matlab-modernize-code

name: matlab-modernize-code description: > Modernize deprecated MATLAB functions and patterns. Use when check_matlab_code or checkcode reports "not recommended" or "to be removed" warnings, when migrating legacy code, or when replacing deprecated APIs (trainNetwork, csvread, xlsread, datenum, eval, subplot, guide, optimset, wavread, svmtrain, uicontrol) with current equivalents. license: MathWorks BSD-3-Clause metadata: author: MathWorks version: "1.0"

Code Modernization

Replace deprecated MATLAB functions and anti-patterns with modern equivalents. This skill is the resolver — check_matlab_code is the detector.

When to Use

• check_matlab_code or checkcode returns "not recommended" or "to be removed" warnings
• User asks to modernize, migrate, or update old MATLAB code
• Code uses functions listed in the quick reference table below
• After static analysis reveals deprecated API usage
• Writing new code in a domain that has known deprecated patterns

When NOT to Use

• Reviewing code quality broadly — use matlab-review-code (which may then trigger this skill)
• Debugging runtime errors — use matlab-debugging
• Performance profiling — use performance skills (though anti-patterns below overlap)

Quick Reference: Top Deprecated Functions

Critical Anti-Patterns

Never use these in new code:

Modern Design Patterns

Prefer these in all new code:

Table-Based Workflows

data = readtable('sensors.csv');
data.Timestamp = datetime(data.Timestamp);
data.Status = categorical(data.Status);
recentData = data(data.Timestamp > datetime('today') - days(7), :);
summary = groupsummary(recentData, 'SensorID', 'mean', 'Value');

String Arrays (not char arrays)

name = "John";                        % not 'John'
names = ["John", "Jane", "Bob"];      % not {'John','Jane','Bob'}
fullName = firstName + " " + lastName; % not [first,' ',last]
idx = contains(names, "Jo");          % not cellfun + strfind

Arguments Block (not nargin/varargin)

function result = processData(data, options)
    arguments
        data (:,:) double
        options.Method (1,1) string {mustBeMember(options.Method, ["fast","accurate"])} = "fast"
        options.Verbose (1,1) logical = false
    end
end

Vectorization (not loops)

% Instead of: for i=1:n, V(i) = pi/12*(D(i)^2)*H(i); end
V = pi/12 * (D.^2) .* H;

% Instead of: loop with if
Vgood = V(D >= 0);   % logical indexing

Preallocation

result = zeros(1, n);     % numeric
C = cell(1, n);           % cell array
S(n) = struct('f1', []);  % struct array

Key Migrations

File I/O: csvread/xlsread → readmatrix/readtable

% Old                          → Modern
M = csvread('data.csv');       % M = readmatrix('data.csv');
M = dlmread('data.txt','\t'); % M = readmatrix('data.txt','Delimiter','\t');
[n,t,r] = xlsread('f.xlsx');  % T = readtable('f.xlsx');
csvwrite('out.csv', M);       % writematrix(M, 'out.csv');
xlswrite('out.xlsx', data);   % writetable(T, 'out.xlsx');

Deep Learning: trainNetwork → trainnet

% Old: classificationLayer specifies loss implicitly
net = trainNetwork(X, Y, layers, options);

% Modern: specify loss explicitly, no classificationLayer needed
net = trainnet(X, Y, layers, "crossentropy", options);

% Prediction
scores = minibatchpredict(net, XTest);
YPred = scores2label(scores, classNames);

eval → Dynamic Field Names / Function Handles

% Old: eval([varName ' = 42;']);
s.(varName) = 42;

% Old: result = eval(['process_' method '(x)']);
handlers.fast = @processFast;
handlers.slow = @processSlow;
result = handlers.(method)(x);

References

Load these when working in a specific domain:

Conventions

• Always run check_matlab_code first — let static analysis find deprecated usage
• After checkcode, scan the source for patterns checkcode misses: subplot (not flagged), str2num (sometimes not flagged), global variables, growing arrays may only warn about size change
• Fix deprecated patterns before other code quality issues
• When writing new code, use the modern pattern from the start — don't write deprecated code and fix it later
• For functions marked "Removed" — they will cause immediate errors, not just warnings
• When migrating, test the modern replacement against the old behavior to confirm equivalence
• Consult the domain-specific reference file for detailed migration patterns with code examples

Copyright 2026 The MathWorks, Inc.