Grammar compression is a general compression framework in which a string T
of length N is represented as a context-free grammar of size n whose
language contains only T. In this paper, we focus on studying the limitations
of algorithms and data structures operating on strings in grammar-compressed
form. Previous work focused on proving lower bounds for grammars constructed
using algorithms that achieve the approximation ratio
ρ=O(polylog N). Unfortunately, for the majority of
grammar compressors, ρ is either unknown or satisfies
ρ=ω(polylog N). In their seminal paper, Charikar et al. [IEEE
Trans. Inf. Theory 2005] studied seven popular grammar compression algorithms:
RePair, Greedy, LongestMatch, Sequential, Bisection, LZ78, and
α-Balanced. Only one of them (α-Balanced) is known to achieve
ρ=O(polylog N).
We develop the first technique for proving lower bounds for data structures
and algorithms on grammars that is fully general and does not depend on the
approximation ratio ρ of the used grammar compressor. Using this
technique, we first prove that Ω(logN/loglogN) time is required
for random access on RePair, Greedy, LongestMatch, Sequential, and Bisection,
while Ω(loglogN) time is required for random access to LZ78. All
these lower bounds hold within space O(n polylog N) and
match the existing upper bounds. We also generalize this technique to prove
several conditional lower bounds for compressed computation. For example, we
prove that unless the Combinatorial k-Clique Conjecture fails, there is no
combinatorial algorithm for CFG parsing on Bisection (for which it holds
ρ=Θ~(N1/2)) that runs in O(nc⋅N3−ϵ) time for all constants c>0 and ϵ>0. Previously,
this was known only for c<2ϵ