This paper presents a comprehensive survey of 76 binary similarity and distance measures used over the last century. Binary similarity and distance measures are essential in pattern analysis tasks such as classification and clustering. The paper collects and analyzes these measures, revealing their relationships through hierarchical clustering. The study shows that many of these measures are closely related, with some being more similar than others. The paper defines the 76 measures and groups them based on their similarity. The results show that some measures are more similar to each other than others, with some measures being grouped together based on their properties. The paper also discusses the inclusion or exclusion of negative matches in these measures, and how this affects their performance. The paper concludes that the relationships between these measures can help researchers select more accurate measures for binary data analysis in various domains.This paper presents a comprehensive survey of 76 binary similarity and distance measures used over the last century. Binary similarity and distance measures are essential in pattern analysis tasks such as classification and clustering. The paper collects and analyzes these measures, revealing their relationships through hierarchical clustering. The study shows that many of these measures are closely related, with some being more similar than others. The paper defines the 76 measures and groups them based on their similarity. The results show that some measures are more similar to each other than others, with some measures being grouped together based on their properties. The paper also discusses the inclusion or exclusion of negative matches in these measures, and how this affects their performance. The paper concludes that the relationships between these measures can help researchers select more accurate measures for binary data analysis in various domains.