Program Analysis, Representation, and

Transformation

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Program Analysis

• Extracting information, in order to present abstractions of, or answer questions about, a software system

• Static Analysis: Examines the source code

• Dynamic Analysis: Examines the system as it is executing

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What are we looking for?

• Depends on our goals and the system– In almost any language, we can find out information

about variable usage

– In an OO environment, we can find out which classes use other classes, which are a base of an inheritance structure, etc.

– We can also find potential blocks of code that can never be executed in running the program (dead code)

– Typically, the information extracted is in terms of entities and relationships

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Entities

• Entities are individuals that live in the system, and attributes associated with them.

Some examples:– Classes, along with information about their superclass,

their scope, and ‘where’ in the code they exists.

– Methods/functions and what their return type or parameter list is, etc.

– Variables and what their types are, and whether or not they are static, etc.

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Relationships

• Relationships are interactions between the entities in the system.

Relationships include:– Classes inheriting from one another.

– Methods in one class calling the methods of another class, and methods within the same class calling one another.

– One variable referencing another variable.

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Information format

• Many different formats in use• Simple but effective: RSF

inherit TRIANGLE SHAPE• TA is an extension of RSF that includes a schema

$INSTANCE SHAPE Class• GXL is a XML-like extension of TA

Blow-up factor of 10 or more makes it rather cumbersome

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Static Analysis

• Involves parsing the source code

• Usually creates an Abstract Syntax Tree

• Borrows heavily from compiler technology but stops before code generation

• Requires a grammar for the programming language

• Can be very difficult to get right

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CppETS

• CppETS is a benchmark for C++ extractors

• It consists of a collection of C++ programs that pose various problems commonly found in parsing and reverse engineering

• Static analysis research tools typically get about 60% of the problems right

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Example program

#include <iostream.h>class Hello {public: Hello(); ~Hello(); };Hello::Hello(){ cout << "Hello, world.\n"; } Hello::~Hello(){ cout << "Goodbye, cruel world.\n"; }main() {

Hello h;return 0;

}

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Example Q&A

• How many member methods are in the Hello class? Answer: Two, the constructor (Hello::Hello()) and destructor (Hello::~Hello()).

• Where are these member methods used?Answer: The constructor is called implicitly when an instance of the class is created. The destructor is called implicitly when the execution leaves the scope of the instance.

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Static analysis in IDEs

• High-level languages lend themselves better to static analysis needs– EiffelStudio automatically creates BON

diagrams of the static structure of Eiffel systems

– Rational Rose does the same with UML and Java

• Unfortunately, most legacy systems are not written in either of these languages

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Static analysis pipeline

Source code Parser Abstract Syntax Tree

Fact base

Fact extractor

Clustering algorithm

Metrics tool

Visualizer

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Dynamic Analysis

• Provides information about the run-time behaviour of software systems, e.g.– Component interactions– Event traces– Concurrent behaviour– Code coverage– Memory management

• Can be done with a profiler or a debugger

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Instrumentation

• Augments the subject program with code that transmits events to a monitoring application, or writes relevant information to an output file

• A profiler can be used to examine the output file and extract relevant facts from it

• Instrumentation affects the execution speed and storage space requirements of the system

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Instrumentation process

Source code Annotator Annotated program

Instrumentedexecutable

CompilerAnnotation

script

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Dynamic analysis pipeline

Instrumentedexecutable

CPU Dynamic analysis data

Fact base

Profiler

Clustering algorithm

Metrics tool

Visualizer

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Non-instrumented approach

• One can also use debugger log files to obtain dynamic information

• Disadvantage: Limited amount of information provided

• Advantage: Less intrusive approach, more accurate performance measurements

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Dynamic analysis issues

• Ensuring good code coverage is a key concern

• A comprehensive test suite is required to ensure that all paths in the code will be exercised

• Results may not generalize to future executions

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Static vs. Dynamic

• Reasons over all possible behaviours (general results)

• Conservative and sound

• Challenge: Choose good abstractions

• Observes a small number of behaviours (specific results)

• Precise and fast

• Challenge: Select representative test cases

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Program Representation

• Fundamental issue in re-engineering– Provides means to generate abstractions– Provides input to a computational model for

analyzing and reasoning about programs– Provides means for translation and

normalization of programs

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Key questions

• What are the strengths and weaknesses of various representations of programs?

• What levels of abstraction are useful?

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Representation schemes

• Chosen based on objectives and tasks to be performed. Popular ones are:– Abstract syntax trees– Control Flow Graphs– Data Flow Graphs– Structure Charts– Module Dependency Graphs

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Abstract Syntax Trees

• A translation of the source text in terms of operands and operators

• Omits superficial details, such as comments, whitespace

• All necessary information to generate further abstractions is maintained

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AST production

• Four necessary elements to produce an AST:– Lexical analyzer (turn input strings into

tokens)– Grammar (turn tokens into a parse tree)– Domain Model (defines the nodes and arcs

allowable in the AST)– Linker (annotates the AST with global

information, e.g. data types, scoping etc.)

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AST example

• Input string: 1 + /* two */ 2• Parse Tree:

• AST (withoutglobal info)

21

+

intint

Add

1 2

arg1 arg2

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Control Flow Graphs

• Offer a way to eliminate variations in control statements by providing a normalized view of the possible flow of execution of a program

• To produce a CFG:– AST of the program

– Decomposition of the program into basic blocks

– Basic semantics on the control statements of the language

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Data Flow Graphs

• Focus mostly on the exchange of information between program components, i.e. basic blocks, functions, modules

• To produce a DFG:– AST of the program

– Decomposition of the program into basic blocks (or more coarsely-grained level)

– Annotations on uses and definitions of variables

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Structure charts

• Represent data and control information in a concise and compact form

• To produce a structure chart:– The CFG of the program– The DFG of the program

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Module Dependency Graphs

• The most common way to represent data coupling and data dependencies between program and system entities

• To produce an MDG:– Structure chart of the program– Information on parameter passing between

procedures and functions– Containment information

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Program Transformation

• A program is a structured object with semantics

• Structure allows us to transform a program

• Semantics allow us to compare programs and decide on the validity of transformations

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Program Transformation

• The act of changing one program into another (from a source language to a target language)

• Used in many areas of software engineering:– Compiler construction

– Software visualization

– Documentation generation

– Automatic software renovation

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Application examples

• Converting to a new language dialect• Migrating from a procedural language to an

object-oriented one, e.g. C to C++• Adding code comments• Requirement upgrading, e.g. using 4 digits for

years instead of 2 (Y2K)• Structural improvements, e.g. changing GOTOs

to control structures• Pretty printing

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Simple program transformation

• Modify all arithmetic expressions to reduce the number of parentheses using the formula: (a+b)*c = a*c + b*c

x := (2+5)*3becomesx := 2*3 + 5*3

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Two types of transformations

• Translation– Source and target language are different– Semantics remain the same

• Rephrasing– Source and target language are the same– Goal is to improve some aspect of the program

such as its understandability or performance– Semantics might change

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Translation

• Program synthesis– Lowers the level of abstraction, e.g. compilation

• Program migration– Transform to a different language

• Reverse Engineering– Raises the level of abstraction, e.g. create architectural

descriptions from the source code

• Program Analysis– Reduces the program to one aspect, e.g. control flow

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Translation taxonomy

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Rephrasing

• Program normalization– Decreases syntactic complexity (desugaring),

e.g. algebraic simplification of expressions

• Program optimization– Improves performance, e.g. inlining, common-

subexpression and dead code elimination

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Rephrasing

• Program refactoring– Improves the design by restructuring while

preserving the functionality

• Program obfuscation– Deliberately makes the program harder to

understand

• Software renovation– Fixes bugs such as Y2K

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Transformation tools

• There are many transformation tools

• Program-Transformation.org lists 90 of them

• Most are based on term rewriting

• Other solutions use functional programming, lambda calculus, etc.

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Term rewriting

• The process of simplifying symbolic expressions (terms) by means of a Rewrite System, i.e. a set of Rewrite Rules.

• A Rewrite Rule is of the formlhs rhswhere lhs and rhs are term patterns

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Example Rewrite System

0 + x x s(x) + y s(x + y)(x + y) + z x + (y + z)

Under these rewrite rules, the term((s(s(a)) + s(b)) + c)will be rewritten ass(s(s(a + (b + c))))

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TXL

• A generalized source-to-source translation system

• Uses a context-free grammar to describe the structures to be transformed

• Rule specification uses a by-example style

• Has been used to process billions of lines of code for Y2K purposes

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TXL programs

• TXL programs consist of two parts:– Grammar for the input language– Transformation Rules

• Let’s look at some examples…

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Calculator.Txl - Grammar

% Part I. Syntax specification

define program

[expression]

end define

define expression

[term]

| [expression] [addop] [term]

end define

define term

[primary]

| [term] [mulop] [primary]

end define

define primary [number] | ( [expression] )end define define addop '+ | '-end define define mulop '* | '/end define

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Calculator.Txl - Rules% Part 2. Transformation rulesrule main replace [expression] E [expression] construct NewE [expression] E [resolveAddition] [resolveSubtraction] [resolveMultiplication] [resolveDivision] [resolveParentheses] where not NewE [= E] by NewEend rule

rule resolveAddition replace [expression] N1 [number] + N2 [number] by N1 [+ N2]end rule rule resolveSubtraction …rule resolveMultiplication …rule resolveDivision …rule resolveParentheses replace [primary] ( N [number] ) by Nend rule

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DotProduct.Txl

% Form the dot product of two vectors,% e.g., (1 2 3).(3 2 1) => 10define program ( [repeat number] ) . ( [repeat number] ) | [number]end define

rule main replace [program] ( V1 [repeat number] ) . ( V2 [repeat number] ) construct Zero [number] 0 by Zero [addDotProduct V1 V2]end rule

rule addDotProduct V1 [repeat number] V2 [repeat number] deconstruct V1 First1 [number]

Rest1 [repeat number] deconstruct V2 First2 [number]

Rest2 [repeat number] construct ProductOfFirsts [number] First1 [* First2] replace [number] N [number] by N [+ ProductOfFirsts]

[addDotProduct Rest1 Rest2]end rule

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Sort.Txl

% Sort.Txl - simple numeric bubble sortdefine program [repeat number]end definerule main replace [repeat number] N1 [number] N2 [number] Rest [repeat number] where N1 [> N2] by N2 N1 Restend rule

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Other TXL constructs

compounds -> :=end compoundskeys var procedure exists inout outend keysfunction isAnAssignmentTo X [id] match [statement] X := Y [expression]end function

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www.txl.ca

• Guided Tour

• Many examples

• Reference manual

• Download TXL for many platforms