tezvyn:

Quantifying the cost of a missing component

AI-drafted, machine-checkedSource: interviewadvanced
WHAT IT TESTS

Whether you justify investment with evidence of waste.

OUTLINE

Scan repos for duplicate hand-rolled tables, count implementations and lines, estimate redundant build and maintenance hours plus defect rates.

WHAT THIS TESTS The interviewer wants evidence-based prioritization: can you measure the waste a missing component causes and turn it into a dollar case for building it, using actual code analysis rather than a hunch.

A GOOD ANSWER COVERS The cost of absence is the redundant work teams do because the component does not exist. Quantify it with code analysis. Scan every repository for table-like implementations: AST or pattern searches for table elements, grid libraries, and hand-rolled table components, deduplicated to count how many distinct reinventions exist. Measure the lines of code and complexity tied up in each, which proxies build and maintenance effort. Estimate redundant build hours (number of reimplementations times average build time) and ongoing maintenance hours. Layer in quality cost: accessibility audits on these ad hoc tables usually surface keyboard and screen-reader defects, and bug trackers show table-related issues, each carrying a fix cost. Add the consistency cost of users seeing many different table behaviors. Convert build, maintenance, and defect costs to dollars to size the cost of absence, then compare it to the build cost of one well-made shared component to show payback.

COMMON WRONG ANSWERS Arguing from intuition that everyone needs a table, with no duplication count. Counting only build cost and ignoring maintenance and defects. No accessibility angle, missing a large hidden cost. Failing to compare against the cost of building the shared component.

LIKELY FOLLOW-UPS How do you detect a hand-rolled table in code? How do you estimate per-implementation build time? How does this compare to the cost of absence for a smaller component?

ONE CONCRETE EXAMPLE A scan finds twenty-three distinct table implementations across eighteen repos, totaling thousands of lines and a dozen accessibility defects. Estimating redundant build plus maintenance plus defect-fix cost yields a figure far above the cost of building one shared Data Table, making the investment an easy yes.

Read the original → netguru.com

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