Normalize inputs
Check record keys, time zones, crew size, trip segments, and required timestamps before a rule is applied.
CASE STUDY 04 / RESEARCH TOOLS
A traceable rules workflow with a separate check of the saved outputs.
How can configured duty-limit rules be applied consistently and checked against the source records?
The screening workflow evaluates time-zone, crew-size, and multi-segment trip conditions. A separate validator recomputes selected expected fields and compares them with the exported audit results.
THE STORY IN PLAIN LANGUAGE
The workflow preserves the decisions behind a classification, then checks saved outputs through a separate reconciliation step. It demonstrates how data-quality logic, explicit boundaries, and an audit trail make a rules process reviewable.
The stack follows the analytical task: prepare the data, fit or apply the method, check the result, and communicate the output.
See how the libraries connect to the wider portfolio →THE PROJECT, STEP BY STEP
Check record keys, time zones, crew size, trip segments, and required timestamps before a rule is applied.
Write intermediate audit fields with each screening result, separating clear outcomes from cases that need human review.
Compare saved outputs with recomputed values, record keys, and duplicate checks instead of trusting a successful export alone.
THE TECHNICAL CASE
A reliable rules workflow makes every decision traceable. The engineering value here is the separation of screening logic, audit fields, and an independent reconciliation of exported results.
The workflow handles time zones, crew-size branches, multi-segment trips, and acclimatization assumptions. Required keys and timestamps determine whether a record can be evaluated or needs review.
Intermediate fields explain how a final classification was reached. A flag without the values and rule branch that produced it is difficult to investigate, especially near a threshold or with incomplete timing information.
A separate script recomputes selected expected fields and compares them with saved outputs. This catches discrepancies in the delivered workbook rather than assuming that a script finishing successfully proves correctness.
Record identity matters alongside numeric agreement. Reconciliation checks should establish whether the output contains the expected keys and whether duplicate records could change the reported counts.
Source record → normalize → evaluate branch → retain audit fields → independently reconcile
Agreement between an implementation and configured rules is a software-validation result. It does not independently certify the rules or their regulatory applicability.
EXPLORE THE METHOD
This teaching example uses an invented 12-hour threshold. It is not an aviation duty-limit rule and must not be used for operational decisions.
QUALITY OF THE EVIDENCE
Exercise a value just below, exactly at, and just above a configured threshold, and state the inequality used.
Send unevaluable cases to review. Missing information should not silently become a pass.
Compare saved outputs with a separately recomputed expectation and retain mismatch fields for investigation.
Reviewed workbook summaries contain 3,198 checked records and zero mismatches in the checked fields; the portfolio does not rerun the original pipeline.
FOR THE TECHNICAL CONVERSATION
A strong engineering discussion is how to prevent a validator from reproducing the same bug as the primary implementation, and how to retain enough audit context to explain an exception months later.
WHAT IT DEMONSTRATES
Saved validation summaries report 3,198 flight records checked and zero mismatches in the checked outputs.