Before starting the topic let me introduce myself. I am a Mobile Developer currently working in Warsaw and spending my free time for interview preparations. I started to prepare for interviews two years ago. At that time I should say I could not solve the two sum problem. Easy problems seemed to me like hard ones so most of the time I had to look at editorials and discuss section. Currently, I have solved ~800 problems and time to time participate in contests. I usually solve 3 problems in a contest and sometimes 4 problems. Ok, lets come back to the topic.

Recently I have concentrated my attention on Dynamic Programming cause its one of the hardest topics in an interview prep. After solving ~140 problems in DP I have noticed that there are few patterns that can be found in different problems. So I did a research on that and find the following topics. I will not give complete ways how to solve problems but these patterns may be helpful in solving DP.

Patterns

Minimum (Maximum) Path to Reach a Target-Path-to-Reach-a-Target)
Distinct Ways
Merging Intervals
DP on Strings
Decision Making

Minimum (Maximum) Path to Reach a Target

Generate problem statement for this pattern

Statement

Given a target find minimum (maximum) cost / path / sum to reach the target.

Approach

Choose minimum (maximum) path among all possible paths before the current state, then add value for the current state.

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routes[i] = min(routes[i-1], routes[i-2], ... , routes[i-k]) + cost[i]

Generate optimal solutions for all values in the target and return the value for the target.

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for (int i = 1; i <= target; ++i) {
   for (int j = 0; j < ways.size(); ++j) {
       if (ways[j] <= i) {
           dp[i] = min(dp[i], dp[i - ways[j]]) + cost / path / sum;
       }
   }
}

return dp[target]

Similar Problems

746. Min Cost Climbing Stairs Easy

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for (int i = 2; i <= n; ++i) {
   dp[i] = min(dp[i-1], dp[i-2]) + (i == n ? 0 : cost[i]);
}

return dp[n]

64. Minimum Path Sum Medium

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for (int i = 1; i < n; ++i) {
   for (int j = 1; j < m; ++j) {
       grid[i][j] = min(grid[i-1][j], grid[i][j-1]) + grid[i][j];
   }
}

return grid[n-1][m-1]

322. Coin Change Medium

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for (int j = 1; j <= amount; ++j) {
   for (int i = 0; i < coins.size(); ++i) {
       if (coins[i] <= j) {
           dp[j] = min(dp[j], dp[j - coins[i]] + 1);
       }
   }
}

931. Minimum Falling Path Sum Medium

983. Minimum Cost For Tickets Medium

650. 2 Keys Keyboard Medium

279. Perfect Squares Medium

1049. Last Stone Weight II Medium

120. Triangle Medium

474. Ones and Zeroes Medium

221. Maximal Square Medium

322. Coin Change Medium

1240. Tiling a Rectangle with the Fewest Squares Hard

174. Dungeon Game Hard

871. Minimum Number of Refueling Stops Hard

Distinct Ways

Generate problem statement for this pattern

Statement

Given a target find a number of distinct ways to reach the target.

Approach

Sum all possible ways to reach the current state.

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routes[i] = routes[i-1] + routes[i-2], ... , + routes[i-k]

Generate sum for all values in the target and return the value for the target.

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for (int i = 1; i <= target; ++i) {
   for (int j = 0; j < ways.size(); ++j) {
       if (ways[j] <= i) {
           dp[i] += dp[i - ways[j]];
       }
   }
}

return dp[target]

Similar Problems

70. Climbing Stairs easy

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for (int stair = 2; stair <= n; ++stair) {
   for (int step = 1; step <= 2; ++step) {
       dp[stair] += dp[stair-step];
   }
}

62. Unique Paths Medium

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for (int i = 1; i < m; ++i) {
   for (int j = 1; j < n; ++j) {
       dp[i][j] = dp[i][j-1] + dp[i-1][j];
   }
}

1155. Number of Dice Rolls With Target Sum Medium

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for (int rep = 1; rep <= d; ++rep) {
   vector<int> new_ways(target+1);
   for (int already = 0; already <= target; ++already) {
       for (int pipe = 1; pipe <= f; ++pipe) {
           if (already - pipe >= 0) {
               new_ways[already] += ways[already - pipe];
               new_ways[already] %= mod;
           }
       }
   }
   ways = new_ways;
}

Note

Some questions point out the number of repetitions, in that case, add one more loop to simulate every repetition.

688. Knight Probability in Chessboard Medium

494. Target Sum Medium

377. Combination Sum IV Medium

935. Knight Dialer Medium

1223. Dice Roll Simulation Medium

416. Partition Equal Subset Sum Medium

808. Soup Servings Medium

790. Domino and Tromino Tiling Medium

801. Minimum Swaps To Make Sequences Increasing

673. Number of Longest Increasing Subsequence Medium

63. Unique Paths II Medium

576. Out of Boundary Paths Medium

1269. Number of Ways to Stay in the Same Place After Some Steps Hard

1220. Count Vowels Permutation Hard

Merging Intervals

Generate problem statement for this pattern

Statement

Given a set of numbers find an optimal solution for a problem considering the current number and the best you can get from the left and right sides.

Approach

Find all optimal solutions for every interval and return the best possible answer.

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// from i to j
dp[i][j] = dp[i][k] + result[k] + dp[k+1][j]

Get the best from the left and right sides and add a solution for the current position.

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for(int l = 1; l<n; l++) {
   for(int i = 0; i<n-l; i++) {
       int j = i+l;
       for(int k = i; k<j; k++) {
           dp[i][j] = max(dp[i][j], dp[i][k] + result[k] + dp[k+1][j]);
       }
   }
}

return dp[0][n-1]

Similar Problems

1130. Minimum Cost Tree From Leaf Values Medium

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for (int l = 1; l < n; ++l) {
   for (int i = 0; i < n - l; ++i) {
       int j = i + l;
       dp[i][j] = INT_MAX;
       for (int k = i; k < j; ++k) {
           dp[i][j] = min(dp[i][j], dp[i][k] + dp[k+1][j] + maxs[i][k] * maxs[k+1][j]);
       }
   }
}

96. Unique Binary Search Trees Medium

1039. Minimum Score Triangulation of Polygon Medium

546. Remove Boxes Medium

1000. Minimum Cost to Merge Stones Medium

312. Burst Balloons Hard

375. Guess Number Higher or Lower II Medium

DP on Strings

General problem statement for this pattern can vary but most of the time you are given two strings where lengths of those strings are not big

Statement

Given two strings s1 and s2, return some result.

Approach

Most of the problems on this pattern requires a solution that can be accepted in O(n^2) complexity.

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// i - indexing string s1
// j - indexing string s2
for (int i = 1; i <= n; ++i) {
   for (int j = 1; j <= m; ++j) {
       if (s1[i-1] == s2[j-1]) {
           dp[i][j] = /*code*/;
       } else {
           dp[i][j] = /*code*/;
       }
   }
}

If you are given one string s the approach may little vary

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for (int l = 1; l < n; ++l) {
   for (int i = 0; i < n-l; ++i) {
       int j = i + l;
       if (s[i] == s[j]) {
           dp[i][j] = /*code*/;
       } else {
           dp[i][j] = /*code*/;
       }
   }
}

1143. Longest Common Subsequence Medium

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for (int i = 1; i <= n; ++i) {
   for (int j = 1; j <= m; ++j) {
       if (text1[i-1] == text2[j-1]) {
           dp[i][j] = dp[i-1][j-1] + 1;
       } else {
           dp[i][j] = max(dp[i-1][j], dp[i][j-1]);
       }
   }
}

647. Palindromic Substrings Medium

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for (int l = 1; l < n; ++l) {
   for (int i = 0; i < n-l; ++i) {
       int j = i + l;
       if (s[i] == s[j] && dp[i+1][j-1] == j-i-1) {
           dp[i][j] = dp[i+1][j-1] + 2;
       } else {
           dp[i][j] = 0;
       }
   }
}

516. Longest Palindromic Subsequence Medium

1092. Shortest Common Supersequence Medium

72. Edit Distance Hard

115. Distinct Subsequences Hard

712. Minimum ASCII Delete Sum for Two Strings Medium

5. Longest Palindromic Substring Medium

Decision Making

The general problem statement for this pattern is forgiven situation decide whether to use or not to use the current state. So, the problem requires you to make a decision at a current state.

Statement

Given a set of values find an answer with an option to choose or ignore the current value.

Approach

If you decide to choose the current value use the previous result where the value was ignored; vice-versa, if you decide to ignore the current value use previous result where value was used.

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// i - indexing a set of values
// j - options to ignore j values
for (int i = 1; i < n; ++i) {
   for (int j = 1; j <= k; ++j) {
       dp[i][j] = max({dp[i][j], dp[i-1][j] + arr[i], dp[i-1][j-1]});
       dp[i][j-1] = max({dp[i][j-1], dp[i-1][j-1] + arr[i], arr[i]});
   }
}

198. House Robber Easy

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for (int i = 1; i < n; ++i) {
   dp[i][1] = max(dp[i-1][0] + nums[i], dp[i-1][1]);
   dp[i][0] = dp[i-1][1];
}

121. Best Time to Buy and Sell Stock Easy

714. Best Time to Buy and Sell Stock with Transaction Fee Medium

309. Best Time to Buy and Sell Stock with Cooldown Medium

123. Best Time to Buy and Sell Stock III Hard

188. Best Time to Buy and Sell Stock IV Hard

I hope these tips will be helpful 😊

https://leetcode.com/discuss/general-discussion/458695/dynamic-programming-patterns