# Chapter 35. Glossary

This glossary defines common terms used throughout the igraph documentation.

- attribute: A piece of data associated with a vertex, an edge, or the graph itself. The igraph C library currently supports numeric, string and Boolean attribute values, and provides a means for implementing attribute handlers that support custom types.

- adjacent: Two vertices are called adjacent if there is an edge connecting them. This term describes a vertex-to-vertex relation.

- adjacency list: A data structure that associates a list of neighbours (i.e. adjacent vertices) to each vertex.

- adjacency matrix: A representation of a graph as a square matrix. `A_ij` gives the number of edge endpoints connecting from the `i`th vertex to the `j`th vertex. Conventionally, the diagonal of the adjacency matrix of an undirected graph contains twice the number of self-loops. All igraph functions follow this convention unless noted otherwise.

- biadjacency matrix: Analogous to the adjacency matrix, but used for bipartite graphs. Element `B_ij` gives the number of edges from the `i`th vertex of the first group to the `j`th vertex of the second group.

- bipartite graph: A graph whose vertices can be partitioned into two groups in such a way that connections are present only between members of different groups.

- complete graph: Also called full graph within the context of igraph, a graph in which all pairs of vertices are connected to each other.

- connected graph: A connected graph consists of a single component, in which any vertex is reachable from any other. In igraph, the null graph is not considered connected, as it has not one, but zero components.

- edge: A connection between two vertices, also called a link. In igraph, edges are referred to by integer indices called edge IDs.

- finalizer stack: A global stack used internally by igraph to keep track of currently allocated objects and their destructors, so that they can be automatically destroyed in case of an error.

- game: Within igraph, this term is used for stochastic graph generators, i.e. functions that sample from random graph models.

- graph or network: A set of vertices with connections between them. In igraph, graphs may carry associated data in the form of vertex, edge or graph attributes.

- incident: An edge is called incident to the vertices that are its endpoints. This term describes a vertex-to-edge relation.

- incidence list: A data structure that associates a list of incident edges to each vertex.

- incidence matrix: A matrix describing the incidence relation between vertices (rows) and edges (columns).

- membership vector: Membership vectors are a means of encoding a partitioning of items, usually vertices, into several groups. The `i`th element of the vector gives an integer identifier of the group the `i`th vertex belongs to. Membership vectors are typically used to describe a vertex clustering obtained through community detection, or by identifying the connected components of a graph.

- multi-edges or parallel edges: More than one edge connecting the same two vertices. In a directed graph, `a -> b, a -> b` are considered parallel edges, but `a -> b, a <- b` are not.

- null graph: A graph with no vertices (and no edges).

- self-loop, self-edge, or simply loop: An edge that connects a vertex to itself.

- simple graph: A graph that does not have self-loops or multi-edges.

- singleton graph: A graph having a single vertex. This term usually refers to a single vertex with no edges, but note that self-loops may in principle be present.

- vertex: Graphs consist of vertices, also called nodes, that are connected to each other. In igraph, vertices are referred to by integer indices called vertex IDs.