Quick Checklists

Validate XML before conversion (single root, matching tags, proper nesting)
Validate JSON (double quotes, no trailing commas, finite numbers only)
Decide how to represent attributes (e.g., use an @ prefix)
Normalize dates to ISO 8601 for consistency
Confirm encoding is UTF-8 when sharing data
Keep naming consistent across systems (camelCase or snake_case)
Document mapping rules so consumers can parse reliably

Common Recipes

Convert attributes to JSON properties

<person id="42">
  <name>Alex</name>
</person>

{
  "person": {
    "@id": "42",
    "name": "Alex"
  }
}

Represent lists consistently

<tags>
  <tag>blue</tag>
  <tag>green</tag>
</tags>

{
  "tags": {
    "tag": ["blue", "green"]
  }
}

Normalize dates and timestamps

<event>
  <timestamp>2026-02-13T08:30:00Z</timestamp>
</event>

{
  "event": {
    "timestamp": "2026-02-13T08:30:00Z"
  }
}

Conversion Strategy

If you’re migrating systems, define a clear mapping specification and test it with real-world data. Identify edge cases like empty fields, optional attributes, and mixed content before converting large datasets.

Start with a small representative sample
Validate output against schemas or contracts
Roll out changes in stages to reduce risk

XML Tips

Use namespaces to avoid name collisions across schemas
Prefer elements for data, attributes for metadata
Escape special characters like & and <
Keep a single root element for valid documents

JSON Tips

Use consistent casing for keys (camelCase or snake_case)
Keep numbers as numbers for downstream calculations
Validate with JSON Schema for APIs and configs
Avoid NaN and Infinity (JSON only supports finite numbers)

Performance Tips

For large payloads, process in chunks where possible
Use pretty formatting only when needed for readability
Validate early to catch errors before conversion

Resources