In short: what is a code diff checker?
A code diff checker compares two versions of text or code and highlights exactly what changed — added, removed and modified lines — using the same Myers diff algorithm that Git uses. This tool adds side-by-side, inline and unified views, word-level highlighting, structured JSON diffing, code-metric deltas, move detection, and security & performance review insights — all 100% privately in your browser, with nothing ever uploaded.
Exact Myers diff
The same shortest-edit-script algorithm Git uses, with word-level highlighting.
Three views
Side-by-side, inline and unified — switch instantly to suit the change.
Structured JSON diff
Compare JSON by key and path, ignoring formatting and key-order noise.
Security scanner
Flags secrets, eval, auth changes and injection risks in added code.
Performance insights
Surfaces N+1, await-in-loop, SELECT * and other costly patterns.
100% private
Everything runs in your browser. Your code is never uploaded.
What is a code diff checker?
A code diff checker (also called a diff tool, file-compare tool or code comparison tool) takes two inputs — an original and a changed version — and computes the precise set of edits that turns one into the other. Instead of squinting at two files trying to spot what moved, you get a colour-coded view: additions in green, deletions in red and in-place edits highlighted down to the individual word.
Diffing is the quiet engine behind modern software development. Every Git commit stores a snapshot that is later diffed against its parent; every pull request is a diff between a feature branch and its base; every code review is, at heart, a human reading a diff. A good diff tool therefore does more than colour lines — it helps you understand the shape and risk of a change so you can review it confidently and quickly.
This tool is built around three pillars:
- An exact diff engine — a from-scratch implementation of Myers' shortest-edit-script algorithm with common prefix/suffix trimming, producing a minimal, provably-correct diff.
- Multiple views — side-by-side (split), inline and unified, plus structured JSON diffing for data files.
- A review layer — change statistics, code-metric deltas, move detection, and security & performance scanners that turn a raw diff into an actionable review.
How Git diffs work
Git does not store diffs — it stores snapshots. Each commit references a tree of file blobs as they existed at that moment. When you run git diff, Git compares two of these snapshots on the fly and produces a unified diff: the minimal sequence of line insertions and deletions needed to go from one to the other, surrounded by a few lines of context.
Under the hood, Git uses a Myers-style diff (with optional patience and histogram variants for cleaner results on certain inputs). The algorithm models the two files as sequences and finds the shortest edit script — the fewest insertions and deletions — which usually corresponds to the most human-intuitive diff. This tool implements the same core algorithm, so the diffs you see here match what Git would produce.
A unified diff hunk header like @@ -12,6 +12,7 @@ means: starting at line 12 of the old file, 6 lines are shown; starting at line 12 of the new file, 7 lines are shown. Lines prefixed with - were removed, + were added, and a leading space marks unchanged context. Because the header encodes positions, a patch can be applied even when the surrounding code has shifted — which is exactly how git apply and the patch utility work. You can export any comparison here as a ready-to-apply unified diff.
Code review best practices
Code review is one of the highest-leverage activities in software engineering: it catches bugs early, spreads knowledge across a team and keeps a codebase coherent. But reviews are only effective when they are focused. Diff tooling exists to make the signal — the real change — easy to find amid the noise of formatting and reorganization.
- Review small, focused changes. Smaller diffs get more thorough reviews. This tool's change-size and churn metrics help you judge whether a change is reviewable in one sitting.
- Separate refactors from behaviour changes. Use move detection to subtract relocated code from the real change, and review pure refactors separately from logic edits.
- Read the summary first. Orient yourself with the change summary and metric deltas before diving line by line.
- Check for security and performance regressions. Scan added code for secrets, unsafe patterns and expensive operations — the review insights here do a first pass automatically.
- Watch complexity. A rising cyclomatic-complexity delta signals more branches and more tests required; question whether the added complexity is justified.
- Be specific and kind. Comment on concrete lines with actionable suggestions, and acknowledge good changes — review is a conversation, not a gate.
Semantic vs text diffs
A text diff treats input as plain lines and reports every character-level change. It is fast, universal and exact — but it does not understand your code, so reformatting a file or renaming a local variable can produce a large diff that represents almost no real change.
A semantic diff compares the structure or meaning of code: it parses the input into a tree (objects and keys for JSON, or an abstract syntax tree for source code) and reports changes in terms of that structure. Re-ordering keys, re-indenting blocks or adding whitespace produces no semantic diff at all, because the underlying structure is identical.
| Aspect | Text diff | Semantic / structural diff |
|---|---|---|
| Granularity | Lines & words | Keys, nodes, structure |
| Formatting noise | Shows it | Ignores it |
| Works on | Any text | Parseable formats (JSON, AST) |
| Speed | Very fast | Slower (needs parsing) |
| Best for | General comparison | Data & deep refactors |
This tool gives you both: a precise line/word text diff for any language, and a structural JSON diff that compares by key and path. Move detection and code-metric deltas further approximate semantic understanding without a full language parser.
JSON diff comparison
Comparing JSON as plain text is frustrating: a re-ordered key or a reformatted block lights up the whole diff even though the data is identical. A structural JSON diff solves this by walking both documents key-by-key and reporting changes by path — for example $.user.email changed, $.items[2] added, $.legacyFlag removed.
Enable structured JSON comparison in the toolbar and, when both sides are valid JSON, the tool switches from a line diff to a deep object diff. It reports added, removed and changed values regardless of key order or formatting, which is ideal for comparing API responses between versions, reviewing configuration changes, or spotting breaking changes in a data contract. When either side is not valid JSON, the tool gracefully falls back to the standard text diff. To clean up JSON before comparing, pair this with our JSON Formatter & Validator.
XML & data-file diff comparison
XML, YAML and CSV are everywhere in configuration, data exchange and infrastructure. Comparing them well is mostly about controlling noise. For XML, re-indentation and attribute re-ordering can swamp a naive diff, so compare with the ignore-whitespace option enabled and let the line and word diff highlight changed elements and attributes precisely.
For YAML — the lingua franca of Kubernetes manifests, CI pipelines and Docker Compose — indentation is significant, so use ignore-whitespace judiciously and rely on the line diff to show changed keys and values. For CSV, compare row-by-row: the diff highlights added, removed and modified records, and the change statistics tell you how many rows differ. To normalize any of these before comparing, our XML Formatter and YAML Validator produce clean, consistently-formatted output that diffs cleanly.
Pull request reviews
A pull request (or merge request) is a proposal to merge one branch into another, presented as a diff. Reviewing one well means understanding not just what changed but why it matters and what could go wrong. The mechanics are simple — read the diff, leave comments, approve or request changes — but the discipline is what separates a rubber stamp from a real safeguard.
To review a pull request with this tool, paste the base-branch version of a file on the left and the proposed version on the right. You then get:
- A change summary — churn, hunks, function and complexity deltas in plain English.
- Move detection — so relocated code does not masquerade as new logic.
- Security & performance insights — an automatic first pass over the added lines.
- A review health grade — an A–F risk signal to help you size your review.
Work through a multi-file PR one file at a time, starting with the files that have the highest churn, complexity increase or security findings. The per-comparison reports can be exported and attached to your review for a clear record of what was inspected.
Secure code reviews
Security review is the practice of examining changes for vulnerabilities and accidental exposures before they reach production. The most common — and most preventable — incidents are leaked credentials and unsafe new code paths, both of which show up plainly in a diff if you know what to look for.
This tool's security scanner inspects only the added lines (the new attack surface) and flags patterns such as:
- Hardcoded secrets & API keys — credential-like assignments, AWS access keys and private-key blocks that should never be committed.
- Dangerous execution — use of
evaland raw HTML injection that can enable code execution or XSS. - Auth & permission changes — edits to roles, tokens and authorization logic that deserve careful scrutiny.
- Injection risks — SQL built via string concatenation rather than parameterized queries.
- Weakened transport security — plaintext HTTP endpoints and disabled TLS verification.
Each finding includes the line, a snippet and a recommended fix. Treat any leaked secret as urgent: rotate it immediately and move it to an environment variable or secrets manager. Because the scanner runs entirely in your browser, you can safely review proprietary code without it ever leaving your device.
Performance impact reviews
Performance regressions rarely announce themselves — they creep in one innocent-looking change at a time. Reviewing the performance impact of a diff means asking whether the added code introduces expensive operations on hot paths, and the answer is often visible in the diff itself.
The performance scanner highlights added code that commonly hurts performance:
- SELECT * queries that fetch more data than needed.
- Await inside loops that serialize asynchronous work instead of running it in parallel.
- Nested array iteration that turns an O(n) operation into O(n²).
- Chained array passes and synchronous file I/O that allocate or block unnecessarily.
- New imports and stray debug logging that affect bundle size and runtime noise.
These are heuristics, not verdicts — they point you to the lines most worth profiling. Combined with the cyclomatic-complexity delta, they give you a fast read on whether a change is likely to make the system slower or harder to maintain, so you can ask the right questions in review.
Enterprise code review workflows
At scale, code review is a system, not an act. Enterprises layer automated checks, required approvals, ownership rules and audit trails on top of the basic diff to keep thousands of changes a day safe and consistent. A browser-based diff tool fits naturally into that system as a fast, private scratchpad for the moments when you need to compare two versions outside the pipeline.
Typical enterprise practices a strong diff workflow supports include:
- Mandatory review & CODEOWNERS — every change is read by someone accountable for that area before merge.
- Automated gates — linting, tests, security scanning and complexity budgets run in CI on every diff.
- Small, atomic changes — encouraged because they review faster and roll back cleanly.
- Auditability — every change is traceable to a diff, a reviewer and a reason, which exportable reports here help document.
- Knowledge sharing — review spreads understanding and reduces bus-factor risk across the team.
Because this tool runs entirely client-side, it is safe to use even in regulated environments where source cannot be sent to third-party services — a genuine advantage over cloud diff tools when you are comparing sensitive code, secrets-adjacent config or pre-release work.
Frequently asked questions
A code diff checker is a tool that compares two pieces of text or code and highlights exactly what changed between them — which lines were added, removed or modified. It turns a wall of text into a clear, colour-coded view so you can review changes quickly. This tool compares any two snippets in your browser and shows side-by-side, inline and unified views, plus change statistics and code-review insights.
Paste the original version on the left and the new version on the right (or upload two files). The diff engine aligns the two and instantly highlights additions in green, deletions in red and modified lines in amber, with word-level highlighting inside changed lines. You can switch between side-by-side, inline and unified views and toggle options like ignore-whitespace.
A diff (short for difference) is a compact description of the changes needed to turn one version of a file into another. It lists the lines that were inserted, deleted or left unchanged. Diffs are the foundation of version control: every Git commit, pull request and code review is built on top of diffs.
A unified diff is the standard text format used by Git and patch tools. It shows changes inline with a few lines of surrounding context, prefixing added lines with +, removed lines with - and unchanged context with a space. Hunks are introduced by @@ headers that give the line ranges. This tool can export your comparison as a unified diff you can apply with git apply or patch.
A side-by-side (split) diff places the original on the left and the new version on the right in two parallel columns, with changed lines aligned across both. It is the easiest view for reading substantial changes because you can see the before and after of each line at the same time. This tool offers side-by-side, inline and unified views.
An inline (unified-style) diff shows a single column where removed lines appear immediately above the added lines that replace them. It is compact and works well on narrow screens or for small changes. You can switch to inline view with one click in the toolbar.
This tool implements Myers’ O(ND) shortest-edit-script algorithm — the same family Git uses — to find the minimal set of insertions and deletions that transform the left text into the right. It first trims any common prefix and suffix for speed, then computes the optimal alignment of the remaining lines, and finally runs a second word-level diff inside modified lines for precise highlighting.
A semantic diff compares the meaning or structure of code rather than its raw text. For example, reformatting a function or renaming a local variable produces a large textual diff but little semantic change. This tool provides structural JSON diffing (key-by-key), refactor and move detection, and code-metric deltas that approximate semantic comparison without a full language parser.
A text diff treats the input as plain lines and reports every character-level change, so cosmetic edits like re-indentation show up as differences. A semantic diff understands the structure — objects, keys, functions — and reports only meaningful changes. Use a text diff for general comparison and a structural/semantic diff (such as the JSON mode here) when formatting noise would obscure the real change.
Git stores snapshots of your files and computes diffs on demand by comparing two snapshots (commits, branches, the index or the working tree). It uses a Myers-style algorithm to produce a minimal edit script and presents it as a unified diff. Commands like git diff, git show and git log -p all render these diffs; pull requests are simply a diff between a feature branch and its base.
Yes. You can paste the two file versions to generate a fresh diff, and you can export your comparison as a unified diff/patch. To review an existing patch, paste the before and after content into the two panels. The unified-diff export is compatible with git apply and the standard patch utility.
Yes. Switch on structured JSON comparison and, when both sides are valid JSON, the tool performs a key-by-key structural diff that reports added, removed and changed values by path (for example $.user.email) — ignoring formatting and key-order noise that a plain text diff would flag. For invalid JSON it falls back to a normal line diff.
Yes. XML is compared as text with whitespace-insensitive options so that re-indentation does not create noise, and the line diff highlights changed elements and attributes. For structured key-level comparison, JSON mode offers the deepest analysis; XML, YAML and CSV are best compared with the text engine plus the ignore-whitespace option.
Yes. Both are compared with the line diff engine. Enable ignore-whitespace for YAML to avoid indentation noise, and compare CSV row-by-row to spot added, removed or changed records. The change statistics tell you exactly how many lines differ.
Paste the base-branch version of a file on the left and the pull-request version on the right. The tool highlights every change, summarizes the additions, deletions and modifications, detects moved blocks, and surfaces security and performance considerations in the added code — giving you a focused checklist before you approve or request changes.
Focus on correctness, readability, security, performance and test coverage. Check that the change does what it claims, that names and structure are clear, that no secrets or unsafe patterns were introduced, that hot paths are not slowed down, and that complexity is not creeping up. This tool’s review insights — change summary, complexity delta, security and performance scanners — help you cover these systematically.
The security scanner inspects only the added lines and flags patterns such as hardcoded secrets and API keys, private-key blocks, use of eval, raw HTML injection, authentication and authorization changes, SQL built by string concatenation and disabled TLS verification. Each finding includes the line, a snippet and a recommended fix so you can act before merging.
The performance scanner looks for added code that often hurts performance: SELECT * queries, await inside loops, nested array iteration (O(n²)), chained array passes, synchronous file I/O and stray debug logging. These are heuristics, not proof of a regression, but they direct your attention to the lines most worth profiling.
A moved block is code that was deleted in one location and re-added verbatim somewhere else — common when you reorder functions or extract code. A naive diff counts it as both a deletion and an addition, inflating the apparent change. This tool detects identical removed/added lines and reports them as moves, so the real logical change looks smaller and is easier to review.
Cyclomatic complexity counts the number of independent paths through a piece of code — roughly the number of branches (if, for, while, case, catch) plus logical operators. Higher complexity means more ways the code can behave and more tests needed to cover it. The tool reports the complexity of each side and the delta, so you can see whether a change is making the code harder to reason about.
A code quality delta is the change in objective metrics between the two versions — lines of code, function and class counts, imports, TODO markers and cyclomatic complexity. A negative complexity delta (complexity going down) generally signals a simplification, while a sharp increase suggests added decision logic that deserves extra scrutiny.
The review health score combines change size, complexity delta and security findings into a single risk grade from A to F. Small, low-complexity, finding-free changes score well and are safe to fast-track; large or security-sensitive changes score lower and signal that a more thorough review is warranted.
Yes — it is 100% free with no sign-up, no usage limits and no watermarks. Compare as many files as you like, as often as you like, and export unlimited reports.
Completely. The entire diff engine, analysis layer, scanners and report generators run locally in your browser using JavaScript. Your code is never uploaded to a server, never logged and never stored remotely, which makes the tool safe for proprietary, confidential and regulated source code.
Yes, within reason. The engine trims common prefixes and suffixes before running the diff, which makes large but similar files fast to compare. Extremely large or wildly different inputs take longer because diffing is inherently more expensive in that case, but the comparison still runs entirely on your device.
Yes. Toggle ignore-whitespace to disregard differences in spaces and tabs, ignore-case to compare without case sensitivity, and trim-lines to ignore leading and trailing whitespace. These options let you focus on substantive changes and hide cosmetic reformatting.
Absolutely. Paste the old function on the left and the new one on the right. The word-level highlighting shows exactly which tokens changed, and the metrics delta tells you whether complexity went up or down — ideal for reviewing a focused refactor.
The line and word diff work with any text, so every programming language is supported out of the box — JavaScript, TypeScript, Python, Go, Rust, Java, C#, PHP, SQL, HTML, CSS, JSON, YAML, XML, Markdown, Bash, Dockerfile and more. The tool also auto-detects the language to label your comparison and tune its heuristics.
Use the Export panel to copy or download your comparison as a unified diff/patch, a self-contained HTML report, or a JSON report containing the full change data and statistics. Reports are generated locally and are ready to attach to a ticket, email or pull-request comment.
Unified diffs are the lingua franca of patches. They are produced by git diff, emailed as patches, posted in code reviews and applied with git apply or patch. Exporting your comparison as a unified diff lets you share an exact, machine-applicable description of the change.
You can paste file contents copied from GitHub, GitLab or any source, and paste unified diffs to inspect them. Direct repository fetching is limited by browser cross-origin rules, so copy-pasting the two file versions is the reliable, privacy-preserving method that always works without granting any access to your account.
The line diff is exact: it computes a minimal edit script, and the result provably reconstructs both inputs. The word-level highlighting is likewise exact. The analysis features — security, performance, refactor detection and the AI-style summary — are heuristic by design and meant to guide attention, not to replace human judgment.
This tool runs entirely in your browser with no upload, no account and no paywall, and it adds a review layer most diff tools lack: security and performance scanners, complexity and metric deltas, move/refactor detection, a review health grade and a plain-English change summary. It is a diff viewer and a lightweight automated code reviewer in one.
The tool compares two inputs at a time, which covers the vast majority of review tasks (old vs new, branch vs branch, theirs vs mine). For multi-file pull requests, compare each file in turn; the per-comparison statistics and reports can be combined into your overall review.
Yes. When a line is modified rather than wholly added or removed, the tool runs a second word-level diff and highlights only the tokens that actually changed, so you can see precisely what was edited instead of the whole line lighting up.
The similarity percentage estimates how much of the content is shared between the two versions, based on the proportion of unchanged lines relative to total churn. 100% means identical; a low percentage means the two inputs are largely different. It is a quick gauge of how substantial a change is.
Yes. The engine diffs any text, so it works for documentation, configuration, logs, contracts or essays just as well as code. Word-level highlighting makes it easy to spot small wording changes in long passages.
Switch on structured JSON comparison. The structural diff walks both objects by key and path rather than by line, so re-ordering keys or reformatting does not register as a change — only genuinely added, removed or changed values are reported.
An AST (Abstract Syntax Tree) diff compares the parsed structure of code rather than its text, so it can ignore formatting entirely and report changes in terms of nodes — functions, expressions, statements. This tool approximates structural comparison with JSON-tree diffing and code-metric analysis; full multi-language AST diffing requires a language-specific parser.
It surfaces likely renames indirectly: word-level highlighting shows an identifier changing on a modified line, move detection catches relocated blocks, and the metrics delta reveals when function or class counts stay constant while names change. A dedicated rename tracker requires semantic parsing, which the heuristics here approximate.
There is no hard cap, but practical performance depends on how different the inputs are. Similar files of several thousand lines compare quickly thanks to prefix/suffix trimming; very large and very different inputs are slower because the underlying problem is harder. Everything runs locally, so the only limit is your device.
When a deletion is immediately followed by an insertion, the tool pairs them as a single modified line and highlights the word-level differences between them. This mirrors how GitHub and other reviewers present edits, and it makes small in-place changes much easier to read than two separate add/remove rows.
You can export an HTML or JSON report and share that file, or copy the unified diff into a ticket or chat. Because everything is generated locally and contains no tracking, the exported report is a clean, self-contained artifact you can attach anywhere.
The input editors use a dark code theme for comfortable reading, and the diff output uses clear, accessible green/red/amber highlighting that meets contrast guidelines. The surrounding interface follows the site’s light theme for consistency across the developer-tools suite.
Churn is the total volume of change — added plus removed plus modified lines. High churn is not inherently bad, but it correlates with review effort and risk. The tool reports churn and factors it into the review health grade so you can size your review appropriately.
Check out each branch, copy the relevant file (or run git show branch:path), and paste the two versions into the panels. The tool will show the branch-to-branch differences exactly as a pull request would, complete with statistics and review insights.
Yes. Because the diff engine and all analysis run client-side, once the page has loaded you can compare and analyze code without a network connection. Nothing is sent anywhere.
You can, though minified single-line code produces a less readable diff. For better results, beautify both versions first (our JSON, CSS, HTML and JS formatters can help), then compare the formatted output so the line and word diff can align meaningfully.
The change summary is a plain-English narrative of the diff: how many lines changed across how many hunks, whether functions were added or removed, whether complexity rose or fell, whether blocks were moved, and whether any security or performance patterns were flagged — a quick orientation before you read the code line by line.
No — and we are transparent about that. The review summary, security scanner and performance scanner are deterministic, rule-based heuristics that run entirely in your browser, with no external model or data sharing. This keeps your code private and the results explainable: every finding maps to a specific, inspectable rule.
A header like @@ -12,6 +12,7 @@ means the change starts at line 12 in the old file and spans 6 lines, and starts at line 12 in the new file and spans 7 lines. The numbers let tools apply the patch to the correct location even if surrounding code has shifted.
Yes. Config files (JSON, YAML, .env, INI, TOML) compare cleanly with the line engine, and JSON config benefits from structural comparison. Enable ignore-whitespace to skip indentation noise and focus on the values that actually changed.
Break it into logical chunks, review each file’s diff separately, and use the change summary and review health grade to triage — start with the files that have the highest churn, complexity increase or security findings. Look at moved blocks first to mentally subtract them from the real change, then read the genuine edits closely.
Yes. The security scanner flags hardcoded secrets, AWS access keys, private-key blocks and credential-like assignments in the added lines. Treat any such finding as urgent: rotate the exposed secret and move it to a secrets manager or environment variable before merging.
Your latest comparison is auto-saved to your browser’s local storage, so if you reload the page you can restore your last session. Because storage is local, your code never leaves your device.
You can upload common source and text files — .txt, .js, .ts, .jsx, .tsx, .json, .xml, .yaml, .yml, .sql, .md, .csv, .html, .css and more. Drag and drop a file onto either panel, or use the upload button. Files are read locally and never transmitted.
By default the diff is exact, so even invisible whitespace differences are reported. Enable ignore-whitespace or trim-lines to hide them. This is useful when comparing code that has been reformatted but is otherwise logically identical.
Yes. Paste two SQL statements or schema definitions to see exactly what changed. The performance scanner will also flag patterns like SELECT * in the added SQL, and the security scanner watches for queries built via string concatenation — useful when reviewing migrations and query changes.
It produces the same kind of result — a Myers-based diff — but in a visual, interactive interface with side-by-side, inline and unified views, word-level highlighting, change statistics and a review layer (security, performance, complexity and a plain-English summary) that the raw command does not provide. It is ideal when you want to review a change without leaving the browser.
No. There are no network requests involved in the comparison or analysis. Everything — parsing, diffing, scanning and report generation — happens in your browser, which is why the tool is safe for sensitive and proprietary code.
Yes, and JSON mode is ideal for it. Paste two JSON API responses, enable structured comparison, and the tool reports exactly which fields were added, removed or changed by path — perfect for spotting breaking changes between API versions.
The interface is keyboard-navigable with visible focus indicators, ARIA labels on controls, and diff colours chosen for sufficient contrast. Screen readers can traverse the controls and content, and the layout is fully responsive for phones, tablets and desktops.
Compare logically related versions of the same file (not unrelated files), keep formatting consistent between the two sides or enable ignore-whitespace, and review the change summary first to orient yourself. Then drill into the security and performance findings, and use the metrics delta to judge whether the change improves or worsens maintainability.
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