Code Modernization

Replace removed or discouraged MATLAB functions and anti-patterns with modern equivalents. This skill is the resolver — the MCP tool check_matlab_code (MATLAB's Code Analyzer) is the detector.

Terms used in this skill:

• Removed — the function is no longer in MATLAB; calling it errors.
• Discouraged — the function still works, but a better API exists. It may or may not be slated for removal in a future release.

When to Use

• check_matlab_code reports a lifecycle diagnostic — any of these three

wordings, matched case-insensitively (STRMATCH is not recommended is the same signal as the lowercase form):

• 'X' is not recommended... (severity: info)
• 'X' will be removed in a future release... (severity: warning)
• 'X' has been removed... (severity: error — the code errors today)
• Code uses a discouraged pattern Code Analyzer does not flag — e.g. containers.Map, bsxfun, str2num, eval, clear all — scan the source, not just the diagnostics (see Conventions)
• User asks to modernize, migrate, or update old MATLAB code
• Code uses functions listed in the quick reference table below
• After static analysis reveals removed or discouraged API usage
• Writing new code in a domain that has known removed or discouraged patterns

When NOT to Use

This skill swaps removed or discouraged APIs for modern equivalents. It does not:

• Review code quality broadly
• Debug runtime behavior (removed-function errors excepted — those are modernization fixes)
• Optimize already-correct code for speed → hand off to matlab-optimize-performance
• Write or migrate function input/output validation (arguments blocks, inputParser/validateattributes → mustBe* validators, repeating args, name-value forwarding) → hand off to matlab-validate-function-arguments

Quick Reference: Removed, Discouraged & Anti-Patterns

`datestr` nuance: datestr's job was to format a date as text, so its modern replacement is string(dt) / char(dt) or setting dt.Format — not a bare datetime(...) call. Use datetime to replace datenum/now (the numeric/serial-date path). Neither is removed; both are Code Analyzer "not recommended" as of R2022b.

>

``matlab s = datestr(t, 'yyyy-mm-dd HH:MM:SS'); % old s = string(t, 'yyyy-MM-dd HH:mm:ss'); % new — note the specifiers change: % datetime uses MM=month, mm=minute (datestr had mm=month, MM=minute) ``

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

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");

eval → Structured Alternatives

Avoid eval/evalc/evalin: the text isn't compiled (slower), can silently overwrite workspace variables, and is hard to read/debug. Match the intent to a construct — see references/core-functions-guidance.md for the full set (sequential names, sprintf filenames, try/catch).

% Old: eval([varName ' = 42;']);          -> dynamic field name
s.(varName) = 42;

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

% Old: for n=1:10, eval(['A' int2str(n) '=magic(n);']); end  -> index a cell
A = cell(10,1);
for n = 1:10, A{n} = magic(n); end

References

Load these when working in a specific domain:

Conventions

• Always run check_matlab_code first — let static analysis find removed or discouraged usage
• After running it, scan the source for patterns the Code Analyzer may under-flag: str2num (framed only as a perf tip); containers.Map (see next point).
• *`containers.Map` is not flagged by `check_matlab_code`. A plain script using it returns zero diagnostics; a `containers.Map` property default* surfaces only a handle-default-sharing warning ("all instances share the same object data"). The detect-first workflow will not find this migration — treat any containers.Map usage, and that handle-sharing warning on a property, as a containers.Map→dictionary trigger.
• *`subplot` is not deprecated or discouraged. It is fully supported and is never flagged by `check_matlab_code`. `tiledlayout`/`nexttile` is a preferred alternative for new code, not a required migration* — do not tell the user to replace working subplot code.
• Fix removed or discouraged patterns before other code quality issues
• When writing new code, use the modern pattern from the start — don't write legacy code and fix it later
• A 'X' has been removed diagnostic (severity error) means the function errors today — treat it as a break-fix modernization, ahead of "not recommended" (info) and "will be removed" (warning) cases
• When migrating, test the modern replacement against the old behavior to confirm equivalence
• Legacy `.m` files are often Windows-1252 encoded. After an edit, verify non-ASCII characters (°, µ, ±) survived — a diff showing an unrelated one-line change on a comment or string is usually a re-encoded byte, not your edit.
• Consult the domain-specific reference file for detailed migration patterns with code examples

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