  Hop-constrained s-t simple path (HC-s-t path) enumeration is a fundamental
problem in graph analysis. Existing solutions for this problem focus on
optimizing the processing performance of a single query. However, in practice,
it is more often that multiple HC-s-t path queries are issued simultaneously
and processed as a batch. Therefore, we study the problem of batch HC-s-t path
query processing in this paper and aim to compute the results of all queries
concurrently and efficiently as a batch. To achieve this goal, we first propose
the concept of HC-s path query which can precisely characterize the common
computation among different queries.We then devise a two-phase HC-s path query
detection algorithm to identify the common HC-s path queries for the given
HC-s-t path queries. Based on the detected HC-s path queries, we further devise
an efficient HC-s-t path enumeration algorithm in which the common computation
represented by HC-s path queries are effectively shared. We conduct extensive
experiments on real-world graphs and the experimental results demonstrate that
our proposed algorithm is efficient and scalable regarding processing multiple
HC-s-t path queries in large graphs at billion-scale.
