In experimental studies on query languages, subjects are required to write queries using di!erent query languages. User query performance is usually measured by query accuracy. There is no clearly de"ned objective method of applying "ndings to other queries. This study examines the suitability of using a software metric based on lines of code to estimate user query accuracy. Lines of code have been measured in various ways, such as physical source code lines, logical source code lines or compiled bytes. A method of counting lines of code for database queries is proposed and applied to two query languages. The new method counts Boolean conditions as well as other statements. The relationship between lines of code and user query accuracy was examined with regression models. The results show that lines of code can explain a high percentage of the variance in accuracy, with R'0.8 for the standard relational model query language SQL, and R'0.9 for the entity relationship model query language KQL. The common assumption that more lines of code will lead to lower accuracy is only partly validated. The "ndings show a nonlinear relationship, with a possible recovery in accuracy for queries with many lines of code. The results indicate that lines of code can be usefully applied in the study of query languages.