ANTLR in SSP
Xingzhong Xu
Hong Man
Aug. 11
Outline
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ANTLR
Abstract Syntax Tree
Code Equivalence (Code Re-hosting)
Future Work
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What is ANTLR?
• ANTLR, ANother Tool for Language
Recognition, is a language tool that
provides a framework for constructing
recognizers, interpreters, compilers,
and translators from grammatical
description containing actions in variety of
target languages.
-- antlr.org
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Why use ANTLR?
• SSP
– Looking for a framework to understanding the
signal processing source code semantically.
• Classical analysis method in CS
– Code Recognizer: Lexer & Parser
– Interpreter: Cognitive Linguistic Modeling &
other syntax tree
– Translator: code re-hosting, different target
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How ANTLR Work? - I
• Lexer
– Converting a sequence of characters into a sequence
of tokens.
• Parser
– Converting a sequence of tokens which generated
from the Lexer to determine its grammatical structure.
• Abstract Syntax Tree
– Tree representation of the abstract syntactic structure
of source code.
– The syntax is ‘abstract’ which means it does not
represent every detail of the real syntax.
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Example
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How ANTLR Work? - II
• In order to generate the Lexer, Parser and
AST. We need analyze the structure of the
target code and write related ANTLR
grammar.
• Example: Matrix Declaration in Matlab
M1
M2
M3
M4
=
=
=
=
[1 2 3; 4 5 6];
[1,2,3;4,5,6];
[M1;M2];
1;
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ANTLR Grammar - I
M1 = [1 2 3; 4 5 6];
• Statement
– [Variable] [Equal] [Expression] [Semicolon] (optional)
• Expression
– [Left Square Bracket] [Matrix] [Right Square Bracket] or [one
digit]
• Matrix
– [Line] [Semicolon] [Line] [Semicolon] ….
• Line
– [digit] [comma] (optional) [digit] [comma] (optional) …
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ANTLR Grammar - II
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Abstract Syntax Tree
M1 = [1 2 3; 4 5 6];
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Abstract Syntax Tree
M2 = [1,2,3;4,5,6];
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Abstract Syntax Tree
M3 = [M1;M2];
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Abstract Syntax Tree
M4 = 1;
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AST Example from GNU-Radio
• Using ANTLR, some example from GNU-Radio
code has been tested.
• http://sites.google.com/site/stevensxingzhong/
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Code Equivalence
• In order to re-hosting the code
– The proper rule to abstract the code.
– The functionality of the code segment.
• Methodology
– Abstraction
– Code Segmentation
– Functionality Analysis
– Replace the segment by equivalence code.
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Current Method in CS
• Syntax Tree based Comparison
– Generate AST or other related abstract tree, perform
tree-matching algorithm.
– Use hash function to mapping the tree structure and
simplify the algorithm.
• Radom Test Comparison
– Code Chopper, segment the code.
– Randomly test the Input/Output behavior.
– Schwartz-Zippel lemma, enough time of the test can
derive the functionality.
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Simplest Filter Example
• Take the simplest filter as an example, following code
segments have exactly same functionality.
for (i = 0; i < n; i++)
acc0 += d_taps[i] *
input[i];
for (i = 0; i < n ; )
acc0 += d_taps[i] *
input[i++];
i = 0;
while ( i < n )
acc0 += d_taps[i] *
input[i++];
i = 0;
for ( ; i < n ; )
acc0 += d_taps[i] *
n 1
input[i++];
yn   hi xi
i 0
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Ordinary AST
for (i = 0; i < n; i++)
acc0 += d_taps[i] * input[i];
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Modified AST
• The ordinary AST is derived from the
programming grammar level.
• Following the idea of the semantic signal
processing. For example, in signal
processing domain abstraction:
– ‘For’, ‘While’, ‘do … while’ -> ‘LOOP’
– ‘+=’, ‘VAR = VAR + whatever’ ->
‘ACCUMLATE’
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Simplest Filter Example
for (i = 0; i < n; i++)
acc0 += d_taps[i] * input[i];
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Simplest Filter Example
for (i = 0; i < n; )
acc0 += d_taps[i] *
input[i++];
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Simplest Filter Example
i = 0;
while ( i < n )
acc0 += d_taps[i] *
input[i++];
i = 0;
for ( ; i < n ; )
acc0 += d_taps[i] *
input[i++];
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Code Equivalence
• Objection: From the syntax tree to
determine the code segments are
equivalence.
– Abstraction
– Tree matching.
• Perform code re-hosting.
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Simplest Filter Example
for (int i = 0; i < noutput_items; i++) {
gr_complex sum(0.0, 0.0);
for (k = 0; k < l; k++)
sum += d_taps[l-k-1]*in[j+k];
out[i] = sum;
}
From gr_adaptive_fir_ccf.cc
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Abstraction
• The basic element for the simplest filter
include:
– LOOP
– ACCUMLATION
– MULTIPLY
– ARRAY
– MOVING INDEX
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Similarity Tree Pattern
• No abstraction can guarantee the same
functional code have precisely same abstraction
form. Therefore, we need perform a similarity
tree pattern recognition.
Similar enough to determine the equivalence
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Future Work
• Using ANTLR generate other language
Lexer and Parser for language recognition.
• Abstract the language into Cognitive
Linguistic Modeling.
• Find proper method to perform a similarity
tree pattern recognition.
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Reference
1.
2.
3.
4.
5.
6.
7.
Terence Parr, The Definitive Antlr Reference: Building Domain-Specific
Language (Pragmatic Programmers), 2007
http://www.antlr.org
http://www.stringtemplate.org
Jiang L. and Su, Z. 2009. Automatic Mining of functionally equivalent
code fragments via random testing. In Proceedings of the Eighteenth
international Symposium on Software Testing and Analysis
Gabel, M., Jiang, L., and Su, Z. 2008. Scalable detection of semantic
clones. In Proceedings of the 30th international Conference on Software
Engineering
C.K. Roy, J.R. Cordy and R. Koschke B. 2009. Comparison and Evaluation
of code Clone Detection Techniques and Tools: A Qualitative Approach.
Science of Computer Programming
Bertran, M., Babot, F., and Climent, A. 2005. An Input/Output Semantics
for Distributed Program Equivalence Reasoning. Electron. Notes Theor.
Comput. Sci. 137, 1 (Jul. 2005)
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