I have a problem with this exercise. This is the LALR(1) parsing table for the grammar G. How can i get the productions of G?
LALR(1) parsing table
Thanks :)
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I am studying for a final in Language Theory and one question asks the following:
If you have a parsing table T in LR(1) and a parsing table T' in LALR(1) for the same grammar. Is it possible that T' introduces new shift/reduce conflicts that were not part of T?
My understanding is that LR(1) is "smarter" than LALR(1), so my gut is telling me the answer is "No". However, I'd like to know the correct answer and a proper justification.
Thank you in advance.
LR(1) is "smarter", so LALR(1) may have conflicts where LR(1) does not.
Given a conflict-free LR(1) grammar, though, LALR(1) will only introduce reduce/reduce conflicts, not shift/reduce conflicts.
I studied LR(1) parsers and then LALR(1) and noticed that if we want to construct LALR(1) parsers, we should FIRST construct the LR(1) parser and then, by combining some states with the same core, we can go ahead for LALR(1) parser. (For complex grammars, it's not easy to construct LR parsers)
Now a question comes to mind: can we make LALR(1) parser DIRECTLY? Without using (Or maybe constructing) LR(1) parser? If Yes, How?
Thanks in advance!
PARSING TECHNIQUES A Practical Guide by Dick Grune and Ceriel J.H. Jacobs is worth getting. The Lemon Parser generator (http://www.hwaci.com/sw/lemon/) has readable code too.
I'm really struggling to unterstand the relationship between:
LR(0)
LL(0)
LALR(1)
SLR(1)
LR(1)
LL(1)
I'm pretty sure LALR(1) and SLR(1) are subsets of LR(1), but I'm lost about the others. Are they all exclusive? Is LL(0) a subset of LL(1)?
Thanks
The containment rules are the following:
Every LR(0) grammar is also SLR(1), but not all SLR(1) grammars are LR(0).
Every SLR(1) grammar is also LALR(1), but not all LALR(1) grammars are SLR(1).
Every LALR(1) grammar is also LR(1), but not all LR(1) grammars are LALR(1).
Every LL(1) grammar is also LR(1), but not all LR(1) grammars are LL(1).
Every LL(0) grammar is also LR(0), SLR(1), LALR(1), LR(1), and LL(1). (LL(0) grammars are basically useless; see this question for details why).
It's also the case that every language that has an LR(1) grammar also has an LR(0) grammar provided that you endmark the grammar, though the grammar isn't guaranteed to be pretty.
I confused Exactly !!!!!!
I read following example in one of my professor note.
1) we have a SLR(1) Grammar G as following. we use SLR(1) parser generator and generate a parse table S for G. we use LALR(1) parser generator and generate a parse table L for G.
S->AB
A->dAa
A-> lambda (lambda is a string with length=0)
B->aAb
Solution: the number of elements with R (reduce) in S is more than L.
but in one site i read:
2) Suppose T1, T2 is created with SLR(1) and LALR(1) for Grammar G. if G be a SLR(1) Grammar which of the following is TRUE?
a) T1 and T2 has not any difference.
b) total Number of non-error entries in T1 is lower than T2
c) total Number of error entries in T1 is lower than T2
Solution:
The LALR(1) algorithm generates exactly the same states as the SLR(1) algorithm, but it can generate different actions; it is capable of resolving more conflicts than the SLR(1) algorithm. However, if the grammar is SLR(1), both algorithms will produce exactly the same machine (a is right).
any one could describe for me which of them is true?
EDIT: infact my question is why for a given SLR(1) Grammar, the parse table of LALAR(1) and SLR(1) is exactly the same, (error and non-error entries are equal and number of reduce is equal) but for the above grammar, the number of Reduced in S is more than L.
I see in another book that in general we have:
Summary:
1) for the above grammar that i wrote in question 1, why number of reduced is different?
2) if we have a SLR(1) Grammar, why the table is exactly the same? (number of reduced and error entries become the same)
Both of these statements are true!
One of your questions was why SLR(1) and LALR(1) parsers have the same states as one another. SLR(1) parsers are formed by starting with an LR(0) automaton, then augmenting each production with lookahead information from FOLLOW sets. In an LALR(1) parser, we begin with an LR(1) parser (where each production has very precise lookahead information), then combine any two states that have the same underlying LR(0) state. This results in an LR(0) automaton with additional information because each LR(0) state corresponds to at least one LR(1) state and each LR(1) state corresponds to some underlying LR(0) state.
SLR(1) and LALR(1) parsers both have the same set of states, which are the same states as in an LR(0) parser. The parsers differ only in what actions they perform in each state.
In both SLR(1) and LALR(1) parsers, each item has an associated set of lookahead tokens. Whenever the parser enters a state with a reduce item in it, the parser will perform that reduction if the next token of input is in the lookahead set. In an SLR(1) parser, the lookahead set is the FOLLOW set for the nonterminal on the left-hand side of the production. In an LALR(1) parser, the lookahead set is, appropriately, called the LA set for the combination of the nonterminal in the production and the automaton state.
You can prove that the LA sets used in an LALR(1) parser are subsets of the FOLLOW sets used in SLR(1) parsers. This means that LALR(1) parsers will never have more reduce actions than SLR(1) parsers, and in some cases the LALR(1) parsers will choose to shift when an SLR(1) parser would have a shift/reduce conflict.
Hope this helps!
Answer to Q1:
First of all you need to create DFA for SLR(1) and LALR(1) parsers. I created DFA for both of them.
Link to images of DFAs SLR(1) and LALR(1) DFAs
For SLR(1) I got 10 states and 10 reduce entries whereas for LALR(1) I created DFA for CLR(1) with 13 states which got minimized to 10 states with 7 reduce entries. Thats answers your first question.
Answer to Q2:
G is SLR(1) grammar, then surely there are no conflicts (or error) S-R or R-R in the SLR(1) table. LALR(1) has more power than SLR(1),therefore there is also no conflict in LALR(1) table for given grammar G. Lets see option by option
(c) : there no error in T1 and T2 (wrong option)
(b) : Non-error entries means shift entries and reduce entries. It should be clearly noted that in bottom up parsers from parser to parser only rules for reduce entries changes while for that of shift entries remain same. For e.g in LR(0) reduce entries are made in each column, for SLR(1) it is done in FOLLOW of left hand side variable, while in CLR(1) and LALR(1) reduce entries are made in lookahead symbols. Thus reduce entries changes from parser to parser but shift entries are same.
We have also already proved in Q1 where reduce entries of SLR(1) parsing table are more than that of LALR(1). Therefore proving (b) option to be incorrect.
(a) T1 and T2 may come out to be same but not always. And other important thing is that multiple choice questions sometimes wants you to choose most appropriate option. Thus for me (a) is the answer
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What is the difference between LR, SLR, and LALR parsers?
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I understand both LR and LALR are bottom-up parsing algorithms, but what's the difference between the two?
What's the difference between LR(0), LALR(1), and LR(1) parsing? How can I tell if a grammar is LR(0), LALR(1), or LR(1)?
At a high level, the difference between LR(0), LALR(1), and LR(1) is the following:
An LALR(1) parser is an "upgraded" version of an LR(0) parser that keeps track of more precise information to disambiguate the grammar. An LR(1) parser is a significantly more powerful parser that keeps track of even more precise information than an LALR(1) parser.
LALR(1) parsers are a constant factor larger than LR(0) parsers, and LR(1) parsers are usually exponentially larger than LALR(1) parsers.
Any grammar that can be parsed with an LR(0) parser can be parsed with an LALR(1) parser and any grammar that can be parsed with an LALR(1) parser can be parsed with an LR(1) parser. There are grammars that are LALR(1) but not LR(0) and LR(1) but not LALR(1).
More formally, an LR(k) parser is a bottom-up parser that works by maintaining a stack of terminals and nonterminals. The parser is controlled by a finite automaton that determines, based on the current state of the parser and the next k tokens of input, whether to shift a new token onto the stack or reduce the top symbols of the stack by applying a production in reverse.
In order to keep track of enough information to make a determination about whether to shift or reduce, LR(k) parsers have each state correspond to a "configurating set," a set of productions annotated with the following information:
How much of the production has been seen so far, and
What tokens to expect after the production has been completed (the lookahead)
The first of these pieces of information is used to determine whether the parser may need to do a reduction - if none of the productions in a current state have been completed, there's no reason to do a reduction. The second of these pieces of information is used when doing a reduction to determine whether the reduction should be performed. When deciding whether to reduce, an LR(k) parser looks at the next k tokens of the input stream. If they match the lookahead tokens, the parser will reduce, and otherwise the parser does nothing.
Problems arise in an LR(k) parser when there are conflicts about what the parser should do in a given state. One type of conflict, a shift/reduce conflict, comes up when the parser is in a state where a production has been completed, but the lookahead symbols for that production conflict are also used by another uncompleted production in the state. This means that the parser can't tell whether to perform the reduction or not. A second type of conflict is a reduce/reduce conflict, where the parser knows it has to do a reduction, but two or more reductions are possible and it can't tell which to do.
Intuitively, as k gets larger and larger, the parser has more and more precise information available to it to determine when to shift and when to reduce. If a grammar is not LR(0), for example, the parser might have a state where given no lookahead at all it can't determine whether to shift or to reduce. However, that grammar might still be LR(1) because given an extra token of lookahead, it may be able to recognize that it should definitely shift and not reduce or definitely reduce and not shift.
The problem with LR(k) parsers is that as k gets larger, the number of states can increase exponentially. Lookahead in LR(k) parsers is handled by building more and more states in the parser to correspond to different combinations of productions and lookaheads, so as the number of possible lookaheads increases so does the number of states. Consequently, LR(1) parsers are commonly too large to be practical, and LR(2) or greater is almost unheard of in practice.
LALR(1) was invented as a compromise between the space efficiency of LR(0) parsers and the expressive power of LR(1) parsers. There are several ways to think about what an LALR(1) parser is. Originally, LALR(1) parsers were specified as a transformation that converts LR(1) automata into smaller automata. Although an LR(1) parser may have many more states than an LR(0) automaton, the only difference is that an LR(1) parser may have multiple copies of any particular state in an LR(0) automaton, each annotated with different lookahead information. An LALR(1) parser can be formed by starting with an LR(1) parser, then combining together all states that have the same "core" (the set of productions and their positions), then aggregating all the lookahead information together. This results in a parser that has the same number of states as an LR(0) parser but retains some amount of information about lookaheads to help avoid LR conflicts.
Another view of LALR(1) grammars uses the "LALR-by-SLR" method. LALR(1) parsers can be constructed by starting with an LR(0) parser for a grammar, then creating a new grammar for the language that annotates nonterminals with information about what states in the LR(0) parser they correspond to. The information about the FOLLOW sets of the nonterminals in that grammar can then be used to compute the lookaheads in the LR(0) parser.
The net result is that
LR(0) parsers are small, but not very expressive.
LALR(1) parsers are slightly larger due to the lookahead information, but very expressive.
LR(1) parsers are huge, but extremely expressive.
As for your second question - how do you determine whether a grammar is LR(1) or LALR(1) - the standard approach is to try to build the parsing automata for the LR(1) parser and LALR(1) parser and checking for conflicts. To build the LR(1) parser, you build up the LR(1) configurating sets, then check to see if any of those configurating sets have a shift/reduce conflict or reduce/reduce conflict. To construct an LALR(1) parser, you can either build the LR(1) parser and then condense configurating sets with the same core or can use the LALR-by-SLR method based on the LR(0) parser for the language. More details about how to construct these configurating sets are available in most compilers textbooks. You can also check out the lecture notes from a compilers course I taught in Summer 2012, which cover all of the above parsing methods and a few others.
Hope this helps!
LR(0), SLR(1), LALR(1) parsers all have the same number of states. Minimal LR(1) parsers will have a few more states if the grammar requires it, to avoid reduce-reduce conflicts.
Canonical LR(1) parsers will have many more states, too many for medium or large computer languages.
SLR(1) parser generators build an LR(0) state machine and determine the k=1 lookaheads by examining the grammar (which may report erroneous conflicts).
LALR(1) parser generators build an LR(0) state machine and determine the k=1 lookaheads by examining the LR(0) state machine (which is very complicated).
Canonical LR(1) parser generators build an LR(1) state machine.
Minimal LR(1) parser generators build an LR(1) state machine and merge compatible states during the build process.
The parsing algorithm for a good LALR(1) parser is different in two ways: (1) It should have shift-reduce actions, which reduces the number of states by about 30% and makes the parser faster, and (2) it must do one or more reductions when detecting a syntax error, which makes error recovery more complicated.
The parsing algorithm for a canonical LR(1) parser (1) does not have shift-reduce actions and (2) does not make any reductions when detecting a syntax error, which makes error recovery simpler.
There is another case, called minimal LR(1), which uses the same parsing algorithm and error recovery algorithm as LALR(1). Minimal LR(1) parsers offer the power of LR(1) and their size is almost as small as LALR(1). The LRSTAR Parser Generator creates minimal LR(1) parsers for C++ programmers.