Transcript aspect - Software Engineering Laboratory

Program Slicing Tool for
Effective Software Evolution
Using Aspect-Oriented Technique
Takashi Ishio
Shinji Kusumoto
Katsuro Inoue
Osaka University
{t-isio, kusumoto, inoue}@ist.osaka-u.ac.jp
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Background
In software evolution process, software is
modified to adapt for the changes of its
specification.
When a programmer changes structure and
functions of a software, several bugs are
usually injected.
Debugging is an important task in software
evolution.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Debugging Large Scale Software
Large scale software is difficult to debug.
Especially, fault localization needs much cost
since the location where a program crushed is
not always close to the fault.
Executed codes for one test case are usually
small pieces of the program.
Excluding automatically unrelated
codes is effective for fault localization.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Program Slicing
Program Slicing extracts a slice of codes,
which affects value of a specific variable.
1:
2:
3:
4:
5:
6:
a = 5;
b = a + a;
if (b > 0) {
c = a;
}
d = b;
a slice based on slice
criteria（6, b）
1:
2:
3:
4:
5:
6:
a = 5;
b = a + a;
if (b > 0) {
c = a;
}
d = b;
Program Slicing excludes unrelated codes
to aid fault localization.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Slice Calculation Process
Phase 1: Extraction of
dependence relations
Data Dependence
Data Dependence Relation:
assignment  reference
Control Dependence Relation:
conditional statement  controlled block
Phase 2: Construction of
Program Dependence Graph
node: a statement.
edge: a dependence relation
Phase 3: Traversal of PDG
1: a = 1;
2: c = 4;
3: b = a;
a
Control Dependence
4: if (a < 1) {
5:
b = a;
6: }
Program Dependence
Graph
traversal backward from a node
corresponding a slice criteria
slice criteria
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Dependence-Cache (DC) slicing using
dynamic information
In slice calculation process, information about the
statements actually executed is effective to
decrease the slice size.
Dynamic information excludes unexecuted codes from a
slice.
Dependence-Cache (DC) slicing method uses:
Dynamic Data Dependence Analysis
Static Control Dependence Analysis
DC slicing calculates an accurate slice with
lightweight costs.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Implementation of dynamic analysis
Dynamic analysis, collecting dynamic information during
program execution, is a kind of logging (or tracing).
Java Virtual Machine (JVM) Customization †
+ JVM can access all information of the runtime environment.
- Customization depends on a specific JVM implementation.
- Byte code optimization may affect analysis results.
Java Debugger Interface (JDI)
+ JDI can access local variables, stack traces, ...
- High runtime cost
Threads of control are blocked for each logging point.
Although various ways exist in implementing the dynamic
analysis, each one requires a high cost in implementation or
in runtime.
† F. Umemori et al.: “Design and Implementation of Bytecode-based
Java Slicing System”, SCAM 2003 (to appear)
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Aspect-Oriented Programming
A key feature of Aspect-Oriented Programming is separation
of crosscutting concerns.
AOP introduces a new module unit named aspect.
In OOP, programmers cannot encapsulate crosscutting
concerns:
logging, error handling, some design patterns
Programmers distribute many call statements into related classes for
object interaction.
It is hard to manage the distributed codes.
In AOP, programmers write a crosscutting concern in an
aspect.
An aspect has information when the aspect is executed.
Call statements are needless.
When a concern is changed, programmers modify one aspect instead of
related classes.
AOP improves modularity, maintainability and reusability.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Example of Aspect
Logging: “Logs a method name for each
method execution.”
In OOP, logging codes are distributed in all
classes. If logging specification is changed,
programmers may modify all classes.
In AOP, logging codes are encapsulated in the
Logging Aspect. It is easy to maintain and reuse.
Class A
Class B
Class C
logger.logs(value);
Logging Class
Class A
when a method is executed,
logger.logs(value) is called.
Class B
Logging Aspect
Class C
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
AspectJ, an AOP extension for Java
AspectJ: an AOP extension for Java
An aspect is defined as a set of advices.
An advice consists of a procedure and pointcut
designators (PCDs).
PCDs describe when the procedure is executed.
AspectJ compiler:
aspects + Java class source  Java bytecode
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Features of AspectJ
AspectJ provides the following PCDs:
Method Call and Execution
Field Assignment and Reference
Exception Handling
An advice body is written in plain Java code.
An advice can access context information
through thisJoinPoint object.
Context information is:
Which method is actually executed ?
What type of object is accessed ?
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Example of AspectJ
How to implement logging in AspectJ:
keyword for Aspect definition
Pointcut is defined by PCDs.
Pointcut represents events during
program execution.
aspect LoggingAspect {
pointcut allMethods():
execution(* *(..)) && !within(java.io.*);
before(): allMethods(){
When the advice is executed.
Logger.println(thisJoinPoint.getSignature());
}
In the advice body, programmers can
}
access context information via thisJoinPoint object.
It is needless to change logging target classes.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Dynamic Analysis Aspect
We implement dynamic analysis using AspectJ.
Dynamic analysis aspect
records a position of the assignment statement when a
new value is assigned to a field,
extracts a dynamic data dependence relation when the
field is referred,
collects method-call information for each thread (multithreading),
collects information when an exception is thrown and
which handling clause caught the exception (exceptionhandling).
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Advantages of Aspect Approach
Advantages
Modularization of dynamic analysis
Independent of a specific JVM implementation
Independent of a byte-code optimizer ( JIT compiler )
Lightweight Analysis
for large scale software.
No local variables are dynamically analyzed.
Local variables affects dependencies in one method.
Little difference comes from dynamic information of local variables.
No library classes are analyzed.
We assume that library classes are reliable.
less overhead: The aspect is linked to target program at
compile time.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Aspect-based Dynamic Analysis and Slice
Calculation System: ADAS
Debugging Support Tool using Program
Slicing for Java
Dynamic Analysis Aspect (written in AspectJ)
Simple logging-like Implementation
size: about 1000 LOC
Program Slicing System (written in Java)
Program Slicing is an application using dynamic
information.
The prototype is implemented as Eclipse plug-in.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Architecture and Use Case of ADAS
1.edit
program slice
slice
criteria
Dynamic
Java Source
Analysis
Aspect
4.slice calculation
Slice Calculation Tool
Static
Analyzer
Static
Info.
2.compile
AspectJ
Java
Bytecode
Java VM
3.execute
a test case
Dynamic
Info.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Demonstration
Slice calculation button
Slice criterion selection
Slice results indicated
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Evaluation: size of a slice
Compare with customized JVM implementation †
JVM approach: Precise DC Slice
Our apparoch: omitting analysis for local variables.
Target programs
P1: A simple database (4 classes, 262 LOC)
P2: A sorting program (5 classes, 228 LOC)
P3: A slice calculation program (125 classes, about 16000 LOC)
size of a slice (LOC)
Our approach calculates
a slice including
some redundant code
JVM can extract a precise
slice using fine-grained
information.
Aspect
JVM
Aspect/JVM
P1
36
29
1.24
P2
50
28
1.70
P3
839
708
1.19
† F. Umemori et al.: “Design and Implementation of Bytecode-based
Java Slicing System”, SCAM 2003 (to appear)
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Evaluation: analysis cost
Our approach shows good performance.
Our approach is a coarse-grained, lightweight analysis.
JVM approach is hard to apply a large scale
software.
ratio
Running Time [seconds]
Normal
Aspect
JVM
Aspect/Normal JVM/Normal
Execution Approach Approach
P1
0.18
0.26
1.8
1.4
10.0
P2
0.19
0.39
2.8
2.1
14.7
P3
1.2
10.3
81.0
8.6
67.5
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Evaluation: Cost of Implementation
Aspect approach:
Our module consists of the dynamic analysis aspect and
data management classes.
The total size is 1000 LOC.
JVM approach:
System consists of customized JVM and Java compiler.
Customized compiler insert source code information into bytecode
files.
Size of additional code for the customization is about
50,000 LOC.
Source code of the original JVM and compiler is 300,000 LOC.
Programmers must re-customize the JVM whenever new
version of JVM is released.
Aspect approach is inexpensive.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University
Remark and Future Work
Debugging is an important task for software
evolution.
Program slicing shows related code to a user.
Dynamic information exclude unexecuted code.
Dynamic Analysis Aspect is
simple implementation,
easy to maintain, customize.
Future Work
Extension of ADAS to calculate AspectJ slice,
Improvement of Usability.
IWPSE 2003
Software Engineering Laboratory, Department of Computer Science, Graduate School of Information Science and Technology, Osaka University