem(grid, mem, i, j - 1);
+    // 返回从左上角到 (i, j) 的最小路径代价
+    // 记录并返回左上角到 (i, j) 的最小路径代价
+    mem[@as(usize, @intCast(i))][@as(usize, @intCast(j))] = @min(left, up) + grid[@as(usize, @intCast(i))][@as(usize, @intCast(j))];
+    return mem[@as(usize, @intCast(i))][@as(usize, @intCast(j))];
+}
+
+// 最小路径和：动态规划
+fn min_path_sum_dp(comptime grid: anytype) i32 {
+    comptime var n = grid.len;
+    comptime var m = grid[0].len;
+    // 初始化 dp 表
+    var dp = [_][m]i32{[_]i32{0} ** m} ** n;
+    dp[0][0] = grid[0][0];
+    // 状态转移：首行
+    for (1..m) |j| {
+        dp[0][j] = dp[0][j - 1] + grid[0][j];
+    }
+    // 状态转移：首列
+    for (1..n) |i| {
+        dp[i][0] = dp[i - 1][0] + grid[i][0];
+    }
+    // 状态转移：其余行列
+    for (1..n) |i| {
+        for (1..m) |j| {
+            dp[i][j] = @min(dp[i][j - 1], dp[i - 1][j]) + grid[i][j];
+        }
+    }
+    return dp[n - 1][m - 1];
+}
+
+// 最小路径和：状态压缩后的动态规划
+fn min_path_sum_dp_comp(comptime grid: anytype) i32 {
+    comptime var n = grid.len;
+    comptime var m = grid[0].len;
+    // 初始化 dp 表
+    var dp = [_]i32{0} ** m;
+    // 状态转移：首行
+    dp[0] = grid[0][0];
+    for (1..m) |j| {
+        dp[j] = dp[j - 1] + grid[0][j];
+    }
+    // 状态转移：其余行
+    for (1..n) |i| {
+        // 状态转移：首列
+        dp[0] = dp[0] + grid[i][0];
+        for (1..m) |j| {
+            dp[j] = @min(dp[j - 1], dp[j]) + grid[i][j];
+        }
+    }
+    return dp[m - 1];
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var grid = [_][4]i32{
+        [_]i32{ 1, 3, 1, 5 },
+        [_]i32{ 2, 2, 4, 2 },
+        [_]i32{ 5, 3, 2, 1 },
+        [_]i32{ 4, 3, 5, 2 },
+    };
+    comptime var n = grid.len;
+    comptime var m = grid[0].len;
+
+    // 暴力搜索
+    var res = min_path_sum_dfs(&grid, n - 1, m - 1);
+    std.debug.print("从左上角到右下角的最小路径和为 {}\n", .{res});
+
+    // 记忆化搜索
+    var mem = [_][m]i32{[_]i32{-1} ** m} ** n;
+    res = min_path_sum_dfs_mem(&grid, &mem, n - 1, m - 1);
+    std.debug.print("从左上角到右下角的最小路径和为 {}\n", .{res});
+
+    // 动态规划
+    res = min_path_sum_dp(&grid);
+    std.debug.print("从左上角到右下角的最小路径和为 {}\n", .{res});
+
+    // 状态压缩后的动态规划
+    res = min_path_sum_dp_comp(&grid);
+    std.debug.print("从左上角到右下角的最小路径和为 {}\n", .{res});
+
+    _ = try std.io.getStdIn().reader().readByte();
+}
diff --git a/codes/zig/chapter_dynamic_programming/unbounded_knapsack.zig b/codes/zig/chapter_dynamic_programming/unbounded_knapsack.zig
new file mode 100644
index 000000000..855d25048
--- /dev/null
+++ b/codes/zig/chapter_dynamic_programming/unbounded_knapsack.zig
@@ -0,0 +1,62 @@
+// File: unbounded_knapsack.zig
+// Created Time: 2023-07-15
+// Author: sjinzh (sjinzh@gmail.com)
+
+const std = @import("std");
+
+// 完全背包：动态规划
+fn unbounded_knapsack_dp(comptime wgt: []i32, val: []i32, comptime cap: usize) i32 {
+    comptime var n = wgt.len;
+    // 初始化 dp 表
+    var dp = [_][cap + 1]i32{[_]i32{0} ** (cap + 1)} ** (n + 1);
+    // 状态转移
+    for (1..n + 1) |i| {
+        for (1..cap + 1) |c| {
+            if (wgt[i - 1] > c) {
+                // 若超过背包容量，则不选物品 i
+                dp[i][c] = dp[i - 1][c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[i][c] = @max(dp[i - 1][c], dp[i][c - @as(usize, @intCast(wgt[i - 1]))] + val[i - 1]);
+            }
+        }
+    }
+    return dp[n][cap];
+}
+
+// 完全背包：状态压缩后的动态规划
+fn unbounded_knapsack_dp_comp(comptime wgt: []i32, val: []i32, comptime cap: usize) i32 {
+    comptime var n = wgt.len;
+    // 初始化 dp 表
+    var dp = [_]i32{0} ** (cap + 1);
+    // 状态转移
+    for (1..n + 1) |i| {
+        for (1..cap + 1) |c| {
+            if (wgt[i - 1] > c) {
+                // 若超过背包容量，则不选物品 i
+                dp[c] = dp[c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[c] = @max(dp[c], dp[c - @as(usize, @intCast(wgt[i - 1]))] + val[i - 1]);
+            }
+        }
+    }
+    return dp[cap];
+}
+
+// Driver Code
+pub fn main() !void {
+    comptime var wgt = [_]i32{ 1, 2, 3 };
+    comptime var val = [_]i32{ 5, 11, 15 };
+    comptime var cap = 4;
+
+    // 动态规划
+    var res = unbounded_knapsack_dp(&wgt, &val, cap);
+    std.debug.print("不超过背包容量的最大物品价值为 {}\n", .{res});
+
+    // 状态压缩后的动态规划
+    res = unbounded_knapsack_dp_comp(&wgt, &val, cap);
+    std.debug.print("不超过背包容量的最大物品价值为 {}\n", .{res});
+
+    _ = try std.io.getStdIn().reader().readByte();
+}