Program Slicing Tool for Effective Software Evolution Using Aspect-Oriented Technique

1. 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

2. 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

3. 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

4. Program Slicing • Program Slicing extracts a slice of codes,which affects value of a specific variable. • Program Slicing excludes unrelated codes to aid fault localization. 1: a = 5; 2: b = a + a; 3: if (b > 0) { 4: c = a; 5: } 6: d = b; 1: a = 5; 2: b = a + a; 3: if (b > 0) { 4: c = a; 5: } 6: d = b; a slice based on slice criteria（6, b） IWPSE 2003

5. Data Dependence 1: a = 1; 2: c = 4; 3: b = a; a Control Dependence 4: if (a < 1) { 5: b = a; 6: } Program Dependence Graph Slice Calculation Process • Phase 1: Extraction of dependence relations • 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 • traversal backward from a node corresponding a slice criteria slice criteria IWPSE 2003

6. 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

7. 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

8. 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

9. 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. when a method is executed, logger.logs(value) is called. Class A Class A logger.logs(value); Logging Aspect Logging Class Class B Class B Class C Class C IWPSE 2003

10. 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

11. 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

12. Example of AspectJ • How to implement logging in AspectJ: aspect LoggingAspect { pointcut allMethods(): execution(* *(..)) && !within(java.io.*); before(): allMethods(){ Logger.println(thisJoinPoint.getSignature()); } } keyword for Aspect definition Pointcut is defined by PCDs. Pointcut represents events during program execution. When the advice is executed. In the advice body, programmers can access context information via thisJoinPoint object. It is needless to change logging target classes. IWPSE 2003

13. 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 (multi-threading), • collects information when an exception is thrown and which handling clause caught the exception (exception-handling). IWPSE 2003

14. 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

15. 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

16. Static Info. Dynamic Info. Architecture and Use Case of ADAS 1.edit program slice slice criteria 4.slice calculation Dynamic Analysis Aspect Java Source Slice Calculation Tool Static Analyzer 2.compile Java VM AspectJ Java Bytecode 3.execute a test case IWPSE 2003

17. Slice calculation button Slice criterion selection Slice results indicated Demonstration IWPSE 2003

18. 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) • Our approach calculates a slice including some redundant code • JVM can extract a precise slice using fine-grained information. size of a slice (LOC) • † F. Umemori et al.: “Design and Implementation of Bytecode-based Java Slicing System”, SCAM 2003 (to appear) IWPSE 2003

19. 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] IWPSE 2003

20. 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

21. 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