Code Review

Systematically review MATLAB code for quality, correctness, performance, and adherence to MathWorks coding conventions using static analysis and manual inspection patterns.

When to Use

• User asks to review, audit, or improve code quality
• User wants to check adherence to MathWorks coding standards
• Preparing code for handoff, publication, or open-source release
• After a significant implementation — verify before committing
• User reports "code smells" or asks for cleanup suggestions

When NOT to Use

• User wants to debug a runtime error — use matlab-debug-code instead
• User wants to optimize performance — use performance profiling skills
• User wants to generate tests — use matlab-write-tests instead

Workflow

1. Run static analysis — Use check_matlab_code MCP tool on all target files
2. Load coding standards — Read the matlab_coding_guidelines MCP resource
3. Check naming — Verify functions, classes, variables, and files follow conventions
4. Review function signatures — Arguments blocks, input/output counts, name-value patterns
5. Assess structure — Function length, nesting depth, complexity
6. Check patterns — Vectorization, preallocation, modern API usage
7. Summarize — Report findings by severity: errors > warnings > suggestions

Step 1: Static Analysis

Use the check_matlab_code MCP tool on each file. Then inspect results programmatically:

info = checkcode("src/computeArea.m", "-struct");
for k = 1:numel(info)
    fprintf('Line %d (col %d-%d): %s\n', ...
        info(k).line, info(k).column(1), info(k).column(end), info(k).message);
end

For directory-wide analysis (R2022b+):

issues = codeIssues("src");
disp(issues.Issues);

Step 2: Load Coding Standards

Read the matlab_coding_guidelines MCP resource to get the authoritative MathWorks coding standards. Use these as the baseline for all naming, formatting, and structural checks.

Review Checklist

Naming

Element	Convention	Example
Functions	lowerCamelCase, verb phrase	computeArea, loadData
Classes	PascalCase	SensorReader, DataProcessor
Variables	lowerCamelCase, descriptive	sampleRate not sr
Constants	UPPER_SNAKE or Constant property	MAX_ITERATIONS
Test files	t prefix	tComputeArea.m
App files	PascalCase	DashboardApp.m
File = function	File name matches primary function	computeArea.m → function computeArea

Function Quality

Check	Standard	Severity
Input count	Max 6 positional inputs	Warning
Output count	Max 4 outputs	Warning
Validation	arguments block present	Warning
Name-value args	options.Name pattern (not varargin)	Suggestion
Length	Flag if >50 lines	Suggestion
Nesting	Flag if >3 levels deep	Warning
end keyword	All functions terminated with end	Warning
Help text	H1 line present for public functions	Suggestion

Code Patterns

Check	Modern	Legacy (flag it)
Multi-panel figures	tiledlayout/nexttile	subplot
Date/time	datetime	datenum/datestr
Strings	string type	char arrays for text
Vectorization	.*, ./, logical indexing	Loops over elements
Preallocation	zeros(n,1) before loop	Growing arrays in loops
Data containers	table/timetable	Raw matrices for named data
Dynamic eval	Direct function calls	eval, evalin, assignin

High-Severity Flags

These should always be reported as errors:

• Use of eval, assignin, or evalin — security and maintainability risk
• Growing arrays inside loops without preallocation — performance
• Shadowing built-in functions — sum = 5 shadows sum()
• Missing arguments block in public-facing functions
• Hardcoded file paths with backslashes

What checkcode Misses

check_matlab_code does NOT catch all issues. After running static analysis, always scan the source code for these common problems that require visual inspection:

• subplot usage — not flagged by checkcode, but should use tiledlayout/nexttile
• Shadowed builtin variables — sum = 0 shadows sum(), checkcode may not flag it
• Deep nesting (>3 levels) — checkcode does not measure nesting depth
• Hardcoded backslash paths — checkcode flags unused variables but not path style
• Magic numbers — unlabeled constants in code (e.g., if length(x) > 10)
• Missing H1 help text — checkcode does not require help text

Do not skip Steps 3-6 of the workflow just because checkcode returns few results.

Patterns

Complexity Assessment

function complexity = assessComplexity(filePath)
%assessComplexity Estimate cyclomatic complexity of a MATLAB function.

    arguments
        filePath (1,1) string {mustBeFile}
    end

    code = fileread(filePath);
    branchKeywords = ["if " "elseif " "case " "while " "for " "catch "];
    complexity = 1;
    for kw = branchKeywords
        complexity = complexity + numel(strfind(code, kw));
    end
end

Check Toolbox Dependencies

[files, products] = matlab.codetools.requiredFilesAndProducts('src/myFunction.m');
fprintf('Required products:\n');
for k = 1:numel(products)
    fprintf('  %s (ID: %d)\n', products(k).Name, products(k).ProductNumber);
end

Review Report Format

Present findings in this format:

## Code Review: computeArea.m

### Static Analysis (checkcode)
- 2 warnings, 0 errors

### Naming ✓
- [x] Function: lowerCamelCase
- [x] Variables: descriptive
- [x] File name matches function

### Structure
- [x] arguments block present
- [x] Function under 50 lines
- [ ] ⚠ Nesting depth reaches 4 levels (line 32)

### Patterns
- [x] Vectorized
- [x] Modern graphics API
- [ ] ⚠ Uses datenum (line 18) — migrate to datetime

### Suggestions
1. Extract nested logic at line 32 into a local function
2. Replace datenum with datetime for date handling

Conventions

• Always run check_matlab_code as the first step — it catches issues automatically
• Load matlab_coding_guidelines for the authoritative standard
• Report findings by severity: errors (must fix) > warnings (should fix) > suggestions (nice to have)
• Flag any use of eval, assignin, or evalin as high-severity
• Check requiredFilesAndProducts to verify toolbox dependencies are documented
• Verify every public function has an H1 help text line
• Use codeIssues for directory-wide analysis (R2022b+)
• Do not suggest changes that alter behavior — review is read-only assessment
• For deprecated API migration details, use the matlab-modernize-code skill

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