Java Enhanced LL LR Animated Parser
NOTE: jeLLRap is no longer supported. Instead it has been incorporated into the tool JFLAP . With JFLAP you can build SLR(1) parse tables and LL(1) parse tables. See JFLAp for more info.
What is it?
JELLRAP is a graphical tool written for people who wish to parse strings using a variety of algorithms: LL1, LL2, or LR1. It is the Java version of LLParse and LRParse combined into a single tool that will run on multiple platforms. LLParse and LRParse were written in C/C++ and run only on an X-windows environment. If you are currently running LLParse and LRParse and are wondering if you should upgrade, here are some changes that may help you decide:
Written in Java, so it is easier to install
JELLRAP is especially useful for Automata Theory or Compiler courses.
Students can explore, practice, and check their work on their own. It is
an instructional tool to aid in learning the parsing algorithms, and thus
is intended for use with small examples.
Is a single tool so you can switch between LL and LR with ease
Similar look and feel -- even maintains the same keyboard shortcuts
Bug fixes were made to the LL2 Parser
Improved graphics for DFA and trees
New feature to show the rules in a derivation
Can TAB through grammar production rules instead of aligning the mouse
LL1 vs LL2 vs LR1
The first L is for parsing input from left to right and the second L is for using leftmost derivations. JELLRAP supports both LL1 parsing and LL2 parsing whereby the 1 and 2 indicates the number of lookahead symbols. For the R in LR1 stand for using the rightmost derivation and JELLRAP only supports using 1 look ahead symbol.
Can I see it first?
Sneak Preview!! (if your browser can support a Java 1.1 Applet)
How do I get my own?
Read the README file and then Download the whole package from here (including the source code):
ftp://ftp.cs.duke.edu/pub/rodger/tools/jellrap.12-97.tar.gz (any platform)
Simplified class diagram
JELLRAP was written by undergraduates at Duke University, Alex Karweit and Robyn Geer, headed by Prof. Susan Rodger, and financed by a grant from the National Science Foundation.