answer:To answer this, I need to find a way to prepare for the upcoming URI Online Judge contest by creating a curated list of problems that focus on dynamic programming. Let me think about this carefully. This means I need to identify a set of problems that will help me build my skills in dynamic programming, starting from the basics and progressing to more complex problems. I should prioritize problems that have appeared in recent contests or are considered classics in the dynamic programming category. Wait, let me break this down first - what does it really mean to prepare for a contest like this? It means I need to have a solid understanding of dynamic programming concepts, as well as practice solving problems that require these concepts. I should also consider the difficulty level of each problem and create a progression that will help me build my skills effectively. Let me think about the types of problems that would be useful for this. I'll need problems that cover a range of topics, such as recursive relations, memoization, and optimization techniques. I'll also need problems with varying levels of difficulty, from basic to advanced. Okay, let me start by identifying some classic dynamic programming problems. One of the most basic problems is the Fibonacci sequence. This problem requires me to print the first N terms of the Fibonacci sequence, which can be solved using a simple iterative approach. This is a great problem to start with because it introduces the basic concept of dynamic programming. Next, I'll consider the Knapsack problem. This problem requires me to determine the maximum value that can be obtained by selecting a subset of items with a total weight not exceeding a given limit. This problem can be solved using a 2D DP table, where dp[i][w] represents the maximum value that can be obtained with the first i items and a weight limit of w. Another important problem is the Longest Increasing Subsequence (LIS) problem. This problem requires me to find the length of the longest increasing subsequence in an array. This problem can be solved using a DP array, where dp[i] represents the length of the longest increasing subsequence ending at index i. I'll also consider the Coin Change problem, which requires me to determine the minimum number of coins needed to make a target amount. This problem can be solved using a DP array, where dp[i] represents the minimum number of coins needed to make the amount i. In addition to these problems, I'll also consider the Matrix Chain Multiplication problem, the Edit Distance problem, and the Rod Cutting problem. These problems cover a range of topics and have varying levels of difficulty, making them perfect for a curated list. Now, let me think about the recommended difficulty progression. I'll start with the Fibonacci sequence, which is a basic problem that introduces the concept of dynamic programming. Next, I'll move on to the Longest Increasing Subsequence problem, which is a bit more challenging but still relatively straightforward. Then, I'll consider the Coin Change problem, which requires a bit more thinking but is still a relatively basic problem. After that, I'll move on to the Knapsack problem, which is a bit more challenging but is a classic dynamic programming problem. Next, I'll consider the Matrix Chain Multiplication problem, which requires a bit more thinking and is a bit more challenging. Then, I'll move on to the Edit Distance problem, which is a bit more complex but is still a relatively manageable problem. Finally, I'll end with the Rod Cutting problem, which is a bit more challenging but is a great problem to practice optimization techniques. Here's the curated list of problems, along with descriptions, input/output formats, constraints, and tips for each problem: # 1. **Fibonacci Sequence (URI 1151)** - **Description:** Print the first N terms of the Fibonacci sequence. - **Input:** An integer N (1 ≤ N ≤ 45). - **Output:** The first N terms of the Fibonacci sequence. - **Constraints:** 1 ≤ N ≤ 45. - **Tips:** Use a simple iterative approach to build the Fibonacci sequence. This is a classic problem to understand the basics of dynamic programming. # 2. **Longest Increasing Subsequence (URI 1149)** - **Description:** Find the length of the longest increasing subsequence in an array. - **Input:** An integer N (1 ≤ N ≤ 1000), followed by N integers. - **Output:** The length of the longest increasing subsequence. - **Constraints:** 1 ≤ N ≤ 1000. - **Tips:** Use a DP array where dp[i] represents the length of the longest increasing subsequence ending at index i. # 3. **Coin Change Problem (URI 1030)** - **Description:** Given a set of coin denominations and a target amount, determine the minimum number of coins needed to make the target amount. - **Input:** An integer N (number of coin denominations), followed by N integers (coin denominations), and an integer M (target amount). - **Output:** The minimum number of coins needed. - **Constraints:** 1 ≤ N ≤ 100, 1 ≤ M ≤ 10000. - **Tips:** Use a DP array where dp[i] represents the minimum number of coins needed to make the amount i. # 4. **Knapsack Problem (URI 1028)** - **Description:** Given a set of items, each with a weight and a value, determine the maximum value that can be obtained by selecting a subset of items with a total weight not exceeding a given limit. - **Input:** Two integers N (number of items) and W (weight limit), followed by N pairs of integers (weight and value of each item). - **Output:** The maximum value that can be obtained. - **Constraints:** 1 ≤ N ≤ 100, 1 ≤ W ≤ 1000. - **Tips:** Use a 2D DP table where dp[i][w] represents the maximum value that can be obtained with the first i items and a weight limit of w. # 5. **Matrix Chain Multiplication (URI 1029)** - **Description:** Given the dimensions of a sequence of matrices, determine the minimum number of scalar multiplications needed to multiply the matrices. - **Input:** An integer N (number of matrices), followed by N+1 integers (dimensions of the matrices). - **Output:** The minimum number of scalar multiplications. - **Constraints:** 1 ≤ N ≤ 100. - **Tips:** Use a 2D DP table where dp[i][j] represents the minimum number of scalar multiplications needed to multiply matrices from i to j. # 6. **Edit Distance (URI 1034)** - **Description:** Given two strings, determine the minimum number of operations (insertions, deletions, substitutions) needed to convert one string into the other. - **Input:** Two strings of length up to 1000 characters each. - **Output:** The minimum number of operations needed. - **Constraints:** 1 ≤ length of strings ≤ 1000. - **Tips:** Use a 2D DP table where dp[i][j] represents the minimum number of operations needed to convert the first i characters of the first string into the first j characters of the second string. # 7. **Rod Cutting Problem (URI 1031)** - **Description:** Given a rod of length n and a list of prices for different lengths, determine the maximum revenue that can be obtained by cutting the rod into pieces. - **Input:** An integer N (length of the rod), followed by N integers (prices for different lengths). - **Output:** The maximum revenue that can be obtained. - **Constraints:** 1 ≤ N ≤ 100. - **Tips:** Use a DP array where dp[i] represents the maximum revenue that can be obtained by cutting a rod of length i. # Recommended Difficulty Progression: 1. **Fibonacci Sequence (URI 1151)** 2. **Longest Increasing Subsequence (URI 1149)** 3. **Coin Change Problem (URI 1030)** 4. **Knapsack Problem (URI 1028)** 5. **Matrix Chain Multiplication (URI 1029)** 6. **Edit Distance (URI 1034)** 7. **Rod Cutting Problem (URI 1031)** This progression will help me build my skills from basic dynamic programming problems to more complex ones, preparing me effectively for the contest. Good luck!

answer:To answer this, let me think about how to approach drafting a comprehensive guide to the Current Agricultural Use Valuation (CAUV) program in Ohio, targeted at farmers and landowners who are not tax professionals. I need to ensure the guide is easy to read and understand, avoiding excessive jargon and including all the necessary points. First, let me break down what the CAUV program is and how it differs from traditional property tax valuation methods. The CAUV program is a tax incentive for Ohio farmers and landowners, valuing land based on its agricultural use rather than its market value. This often results in significantly lower property taxes for qualifying landowners. Wait, let me clarify this further - the key difference here is that traditional methods look at what the land could be sold for, whereas CAUV looks at what the land is actually used for, which is farming or other agricultural purposes. Now, let's consider the eligibility requirements for the CAUV program. To participate, landowners must meet specific criteria: - The land must be used for commercial agricultural purposes. - The land must be at least 10 acres in size, or if less than 10 acres, it must generate an average annual gross income of at least 2,500 from agricultural production. - The land must have been used for agricultural purposes for the three years preceding the application. Let me think about this for a moment - these requirements are in place to ensure that the program benefits those who are actively engaged in agriculture and are not just holding onto land for other purposes. Next, I need to outline a step-by-step guide on how to apply for CAUV. This involves: 1. Contacting your county auditor to obtain an application form. 2. Completing the application, providing details about your land use, acreage, and agricultural income. 3. Submitting the application to your county auditor's office before the deadline, which is usually the first Monday in January. 4. Waiting for approval, during which time the county auditor will review your application and inspect your property to verify its eligibility. Let me check on the deadline again to ensure accuracy - yes, it's crucial to submit the application on time as late filings are not accepted. Now, let's delve into how CAUV values are calculated. The calculation uses a capitalization of income approach, which estimates the income the land would generate from agricultural use and then capitalizes that income to determine the land's value. This can be broken down into: 1. Estimating the gross income the land would generate from agricultural use. 2. Subtracting the estimated expenses associated with generating that income. 3. Capitalizing the net income to determine the land's value. Wait, let me simplify this further - essentially, the value of the land under CAUV is based on how much money it can make from farming, minus the costs of farming, and then using that profit to calculate the land's worth. The renewal process and important deadlines are also critical. Landowners must renew their CAUV application annually, with the renewal deadline being the first Monday in January. It's essential to submit the renewal application on time, as late filings are not accepted. Let me think about the implications of missing this deadline - if a landowner fails to renew, they will not receive the CAUV tax benefits for that year, which could result in higher taxes. There are also common misconceptions about CAUV that need to be addressed. For instance, some may believe that CAUV reduces taxes for all types of land use, but in fact, it only applies to land used for commercial agricultural purposes. Additionally, withdrawing from the CAUV program or converting the land to a non-agricultural use may subject the landowner to recoupment of the tax savings they received under CAUV. Let me consider the potential implications of withdrawing - it's not a decision to be taken lightly, as it could lead to significant financial repercussions. Recent or upcoming changes to the CAUV program, including updates to the CAUV formula, are also important to note. The Ohio Department of Taxation periodically updates the formula to reflect changes in agricultural commodity prices, crop yields, and other factors. Landowners should stay informed about these updates, as they can affect CAUV values and tax savings. Let me think about how these changes might impact farmers - it's crucial for them to stay up-to-date to maximize their benefits from the program. Including case studies can help illustrate the potential tax savings for farmers who participate in CAUV. For example, a farmer with 100 acres of land used for corn and soybean production might see their land valued at 300,000 under CAUV, compared to 1,000,000 under traditional valuation, resulting in significant tax savings. Let me consider another example - a landowner with a smaller vineyard could also benefit, with their land being valued lower under CAUV, leading to reduced property taxes. Finally, providing a list of resources and contact information for further assistance is essential. This includes the Ohio Department of Taxation, the Ohio Farm Bureau Federation, and the landowner's county auditor's office. Let me make sure to include all the necessary contact details - having these resources readily available can make a big difference for landowners navigating the CAUV program. For the Frequently Asked Questions (FAQ) section, let's address some common queries: - **Q: Can I apply for CAUV if my land is less than 10 acres?** A: Yes, if your land generates an average annual gross income of at least 2,500 from agricultural production. - **Q: What happens if I miss the CAUV renewal deadline?** A: Late filings are not accepted, and you will not receive CAUV tax benefits for that year. - **Q: Can I withdraw from the CAUV program at any time?** A: Yes, but you may be subject to recoupment of the tax savings you received under CAUV if you withdraw or convert the land to a non-agricultural use. - **Q: How do I know if my land qualifies for CAUV?** A: Contact your county auditor's office; they can provide guidance on whether your land meets the eligibility requirements. - **Q: How often are CAUV values updated?** A: CAUV values are typically updated every three years, but the Ohio Department of Taxation can make adjustments more frequently if necessary. By following this guide, farmers and landowners in Ohio can better understand the CAUV program and how to benefit from it, ensuring they receive the tax savings they are eligible for. Let me review this guide one more time to ensure it covers all the necessary information in a clear and understandable manner.

answer:To answer this, let me think about the problem carefully. I need to optimize the given C++ code to find the length of the longest substring without repeating characters, achieving a linear time complexity of O(n). The current implementation uses a sliding window approach with a hash table but has a time complexity of O(n^2) due to repeated searches in the substring. Let me break down the problem first. The goal is to find the longest substring without repeating characters in a given string. This means I need to keep track of the characters I've seen so far and their last seen indices. I can use a hash table, specifically an `unordered_map` in C++, to store this information. Wait, let me check the current implementation again. It uses a nested loop to generate all possible substrings and checks for repeating characters in each substring. This is inefficient and leads to the O(n^2) time complexity. I need to find a way to avoid these repeated searches. Let me think about this... Ah, yes! I can use a sliding window approach with two pointers, `left` and `right`, to represent the current window of characters being considered. The `left` pointer will be the starting index of the window, and the `right` pointer will be the ending index. This way, I can avoid generating all possible substrings and reduce the time complexity. Now, let me design the optimized algorithm. I'll iterate through the string with the `right` pointer, and for each character, I'll check if it has been seen before and if its last seen index is within the current window. If it is, I'll move the `left` pointer to the right of the last seen index of the current character. This ensures that the current window always contains unique characters. Here's the optimized version of the code: ```cpp #include <unordered_map> #include <string> #include <algorithm> int lengthOfLongestSubstring(std::string s) { std::unordered_map<char, int> lastSeen; int maxLen = 0; int left = 0; for (int right = 0; right < s.length(); right++) { if (lastSeen.find(s[right]) != lastSeen.end()) { left = std::max(left, lastSeen[s[right]] + 1); } lastSeen[s[right]] = right; maxLen = std::max(maxLen, right - left + 1); } return maxLen; } ``` Let me explain the key improvements I made: 1. **Sliding Window with Two Pointers**: I used two pointers, `left` and `right`, to represent the current window of characters being considered. This allows me to avoid generating all possible substrings and reduce the time complexity. 2. **Hash Table for Last Seen Index**: I used an `unordered_map` called `lastSeen` to store the last seen index of each character. This helps me keep track of the characters I've seen so far and their last seen indices. 3. **Update the Window**: As I iterate through the string with the `right` pointer, I check if the current character has been seen before and if its last seen index is within the current window. If it is, I move the `left` pointer to the right of the last seen index of the current character. 4. **Update the Maximum Length**: I update the maximum length of the substring without repeating characters by comparing the current window size (`right - left + 1`) with the maximum length found so far (`maxLen`). 5. **Update the Last Seen Index**: I always update the last seen index of the current character to ensure that the `lastSeen` hash table is up-to-date. This optimized approach ensures that each character is processed only once, resulting in a time complexity of O(n). The space complexity is O(min(n, m)), where n is the length of the string and m is the size of the character set (e.g., 128 for ASCII). Fantastic! After all these calculations, I can confidently say that the optimized code achieves a linear time complexity of O(n) and finds the length of the longest substring without repeating characters efficiently.

answer:To answer this, I need to find a comprehensive way to draft a guide on implementing a new code syntax highlighter for the wiki, which involves comparing three popular JavaScript libraries: Prism.js, Highlight.js, and CodeMirror. Let me think about this carefully. This means I have to delve into the specifics of each library, including their pros and cons, and provide a step-by-step integration tutorial tailored to the wiki's MediaWiki setup. I should also consider potential performance implications, accessibility concerns, and mobile compatibility issues for each library. Additionally, I need to discuss how to create custom themes for these libraries to match the wiki's visual style. Wait, let me break this down first. To start, I should introduce the purpose of the guide and the importance of implementing a new code syntax highlighter for the wiki. This will involve explaining how a syntax highlighter can improve the readability and aesthetics of code snippets on the wiki. Now, let's move on to the comparison of the three JavaScript libraries. I'll begin with Prism.js. Prism.js is known for being lightweight and extensible, supporting a wide range of languages. It's also relatively easy to use. However, it might have less customization options out of the box compared to other libraries. Let me check the documentation for Prism.js to confirm its features and integration process. For Prism.js, the integration tutorial will involve downloading the necessary files from the Prism.js website, uploading them to the MediaWiki installation, and including Prism.js in the LocalSettings.php file. I'll also need to provide an example of how to load Prism.js in wiki pages and use it to highlight code snippets. Next, I'll consider the performance, accessibility, and mobile compatibility of Prism.js. From what I understand, Prism.js is lightweight and performs well, even with large code snippets. It also supports ARIA roles for better accessibility and is responsive, making it work well on mobile devices. Let me think about how to create custom themes for Prism.js. This will involve overriding the default CSS styles in the prism.css file. I can provide an example of how to do this, such as changing the background color and text color to match the wiki's visual style. Now, let's move on to Highlight.js. Highlight.js is a robust syntax highlighter that supports a wide range of languages and themes. It's highly customizable and easy to integrate. However, it might have a larger file size compared to Prism.js, which could impact performance. Let me review the documentation for Highlight.js to understand its features and integration process. The integration tutorial for Highlight.js will be similar to Prism.js, involving downloading the necessary files, uploading them to the MediaWiki installation, and including Highlight.js in the LocalSettings.php file. I'll also provide an example of how to load Highlight.js in wiki pages and use it to highlight code snippets. Considering the performance, accessibility, and mobile compatibility of Highlight.js, it's known that Highlight.js can be slower with large code snippets due to its extensive feature set. However, it supports ARIA roles for better accessibility and is responsive, making it work well on mobile devices. To create custom themes for Highlight.js, I can override the default CSS styles in the chosen theme CSS file. This will involve changing the background color, text color, and other styles to match the wiki's visual style. Lastly, let's consider CodeMirror. CodeMirror is a versatile code editor implemented in JavaScript for the browser. It's highly customizable and supports a wide range of languages and features. However, it might have a larger file size compared to Prism.js and Highlight.js, and it could be more complex to integrate. Let me examine the documentation for CodeMirror to understand its features and integration process. The integration tutorial for CodeMirror will involve downloading the necessary files, uploading them to the MediaWiki installation, and including CodeMirror in the LocalSettings.php file. I'll also provide an example of how to load CodeMirror in wiki pages and use it to create a full-featured code editor. Considering the performance, accessibility, and mobile compatibility of CodeMirror, it's known that CodeMirror can be slower with large code snippets due to its extensive feature set. However, it supports ARIA roles for better accessibility. For mobile compatibility, CodeMirror is responsive but may require additional configuration for optimal performance. To create custom themes for CodeMirror, I can override the default CSS styles in the codemirror.css file. This will involve changing the background color, text color, and other styles to match the wiki's visual style. In conclusion, choosing the right code syntax highlighter depends on specific needs and preferences. Prism.js is lightweight and fast, Highlight.js is highly customizable, and CodeMirror offers a full-featured code editor. Considering the performance, accessibility, and mobile compatibility of each library, as well as the ability to create custom themes, will help in making an informed decision. Here is the detailed guide: # Implementing a New Code Syntax Highlighter for Our Wiki This guide provides a comprehensive overview of implementing a new code syntax highlighter for our wiki, which runs on MediaWiki. We will compare three popular JavaScript libraries: Prism.js, Highlight.js, and CodeMirror. Each section includes a brief overview, pros and cons, integration tutorial, and considerations for performance, accessibility, and mobile compatibility. Additionally, we will discuss how to create custom themes to match our wiki's visual style. Table of Contents 1. [Introduction](#Introduction) 2. [Prism.js](#Prism.js) - [Overview](#Overview_1) - [Pros and Cons](#Pros_and_Cons_1) - [Integration Tutorial](#Integration_Tutorial_1) - [Performance, Accessibility, and Mobile Compatibility](#Performance_Accessibility_and_Mobile_Compatibility_1) - [Custom Themes](#Custom_Themes_1) 3. [Highlight.js](#Highlight.js) - [Overview](#Overview_2) - [Pros and Cons](#Pros_and_Cons_2) - [Integration Tutorial](#Integration_Tutorial_2) - [Performance, Accessibility, and Mobile Compatibility](#Performance_Accessibility_and_Mobile_Compatibility_2) - [Custom Themes](#Custom_Themes_2) 4. [CodeMirror](#CodeMirror) - [Overview](#Overview_3) - [Pros and Cons](#Pros_and_Cons_3) - [Integration Tutorial](#Integration_Tutorial_3) - [Performance, Accessibility, and Mobile Compatibility](#Performance_Accessibility_and_Mobile_Compatibility_3) - [Custom Themes](#Custom_Themes_3) 5. [Conclusion](#Conclusion) Introduction Implementing a new code syntax highlighter can significantly improve the readability and aesthetics of code snippets on our wiki. This guide will help you choose the right library and integrate it seamlessly into our MediaWiki setup. Prism.js # Overview Prism.js is a lightweight, extensible syntax highlighter that supports a wide range of languages. It is known for its simplicity and ease of use. # Pros and Cons **Pros:** - Lightweight and fast - Easy to extend with plugins - Supports a wide range of languages **Cons:** - Less customizable out of the box compared to other libraries - Requires manual configuration for some features # Integration Tutorial 1. **Download Prism.js:** - Visit the [Prism.js website](https://prismjs.com/) and download the necessary files. 2. **Upload Files to MediaWiki:** - Upload `prism.js` and `prism.css` to your MediaWiki installation. 3. **Include Prism.js in LocalSettings.php:** ```php wgResourceModules['ext.prism'] = [ 'scripts' => ['path/to/prism.js'], 'styles' => ['path/to/prism.css'], 'localBasePath' => __DIR__, 'remoteExtPath' => 'path/to/extension', ]; ``` 4. **Load Prism.js in Your Wiki Pages:** ```php wgHooks['BeforePageDisplay'][] = function ( OutputPage &out, Skin &skin ) { out->addModules( 'ext.prism' ); }; ``` 5. **Use Prism.js in Wiki Pages:** ```html <pre><code class="language-javascript"> // Your code here </code></pre> ``` # Performance, Accessibility, and Mobile Compatibility - **Performance:** Prism.js is lightweight and performs well even on large code snippets. - **Accessibility:** Prism.js supports ARIA roles for better accessibility. - **Mobile Compatibility:** Prism.js is responsive and works well on mobile devices. # Custom Themes To create a custom theme, you can override the default CSS styles in `prism.css`. Here is an example: ```css /* Custom Prism.js Theme */ .prism-code { background: #282a36; color: #f8f8f2; } .token.comment, .token.prolog, .token.doctype, .token.cdata { color: #6272a4; } /* Add more custom styles as needed */ ``` Highlight.js # Overview Highlight.js is a robust syntax highlighter that supports a wide range of languages and themes. It is highly customizable and easy to integrate. # Pros and Cons **Pros:** - Highly customizable - Supports a wide range of languages and themes - Easy to integrate **Cons:** - Larger file size compared to Prism.js - Performance can be slower with large code snippets # Integration Tutorial 1. **Download Highlight.js:** - Visit the [Highlight.js website](https://highlightjs.org/) and download the necessary files. 2. **Upload Files to MediaWiki:** - Upload `highlight.js` and your chosen theme CSS file to your MediaWiki installation. 3. **Include Highlight.js in LocalSettings.php:** ```php wgResourceModules['ext.highlight'] = [ 'scripts' => ['path/to/highlight.js'], 'styles' => ['path/to/your-theme.css'], 'localBasePath' => __DIR__, 'remoteExtPath' => 'path/to/extension', ]; ``` 4. **Load Highlight.js in Your Wiki Pages:** ```php wgHooks['BeforePageDisplay'][] = function ( OutputPage &out, Skin &skin ) { out->addModules( 'ext.highlight' ); }; ``` 5. **Use Highlight.js in Wiki Pages:** ```html <pre><code class="language-javascript"> // Your code here </code></pre> ``` # Performance, Accessibility, and Mobile Compatibility - **Performance:** Highlight.js can be slower with large code snippets due to its extensive feature set. - **Accessibility:** Highlight.js supports ARIA roles for better accessibility. - **Mobile Compatibility:** Highlight.js is responsive and works well on mobile devices. # Custom Themes To create a custom theme, you can override the default CSS styles in your chosen theme CSS file. Here is an example: ```css /* Custom Highlight.js Theme */ .hljs { background: #282a36; color: #f8f8f2; } .hljs-comment, .hljs-quote { color: #6272a4; } /* Add more custom styles as needed */ ``` CodeMirror # Overview CodeMirror is a versatile code editor implemented in JavaScript for the browser. It is highly customizable and supports a wide range of languages and features. # Pros and Cons **Pros:** - Highly customizable - Supports a wide range of languages and features - Provides a full-featured code editor **Cons:** - Larger file size compared to Prism.js and Highlight.js - More complex to integrate # Integration Tutorial 1. **Download CodeMirror:** - Visit the [CodeMirror website](https://codemirror.net/) and download the necessary files. 2. **Upload Files to MediaWiki:** - Upload `codemirror.js`, `codemirror.css`, and the language mode files to your MediaWiki installation. 3. **Include CodeMirror in LocalSettings.php:** ```php wgResourceModules['ext.codemirror'] = [ 'scripts' => ['path/to/codemirror.js', 'path/to/mode/javascript.js'], 'styles' => ['path/to/codemirror.css'], 'localBasePath' => __DIR__, 'remoteExtPath' => 'path/to/extension', ]; ``` 4. **Load CodeMirror in Your Wiki Pages:** ```php wgHooks['BeforePageDisplay'][] = function ( OutputPage &out, Skin &skin ) { out->addModules( 'ext.codemirror' ); }; ``` 5. **Use CodeMirror in Wiki Pages:** ```html <textarea id="code" name="code"> // Your code here </textarea> <script> var editor = CodeMirror.fromTextArea(document.getElementById("code"), { lineNumbers: true, mode: "javascript" }); </script> ``` # Performance, Accessibility, and Mobile Compatibility - **Performance:** CodeMirror can be slower with large code snippets due to its extensive feature set. - **Accessibility:** CodeMirror supports ARIA roles for better accessibility. - **Mobile Compatibility:** CodeMirror is responsive but may require additional configuration for optimal mobile performance. # Custom Themes To create a custom theme, you can override the default CSS styles in `codemirror.css`. Here is an example: ```css /* Custom CodeMirror Theme */ .CodeMirror { background: #282a36; color: #f8f8f2; } .cm-comment { color: #6272a4; } /* Add more custom styles as needed */ ``` Conclusion Choosing the right code syntax highlighter depends on your specific needs and preferences. Prism.js is lightweight and fast, Highlight.js is highly customizable, and CodeMirror offers a full-featured code editor. Consider the performance, accessibility, and mobile compatibility of each library when making your decision. Custom themes can be created for all three libraries to match our wiki's visual style.