As a matter of practicality, you could probably get away with just (a) finite automata, both in the hand-coded lexer style and regular expression style tools like lex; (b) LL(k), both in hand-coded recursive descent and tools like antlr; and (c) GLR, when you need to pull out bigger guns.
A little googling uncovers a Second Edition, also available on pdf.
I'm probably too close to this domain to have a useful perspective for those not familiar with it though.
"In [3], Hopcroft gives an algorithm for minimizing the number of states in a finite automaton. [...] Unfortunately the algorithm, its proof of correctness and the proof of running time, are all very difficult to understand. We present here a "structured", top-down approach to the presentation of the algorithm which makes it much clearer. [...] Such a structured approach to presenting an algorithm seems to be longer and require more discussion than the conventional way. If the reader wishes to complain about this, he is challenged to first read Hopcroft's original paper and see whether he can understand it easily. The advantages of our approach will thus be clear."
And this is just a DFA minimization algorithm! It's not an undecidability proof or anything like that. And Hopcroft's original paper (PDF: ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/71/190/CS-TR-71-190.pdf) isn't nearly as dense or symbol-heavy as a lot of parsing papers out there.
There is a wide gap between reading papers that begin "A grammar G is a 4-tuple G=(N, sigma, P, S)" and are full of proofs and lemmas, and actually implementing algorithms.
This is why 'parsing techniques' is a joy. It explains with clarity what is often nightmarish to gleam from papers.
edit: I read a draft copy and after getting sucked into it for a weekend I grabbed the hard copy.
This is to complement the existing literature with a broad and deep coverage of parsing in specific. There is most to parsing than just the front end of a compiler :-)