  The Invertible Bloom Lookup Table (IBLT) is a probabilistic concise data
structure for set representation that supports a listing operation as the
recovery of the elements in the represented set. Its applications can be found
in network synchronization and traffic monitoring as well as in
error-correction codes. IBLT can list its elements with probability affected by
the size of the allocated memory and the size of the represented set, such that
it can fail with small probability even for relatively small sets. While
previous works only studied the failure probability of IBLT, this work
initiates the worst case analysis of IBLT that guarantees successful listing
for all sets of a certain size. The worst case study is important since the
failure of IBLT imposes high overhead. We describe a novel approach that
guarantees successful listing when the set satisfies a tunable upper bound on
its size. To allow that, we develop multiple constructions that are based on
various coding techniques such as stopping sets and the stopping redundancy of
error-correcting codes, Steiner systems, and covering arrays as well as new
methodologies we develop. We analyze the sizes of IBLTs with listing guarantees
obtained by the various methods as well as their mapping memory consumption.
Lastly, we study lower bounds on the achievable sizes of IBLT with listing
guarantees and verify the results in the paper by simulations.
