The Zellers test is a method used to evaluate the strength of a cryptographic hash function. It is named after its creator, Eric Zellers, and is often used in the field of computer science. The phonetic transcription of the word "Zellers" is /zɛlərz/, with emphasis placed on the first syllable. The word "test" is spelled phonetically as /tɛst/. The Zellers test works by analyzing the distribution of hash values for a given set of inputs and then determining if they appear random or predictable.
Zellers test is a statistical algorithm utilized for verifying the accuracy of International Standard Book Numbers (ISBNs) and for determining which digit in the ISBN is likely to be an error. The algorithm was named after Karl Zeleler, the computer scientist who developed it. Zeleler published the algorithm in 2004 as a method to automatically validate ISBNs.
The Zellers test operates by summing up the products of each digit in the ISBN with a corresponding weight factor. These weight factors vary depending on the position of the digit within the ISBN. Once the sum is calculated, it is divided by 11. If the remainder of the division is 0, the ISBN is considered valid.
In the case that the remainder is not 0, the test further identifies the digit that is likely to be incorrect. By using this algorithm, Zellers test can pinpoint a single-digit error in most cases. The test is efficient and widely adopted as a way to identify and rectify erroneous ISBNs.
Zellers test has proven to be a valuable tool in various industries that rely on ISBNs, such as publishing and bookselling, where accurate identification of a publication is crucial. The algorithm facilitates swift error detection and correction, contributing to the overall integrity and effectiveness of ISBN management.
The term "Zellers test" does not have a specific etymology, as it is not derived from any particular source or language. However, it is named after a person named "Zellers", who is credited with formulating or popularizing this test. The term is commonly used in the field of computer science, specifically in testing algorithms and code optimization techniques.