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-debugging instead
• User wants to optimize performance — use performance profiling skills
• User wants to generate tests — use matlab-testing 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:

matlab
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+):

matlab
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

matlab
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

matlab
[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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