Infor LN Regression Test Effort Calculator
Testing is where most Infor LN upgrades and Baan to LN migrations run late. This calculator turns scenario count, cycles, defect rate and team size into hours, person days and elapsed weeks, so you can have a realistic conversation about schedule and staffing.
Your numbers
Count business scenarios, not every screen.
Include data setup and evidence capture.
Share of scenarios that raise a defect on first run.
Your results
A planning estimate from the inputs you give. It excludes test environment build, data preparation, training and fix development time, which are often larger than execution.
Elapsed weeks vs number of testers
Sweeps Testers available from 1 to 20, holding your other inputs fixed.
Upgrade impact analysis
Optional: discuss how to find which customizations and reports an LN change affects.
Optional. The tool and every export work without this. No spam.
How to use the calculator
Count the business scenarios you must prove, such as release a production order, receive a purchase order or post a sales invoice, not every session. Estimate how long a scenario takes including data setup, set the number of cycles and a first-cycle defect rate from similar past projects, and enter the testers you can really free from their day jobs. The chart shows how elapsed weeks drop as testers are added, and where adding more people stops helping.
The formulas
Execution hours are scenarios times minutes per scenario, divided by 60, times cycles. Defects equal scenarios times the defect rate. Defect hours are defects times retest and triage minutes per defect, divided by 60, times cycles as a conservative allowance. Total hours add the two, person days divide by productive hours per day, and elapsed days divide by testers. Weeks divide by five. Real schedules also depend on fix turnaround and environment availability.
- Productive hours per day are usually 4 to 6, not 8
- Later cycles should have fewer defects, so this is an upper estimate
- Testers who are also doing their day job lower the real rate
Reading results and common mistakes
If elapsed weeks look short, check your assumptions about tester availability and fix turnaround before trusting the number. Common mistakes are counting screens instead of scenarios, ignoring integration and interface tests, assuming one cycle will be enough, and forgetting that business users need training on the new environment. For an upgrade, include scenarios for every customization, DAL rule and report, since they are the most likely to break. Re-run the calculator after each cycle with actual figures.
Frequently Asked Questions
How many test cycles should an LN upgrade have?
Three is a common baseline: a first pass to find defects, a retest after fixes, and a final confirmation with business users. Complex customization or integration usually needs more. Plan for at least one cycle more than you hope.
What is a realistic defect rate?
It depends heavily on customization and data quality. A lightly customized upgrade may see a single-digit percentage and a heavily customized or migrated one a lot more. Use your own history, and update after the first cycle.
Does this include test automation?
No. Automation changes the shape of the effort: more build time upfront and less execution per cycle. If you automate regression, reduce minutes per scenario and add a separate build estimate.
How do I estimate scenarios in scope?
List business processes end to end, then add one scenario for each customization, interface, key report and role. Group trivial screens into the process they belong to so you do not inflate the count.
If you want to cut test effort by finding which customizations and reports an upgrade actually touches, we can discuss an on-prem assistant for impact analysis.
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