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  2. Instruction path length - Wikipedia

    en.wikipedia.org/wiki/Instruction_path_length

    The instruction path length of an assembly language program is generally vastly different than the number of source lines of code for that program, because the instruction path length includes only code in the executed control flow for the given input and does not include code that is not relevant for the particular input, or unreachable code.

  3. Average path length - Wikipedia

    en.wikipedia.org/wiki/Average_path_length

    All these models had one thing in common: they all predicted very short average path length. [1] The average path length depends on the system size but does not change drastically with it. Small world network theory predicts that the average path length changes proportionally to log n, where n is the number of nodes in the network.

  4. Longest path problem - Wikipedia

    en.wikipedia.org/wiki/Longest_path_problem

    In graph theory and theoretical computer science, the longest path problem is the problem of finding a simple path of maximum length in a given graph.A path is called simple if it does not have any repeated vertices; the length of a path may either be measured by its number of edges, or (in weighted graphs) by the sum of the weights of its edges.

  5. XPath - Wikipedia

    en.wikipedia.org/wiki/XPath

    [a] Every value is now a sequence (a single atomic value or node is regarded as a sequence of length one). XPath 1.0 node-sets are replaced by node sequences, which may be in any order. To support richer type sets, XPath 2.0 offers a greatly expanded set of functions and operators. XPath 2.0 is in fact a subset of XQuery 1.0.

  6. Closeness centrality - Wikipedia

    en.wikipedia.org/wiki/Closeness_centrality

    The number next to each node is the distance from that node to the square red node as measured by the length of the shortest path. The green edges illustrate one of the two shortest paths between the red square node and the red circle node. The closeness of the red square node is therefore 5/(1+1+1+2+2) = 5/7.

  7. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Find the Shortest Path: Use a shortest path algorithm (e.g., Dijkstra's algorithm, Bellman-Ford algorithm) to find the shortest path from the source node to the sink node in the residual graph. Augment the Flow: Find the minimum capacity along the shortest path. Increase the flow on the edges of the shortest path by this minimum capacity.

  8. Connectivity (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Connectivity_(graph_theory)

    This graph becomes disconnected when the right-most node in the gray area on the left is removed This graph becomes disconnected when the dashed edge is removed.. In mathematics and computer science, connectivity is one of the basic concepts of graph theory: it asks for the minimum number of elements (nodes or edges) that need to be removed to separate the remaining nodes into two or more ...

  9. Betweenness centrality - Wikipedia

    en.wikipedia.org/wiki/Betweenness_centrality

    Percolation centrality is defined for a given node, at a given time, as the proportion of ‘percolated paths’ that go through that node. A ‘percolated path’ is a shortest path between a pair of nodes, where the source node is percolated (e.g., infected). The target node can be percolated or non-percolated, or in a partially percolated state.