The Luhn part itself is fine once you remember the direction matters: start from the rightmost non-check digit and double every second one going left.
Start by clarifying the requirements: the input is a 16-digit string, and the output should be 'VISA' if the Luhn checksum is valid, otherwise 'INVALID_CHECKSUM'. Then, explain the Luhn algorithm step-by-step, emphasizing the doubling of every second digit from the right and the handling of digits greater than 9. Finally, walk through a code implementation, discussing edge cases and potential optimizations.
Pro tip: Mention that you would validate the input format (e.g., exactly 16 digits, numeric) before applying the Luhn algorithm, and consider discussing how this could be extended to other card types or integrated into a payment system.
Confirm that the input is a 16-digit string representing a VISA card number, and the output should be 'VISA' if the checksum is valid, otherwise 'INVALID_CHECKSUM'. Ask if any other validation (e.g., prefix check) is needed.
Describe the steps: starting from the rightmost digit (the check digit), double the value of every second digit. If doubling results in a number greater than 9, subtract 9 (or sum the digits). Sum all digits and check if the total modulo 10 is 0.
Write code (in a language of your choice) that iterates over the digits from right to left, applies the doubling rule, accumulates the sum, and returns 'VISA' if sum % 10 == 0, else 'INVALID_CHECKSUM'.
Provide a valid VISA test number (e.g., 4111111111111111) and an invalid one (e.g., 4111111111111112) to demonstrate correctness. Walk through the algorithm manually for at least one example.
Mention handling non-digit characters, varying lengths (though specified as 16), and potential optimizations like processing digits in a single pass without converting to an array.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
The Mastercard prefix range (51-55) is where people slip up.
Start by clarifying the requirements and edge cases, then design a data-driven solution using a table of network rules (prefixes and lengths). Implement the validation in clear stages: first check the network, then validate the checksum, and finally return the appropriate result.
Pro tip: Mention that you would make the network rules configurable (e.g., via a data structure or external config) to easily add new networks without changing the core logic. Also, discuss the trade-off between hardcoding rules for performance vs. configurability for maintainability.
Ask about the expected input format (string with or without spaces), whether the network detection should be based on prefix only or also length, and how to handle ambiguous cases (e.g., a number that matches multiple networks).
Propose a table (e.g., array of objects or map) where each entry contains the network name, a list of valid prefixes (or prefix ranges), and valid lengths. This makes the solution extensible and easy to read.
Iterate through the rules to find a matching network based on the card number's prefix and length. If no match, return 'UNKNOWN_NETWORK'.
If a network is matched, apply the Luhn algorithm to verify the checksum. If it fails, return 'INVALID_CHECKSUM'.
If both checks pass, return the network name. Also mention how the design allows adding new networks by simply updating the rules table.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the card network rules (prefix ranges and lengths) and the wildcard positions, then for each network count valid completions by checking if the fixed digits match the network's prefix and length constraints, and if so, compute 10^(number of asterisks) as the count. Finally, sort the networks alphabetically and output the counts.
Pro tip: Mention that you would precompute the network rules as a list of (name, length, prefix ranges) and use a trie or simple iteration for efficiency, and note that the count can be huge so you might need to handle big integers or modulo if required.
Ask about the exact card network rules (e.g., Visa, Mastercard, Amex) including prefix ranges and valid lengths, and confirm the input format (e.g., asterisks only replace digits, no other characters).
Represent each network as a set of rules: a list of valid lengths and a list of prefix ranges (e.g., Visa: length 16, prefix 4; Mastercard: length 16, prefix 51-55 or 2221-2720).
For each network, check if the card number's length matches any valid length and if the fixed digits (non-asterisk) are compatible with the network's prefix ranges. If compatible, the number of completions is 10^(number of asterisks).
Collect the counts for each network that has at least one valid completion, sort the network names alphabetically, and output the results in the required format.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the problem: the input is a card number string with exactly one '?' representing a single digit, and exactly one error (either a digit change or adjacent swap) was introduced. Then, systematically generate all possible original numbers by reversing the error model: for each position, try all 10 digits (if it's a digit change) and try swapping adjacent digits (if it's a swap), validate each candidate using Luhn's algorithm and network detection, and collect unique valid cards. Finally, sort the results numerically and output in the required format.
Pro tip: Mention that you would use Luhn's algorithm for validation and a prefix-based network detection (e.g., Visa starts with 4, Mastercard 51-55 or 2221-2720, Amex 34/37, Discover 6011/65). Also, emphasize the importance of deduplication and sorting to handle cases where multiple error models produce the same valid card.
Confirm that the input is a string with exactly one '?' and that exactly one error (digit change or adjacent swap) was introduced. Ask about the expected output format, network detection rules, and whether the original card must pass Luhn validation.
For each position, consider two error types: (1) if the character is a digit, try changing it to each of the other 9 digits; if it's '?', try all 10 digits. (2) For each adjacent pair, try swapping them. This generates a set of candidate numbers.
For each candidate, check if it passes Luhn's algorithm and matches a known card network prefix. If valid, record it along with its network.
Remove duplicates (since different error models might yield the same valid card) and sort the results numerically by the card number.
Output each valid card as '<number>,<NETWORK>' in sorted order. Ensure the network name is in the expected format (e.g., 'VISA', 'MASTERCARD').
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.