Programmers spend significantly more time trying to comprehend existing code than writing new code. They gain an understanding of the code by navigating the code base in an IDE, by reading documentation online, and by browsing code repositories on websites such as GitHub. To create rich experiences for programming languages across those various media is a large effort for developers of programming languages. This effort might be worthwhile for popular languages, but for new or experimental languages the required effort is often too large. Solutions to reduce this effort of implementing an IDE exist,such as LSP, but to reduce the effort in other places outside IDEs, we introduce the Codex metadata format, which separates language-specific generation of code metadata from its language-agnostic presentation. To demonstrate this approach by implementing four language-specific metadata generators (based on LSP, CTAGS, TextMate and Elaine) and two language-agnostic presentations (PDF documents and a code viewer websites) of code and metadata. To demonstrate different kinds of code metadata, we implemented four code exploration services: syntax colouring, code navigation, structure outline, and diagnostic messages. We show that with the Codex metadata format, we can decouple the metadata generators from the presentations.

Multi-agent pathfinding (MAPF) is the process of finding collision-free paths for multiple agents. MAPF can be extended by grouping agents into teams. In a team, agents need to be assigned (or matched) to one of the team's goals such that the sum of individual cost} is minimised. This extension is called MAPF with matching (MAPFM). M* is a complete and optimal algorithm to solve MAPF problems. In this paper, two strategies are proposed which allow M* to solve MAPFM problems. These strategies are called inmatching and prematching. It is shown that prematching is generally preferable to inmatching, the benefits of different optimisations for M* are compared, and it is shown that the performance of M* performs very comparably to other A*-derived algorithms.