How does the diff algorithm work?

This tool uses the Longest Common Subsequence (LCS) algorithm. It builds a dynamic programming table comparing every line of the first text against every line of the second text, then backtracks through the table to identify which lines are common (unchanged), which exist only in the first text (removed), and which exist only in the second text (added). The LCS approach produces a minimal set of changes, which is the same fundamental technique used by Git diff and the Unix diff command.

Can I ignore whitespace or case differences?

Yes. The tool provides two toggle options: "Ignore Whitespace" strips all whitespace before comparing lines, so lines that differ only in spacing or indentation are treated as identical. "Ignore Case" converts both texts to lowercase before comparison, so "Hello" and "hello" are treated as the same. You can enable both simultaneously. The diff output still shows the original content with its original formatting.

What is the difference between inline and side-by-side view?

In inline (unified) view, all changes are shown in a single column with + and - prefixes indicating additions and removals, similar to git diff output. In side-by-side view, the original text appears on the left and the modified text on the right, with added, removed, and unchanged lines aligned. Side-by-side view makes it easier to visually compare corresponding sections, while inline view is more compact and better for copying into commit messages or pull requests.

Is my data sent to a server?

No. This tool runs entirely in your browser. All diff computation happens client-side using JavaScript, and your text never leaves your device or gets uploaded to any server. This makes it safe to use with sensitive data like proprietary source code, private documents, or configuration files containing secrets. Once you close or refresh the page, all data is cleared.

What types of text can I compare?

You can compare any plain text: source code in any programming language, configuration files (JSON, YAML, XML, INI), markdown documents, log files, CSV data, prose, legal documents, translations, and more. The tool compares line by line, so it works best with text that has meaningful line breaks. Very long single-line texts may not produce useful diffs since the entire line would be marked as changed.

Does the tool work on mobile devices?

Yes. The tool is fully responsive and works on all modern mobile browsers. On smaller screens, the input textareas stack vertically and the side-by-side diff view adapts to fit the screen. All features including the compare, copy, clear, and load example buttons are available on mobile. The touch-friendly interface ensures a smooth experience on phones and tablets.

🛠️DevToolsHub

Text Diff Checker

Compare two text blocks and highlight the differences line by line.

What is a Text Diff Checker?

A text diff checkeris a tool that compares two pieces of text and highlights the differences between them. The word “diff” is short for “difference,” and diff tools have been a staple of software development since the early days of Unix in the 1970s. The originaldiff command, created by Douglas McIlroy in 1974, established the fundamental approach that modern diff tools still follow: identify which lines were added, removed, or changed between two versions of a file.

DevToolsHub’s Text Diff Checker brings this essential capability to your browser with a clean, intuitive interface. It uses the Longest Common Subsequence (LCS)algorithm — the same mathematical foundation used by Git, diff utilities, and merge tools — to determine the minimal set of changes between two texts. The result is presented in two view modes: an inline unified view (similar to diff -u output) and a side-by-side view that shows both versions simultaneously for easy visual comparison.

Unlike command-line diff tools that require a terminal and file access, this tool runs entirely in your browser. You can paste any two texts — code snippets, configuration files, blog drafts, legal documents, or any plain text — and instantly see what changed. The tool works offline once loaded, never sends your data to a server, and handles files of any size that your browser can manage. It also supports options to ignore whitespace differences and case, making it flexible enough for a wide range of comparison scenarios.

How to Use

Paste the original textinto the left textarea. This is the “before” version.
Paste the modified textinto the right textarea. This is the “after” version.
Adjust optionsif needed: toggle “Ignore Whitespace” to treat lines that differ only in spacing as identical, or “Ignore Case” for case-insensitive comparison.
Choose a view mode: “Inline” for a unified diff (additions prefixed with +, removals with -), or “Side-by-Side” for a two-column layout.
Click Compare to generate the diff. The results appear below with color-coded lines: green for additions, red for removals, and gray for unchanged lines.
Review the stats showing the number of additions, deletions, and unchanged lines.
Copy the diffto your clipboard using the “Copy Diff” button (available in inline mode).
Click Load Example to see how the tool works with sample code, or Clear to reset everything.

Diff Algorithms Explained

The core of any diff tool is the algorithm used to find the differences between two texts. This tool uses the Longest Common Subsequence (LCS) algorithm, which is one of the most widely used approaches in diff tools. The LCS algorithm works by finding the longest sequence of lines that appear in both texts in the same order (though not necessarily consecutively). Once the LCS is identified, any lines not in the LCS are classified as additions or removals.

The algorithm operates in two phases. First, it builds a dynamic programming table where each cell table[i][j] stores the length of the LCS of the first i lines of text 1 and the first j lines of text 2. This table is built bottom-up in O(m × n) time and space, where m and n are the number of lines in each text. Second, it backtracks through the table from table[m][n] back to table[0][0], emitting diff lines as it goes: when the lines match, it emits an unchanged line; when it moves up, it emits a removal; when it moves left, it emits an addition.

The LCS-based approach produces a minimal edit script— the smallest set of changes needed to transform text 1 into text 2. This is the same approach used by Git’s git diff command, the diff utility, and many code review tools. More advanced algorithms like Myers’ difference algorithm or the patience diff algorithm offer performance improvements or better semantic grouping, but the LCS algorithm remains the clearest and most educational approach for understanding how diffs work.

The unified diff format (shown in inline mode) is a standard way to represent diffs compactly. It groups changes into hunks, each preceded by a header like @@ -1,3 +1,4 @@ that indicates the starting line and count in both the original and modified files. Lines prefixed with + are additions, lines prefixed with - are removals, and lines prefixed with a space are context (unchanged). This format is used by Git, patch files, and code review tools.

Common Use Cases

Code review— Compare two versions of a source file to see exactly what changed before committing or merging. This is especially useful when reviewing patches or pull requests outside of a Git interface.
Configuration file changes— Diff an old config file against a new one to verify that only the intended settings changed and nothing was accidentally modified or removed.
Document revision tracking— Compare two drafts of a document, article, or README to see what was added, removed, or rephrased between versions.
Log file comparison— Diff two log files from different runs to identify when behaviour changed or new errors appeared.
Data file validation— Compare exported data files (CSV, JSON, YAML) to spot unexpected differences after a migration or transformation.
Legal and contract review— Compare two versions of a contract or agreement to identify exactly which clauses were modified, added, or removed.
Translation QA— Compare source text with translations or updated source to keep translation files in sync.
Education— Teach students how diff algorithms work by showing the LCS in action with visual, color-coded output.

Frequently Asked Questions