1 Gemini: Maintenance Support Environment Based on Code Clone Analysis *Graduate School of Engineering Science, Osaka Univ. **PRESTO, Japan Science and Technology Corp. ***Graduate School of Information Science and Technology, Osaka Univ. {kamiya, kusumoto, Yasushi Ueda*, Toshihiro Kamiya**, Shinji Kusumoto*** and Katsuro Inoue***

2 Contents Background Maintenance support environment, Gemini Overview System structure Scatter Plot Case Study Conclusions

3 Background (1/2) A code clone is a pair/set of code portions in source files that are identical or similar to each other. clone pair clone class

4 Background (2/2) Code clone is one of the factors that make software maintenance more difficult. If some faults are found in a code fragment, it is necessary to correct the faults in its all clone pairs. [1] T. Kamiya, S. Kusumoto, and K. Inoue, “CCFinder: A multi-linguistic token-based code clone detection system for large scale source code”, IEEE Transactions on Software Engineering, (to appear). We have developed a code clone detection tool, CCFinder[1]. Token-based clone detector Its input is a set of source files and output is the locations of clone pairs.

5 CCFinder (1/4) Clone detection process consists of four steps. Source files Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting Clone pairs CCfinder Step 1 Step 2 Step 3 Step 4 Target program C / C++ Java FORTRAN COBOL LISP

6 Source files Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting Clone pairs 1. static void foo() throws RESyntaxException { 2. String a[] = new String [] { "123,400", "abc", "orange 100" }; 3. org.apache.regexp.RE pat = new org.apache.regexp.RE("[0-9,]+"); 4. int sum = 0; 5. for (int i = 0; i < a.length; ++i) 6. if (pat.match(a[i])) 7. sum += Sample.parseNumber(pat.getParen(0)); 8. System.out.println("sum = " + sum); 9. } 10. static void goo(String [] a) throws RESyntaxException { 11. RE exp = new RE("[0-9,]+"); 12. int sum = 0; 13. for (int i = 0; i < a.length; ++i) 14. if (exp.match(a[i])) 15. sum += parseNumber(exp.getParen(0)); 16. System.out.println("sum = " + sum); 17. } Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting CCFinder (2/4) Example of clone detection process

7 Example of transformation rules in Java All identifiers defined by user are transformed to same tokens. Unique identifier is inserted at each end of the top-level definitions and declarations. Prevents detecting clones that begin at the middle of class definition and end at the middle of another one. ”java. lang. Math. PI” is transformed to ”Math. PI”. By using import sentence, a class is referred to with either full package name or a shorter name ” new int[] {1, 2, 3} ” is transformed to ” new int[] {$} ” Eliminates table initialization code.

8 Source files Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting Clone pairs 1. static void foo() throws RESyntaxException { 2. String a[] = new String [] { "123,400", "abc", "orange 100" }; 3. org.apache.regexp.RE pat = new org.apache.regexp.RE("[0-9,]+"); 4. int sum = 0; 5. for (int i = 0; i < a.length; ++i) 6. if (pat.match(a[i])) 7. sum += Sample.parseNumber(pat.getParen(0)); 8. System.out.println("sum = " + sum); 9. } 10. static void goo(String [] a) throws RESyntaxException { 11. RE exp = new RE("[0-9,]+"); 12. int sum = 0; 13. for (int i = 0; i < a.length; ++i) 14. if (exp.match(a[i])) 15. sum += parseNumber(exp.getParen(0)); 16. System.out.println("sum = " + sum); 17. } Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting CCFinder (2/4) Example of clone detection process Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting Lexical analysis Transformation Token sequence Match detection Transformed token sequence Clones on transformed sequence Formatting 1. static void foo() throws RESyntaxException { 2. String a[] = new String [] { "123,400", "abc", "orange 100" }; 3. org.apache.regexp.RE pat = new org.apache.regexp.RE("[0-9,]+"); 4. int sum = 0; 5. for (int i = 0; i < a.length; ++i) 6. if (pat.match(a[i])) 7. sum += Sample.parseNumber(pat.getParen(0)); 8. System.out.println("sum = " + sum); 9. } 10. static void goo(String [] a) throws RESyntaxException { 11. RE exp = new RE("[0-9,]+"); 12. int sum = 0; 13. for (int i = 0; i < a.length; ++i) 14. if (exp.match(a[i])) 15. sum += parseNumber(exp.getParen(0)); 16. System.out.println("sum = " + sum); 17. }

9 CCFinder (3/4) Application of CCFinder Free software JDK libraries (Java, 570 KLOC) Linux, FreeBSD (C, MLOC) FreeBSD, OpenBSD ， NetBSD(C) Qt(C++ ， 240KLOC) Commercial software NTT data Corp., Hitachi Ltd., NEC soft Ltd., ASTEC Inc., SRA Inc. NASDA (Control program for rocket)

10 CCFinder (4/4) Output of CCFinder #version: ccfinder 3.1 #langspec: JAVA #option: -b 30,1 #option: -k + #option: -r abcdfikmnprsv #option: -c wfg #begin{file description} C:\Gemini.java C:\GeneralManager.java : #end{file description} #begin{clone} ,9 63, ,9 553, ,9 63, ,9 633, ,9 152, ,9 216,51 42 : #end{clone} Object file ID ( file 0 in Group 0 ) Location of a clone pair ( Lines in file 0.1 and Lines in file 1.10 are identical or similar to each other) It is difficult to analyze source code by only this text-based information of the location of clone pairs.

11 Goals of this study Proposal of an interactive code clone analysis environment Gemini Case study to evaluate the proposed environment Apply Gemini to programming exercise in our university and analyze the results.

12 Gemini overview A GUI-based code clone analysis environment Uses CCFinder as a code clone detector. Has several views to interactive analysis. Scatter plot view Select by mouse dragging Sorting function Zoom in/out Metric graph view Select by metric values Source code view Implemented in Java About 10,000 lines of code

13 Clone pair manager (CPM) Clone class manager (CCM) Scatter plot view Clone pair list view Metrics graph Clone class list view User Interfaces System structure of Gemini Source files Source code manager (SCM) Source code view Clone selection information User Gemini Code clone detector (CCD) CCFinder Code clone database (CDB)

14 Scatter plot Both the vertical and horizontal axes represent a token sequence of source code. A dot means that corresponding two tokens on the two axes are same. The main diagonal line is always drawn, since each dot on it refers to an identical position of the two axes. A clone pair is shown as a diagonal line segment. The distribution is symmetrical with the main diagonal line. a b c a b c a d e c a, b, c,... : tokens : matched position

15 Sorting function f1 f6 f3 f1 f6f3 f4 f2 f5 f2 When multiple files are compared in scatter plot, boundaries of their files are shown on the axes. Depending on the file orders, the distribution of dots is spread widely. We put similar files as near as possible.

16 Snapshots of scatter plot

17 Clone class metrics LEN (C ): Length of token sequence of each element in clone class C POP (C ): Number of elements in clone class C RAD (C ): Distribution in the file system of elements in clone class C DFL (C ): Estimation of how many tokens would be removed from source files when all code fragments of clone class C are replaced with caller statements of a new identical routine new sub routine caller statements

18 Aims of clone class metrics We are interested in Clone classes whose elements are spread widely. High value of POP means that there are many similar code fragments. High value of RAD means that the clones are spread over many subsystems. They are difficult to find all together in maintenance. Clone classes which are appropriate for refactoring. High value of DFL (high value POP and high value of LEN) means that the clone class is worth evaluating whether the elements can be merged into one routine.

19 Snapshots of clone class metric graph RAD LENPOP DFL Filtering mode : ON

20 Case study overview Application target Programs developed in a programming exercise of Osaka Univ. Compiler in C language Programs of 69 students Total size is 360,000 lines of code Issue of Analysis Similarity among all programs In the programming exercise, plagiarisms sometimes happen.

21 Analysis (1/2) Compiler of 69 students are arranged on the two axes. The distribution is spread widely. Rearrangement of scatter plot using sorting function The grid represents boundary lines between individuals.

22 Analysis (2/2) A B The corresponding code A (2 students) Similar code fragments were from source code of sample compiler described in textbook. B (4 students) Many code fragments were similar even with respect to name of variables or comments.

23 Conclusions We presented a maintenance support environment based on code clone analysis, Gemini. We also applied it to programming exercise to evaluate its usefulness. We are going to evaluate the applicability of Gemini to large scale software in actual software maintenance as future research work.

24 Suffix-tree Suffix tree is a tree that satisfies the following conditions. 1.A leaf node represents the starting position of sub-string. 2.A path from root node to a leaf node represents a sub-string. 3.First characters of labels of all the edges from one node are different from each other. → A common path means a clone

25 Definition of DFL and RAD DFL(C ) DFL(C) = LEN(C) ×POP(C) - 5×POP(C) + LEN(C) LEN(C) ×POP(C) : the target code size for restructuring 5×POP(C) : the code size of new caller statements LEN(C) : the code size of new identical routine RAD (C ) Distribution in the file system of elements in clone class C RAD(C) = 0 : C is enclosed within a single file. RAD(C) = 1 : C is enclosed within a single directory. RAD(C) = n : C is enclosed within a directory tree of n layers. new sub routine caller statements

26 RSA(i) : Ratio of covered code range in file i by clones between one file i of other files Step2: From among the remaining files, select the most similar file to F and put it next to F by the value of RST RST(i,j) : Ratio of covered code range in file i by clones between a file i and a file j f1 Sorting function Step1: Select a head file by the value of RSA (Make F the head file) Step3: Repeat step2 recursively while any file remains, treating the most similar file in previous step2 as new F f1 f6 f1 f6 f1 f6 f3 f1 f6f3 f4 f2 f5 f2

27 Analysis - reuse of programs (1/3) RST(Parser,Checker) and RST(Checker,SPC) of each student were used as ratio of reused code. RSTParser, CheckerChekcer, SPCave S1S S2S S3S :::: S ave max min

28 Analysis - reuse of programs (2/3) Parser Checker SPC The average of RST of S 1 is the lowest. C : between Parser and Checker D : between Checker and Parser C D Minimum length of clone to be detected was changed to 15 tokens.

29 Analysis - reuse of programs (3/3) Parser Checker SPC S3S3 S2S2 The highest average value of RST S 2 : 0.549, S 3 : Different appearances in scatter plot

30 Parser Checker SPC S 10 S 10 ： The value of DFL(SPC) was very high Parser Checker SPC S9S9 S 9 ： The value of DFL(Parser) was very high Analysis - Usefulness of metric graph Verified the value of DFL from metrics graph DFL(C) = (LEN(C) ×POP(C))– (LEN (C) + 5×POP(C)) DFLParserCheckerSPC S1S :::: S9S S :::: S ave E C D The highest values of DFL in each program