In software development, the efficiency and accuracy of code completion systems are crucial for productivity and codebase discovery. From simple spell checkers to advanced AI-powered tools, there are more ways to complete your code than ever. This results in an explosion in the number of possible valid proposals, especially when working with today’s increasingly large codebases. Over the years, a lot of effort has been put into developing effective ranking systems to prioritise proposals with more potential. Yet developers still often struggle with an overwhelming number of suggestions, leading to reduced productivity and increased cognitive load.

In this paper, instead of just performing completion by name, we propose \emph{CoCoCoLa} — an alternative approach to give back the control over the presented proposals to the developer. By investigating the recorded code completion events, frequencies of desirable code elements’ properties were calculated to identify useful control factors. To avoid adding further complexity to the completion process, we propose a simple language, defined within the boundary of a valid identifier of the 50+ most popular software languages in 2024. This language allows developers to specify and filter for desired properties of the proposals.