Overriding instance properties in Figma - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Instance Property Overrides

In Figma, when you override a property of an instance, what happens to the original component's property?

A The instance loses the ability to override that property again.

B The instance automatically updates to match any changes in the original component's property.

C The original component's property is permanently changed for all instances.

D The instance keeps its own value, ignoring changes to the original component's property.

💡 Hint

Think about how overrides allow customization without affecting the master component.

When you override a property in an instance, that instance uses its own value for that property. Changes to the original component's property won't affect the overridden property in that instance.

🎯 Scenario

intermediate

Overriding Text in Multiple Instances

You have a button component with default text 'Submit'. You create three instances and override the text in each to 'Save', 'Send', and 'Upload'. Later, you change the default text in the main component to 'Confirm'. What text will appear in each instance?

A Instances show 'Save', 'Send', and 'Upload' as overridden; none change to 'Confirm'.

B All instances revert to 'Submit' ignoring overrides.

C Only the instance with no override changes to 'Confirm'; others keep their text.

D All instances show 'Confirm' because the main component changed.

💡 Hint

Overrides protect instance properties from changes in the main component.

Since all three instances have overridden the text, they keep their custom text. Changes to the main component's text do not affect overridden properties.

❓ dax_lod_result

advanced

Calculating Overridden Property Counts

Imagine a dataset of component instances with a column 'IsOverridden' (TRUE/FALSE). You want to calculate the percentage of instances that have overridden properties.

Which DAX measure correctly calculates this percentage?

A Override Percentage = DIVIDE(CALCULATE(COUNTROWS(Instances), Instances[IsOverridden] = TRUE()), COUNTROWS(Instances), 0)

B Override Percentage = COUNTROWS(FILTER(Instances, Instances[IsOverridden] = TRUE())) / COUNTROWS(Instances)

C Override Percentage = CALCULATE(COUNTROWS(Instances), Instances[IsOverridden] = TRUE()) * 100

D Override Percentage = COUNTROWS(Instances) / COUNTROWS(FILTER(Instances, Instances[IsOverridden] = TRUE()))

💡 Hint

Use DIVIDE to avoid division by zero errors and CALCULATE to filter rows.

Option A uses CALCULATE to count overridden instances, divides by total instances, and uses DIVIDE to safely handle division.

🔧 Formula Fix

advanced

Fixing Incorrect Override Count Measure

A DAX measure to count overridden instances is written as:

OverrideCount = COUNTROWS(FILTER(Instances, Instances[IsOverridden] == TRUE()))

Why does this measure cause an error?

A The column 'IsOverridden' must be aggregated before filtering.

B COUNTROWS cannot be used with FILTER in DAX.

C The '==' operator is invalid in DAX; it should be a single '='.

D FILTER requires a table, but Instances is a column.

💡 Hint

Check the syntax for comparison operators in DAX.

DAX uses a single '=' for comparison, not '=='. Using '==' causes a syntax error.

❓ visualization

expert

Designing a Dashboard to Show Override Impact

You want to create a dashboard that shows how many instances have overridden properties and how those overrides affect component usage over time.

Which visualization setup best communicates this information?

A A scatter plot with instance IDs on X-axis and override status on Y-axis, colored by component type.

B A stacked bar chart showing counts of overridden vs non-overridden instances by month, plus a line chart showing total instances over time.

C A pie chart showing the percentage of overridden instances, with a table listing all instance names.

D A single KPI card showing total number of instances without any breakdown.

💡 Hint

Think about combining categorical and time series data for clear insights.

Option B uses a stacked bar chart to compare overridden vs non-overridden counts over time, and a line chart to show overall trends, making it easy to see impact and usage.