Start by clarifying the requirements and constraints, then propose a modular design with a configurable priority list and a rule engine that evaluates each transaction against specific checks. Discuss how to integrate this into the existing pipeline, ensuring backward compatibility and testability, and cover trade-offs like performance and extensibility.
Pro tip: Emphasize configurability and observability: make the priority order easily changeable without code deployment, and log which rules triggered to aid debugging and auditing. This shows you think about production readiness and maintainability.
Ask about expected transaction volume, latency requirements, and whether the priority order should be dynamic or static. Confirm that each transaction should output at most two error codes and that 'OK' means no errors.
Propose a rule-based system where each error code corresponds to a specific validation rule. Use a configurable priority list (e.g., via config file or database) to determine the order of error codes.
For each transaction, evaluate all rules, collect triggered error codes, sort them by the configured priority, and select the top two (or fewer). Return 'OK' if none triggered.
Refactor the existing pipeline to replace the SUSPICIOUS label with the new error codes. Write unit tests for each rule and integration tests for the overall behavior, including priority ordering.
Address performance implications (e.g., evaluating all rules vs. short-circuiting), how to add new error codes, and how to handle changes in priority without redeploying.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Honestly the formatting part felt like a trap at first because it seems trivial but there are real edge cases.
Start by clarifying the requirements: what defines a column, how to handle missing error codes, and whether the output is for a fixed-width console or a file. Then explain that you compute each column's width as the maximum length of its content (including header) and pad each cell with spaces to that width, using left or right alignment as appropriate. Finally, discuss edge cases like truncation, Unicode, and dynamic data.
Pro tip: Mention that you would use a two-pass approach: first collect all rows and compute max widths, then format and output. This avoids buffering issues and ensures correct alignment even with streaming data.
Ask about the expected output format (fixed-width text, console, file), whether columns have fixed or dynamic widths, and how to handle missing or overly long values.
For each column, compute the maximum length of the header and all cell values. This can be done in a single pass if all data is available, or in two passes if streaming.
For each cell, convert to string, then pad with spaces to the computed width. Use left alignment for text and right alignment for numbers, or as specified.
Address missing values (e.g., empty string or placeholder), truncation with ellipsis if a value exceeds a maximum width, and Unicode characters that may have varying display widths.
Join padded cells with a delimiter (e.g., space or pipe) and output rows. Optionally include a separator line between header and data.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.