1. Portability by Automatic Translation: Two Case Studies Yishai A. Feldman The Interdisciplinary Center Herzliya, Israel

2. First Case: Bogart Large-Scale Translation from Assembly Language to C Joint Work with Doron A. Friedman

3. The Problem u 400,000 lines of IBM 370 assembly code u Customers downsizing mainframes u Hand-optimized code over 15 calendar years u Live system

4. Success Criteria u Portability u Efficiency u Minimum manual work BUT u Readability is not important

5. Difficult Assembly Features u Registers u Condition code u Untyped language u Unstructured code u Large unstructured memory areas u Portability: u Different byte order u Different word size u Different pointer size

6. The Simulating Translator STM R14,R12,12(R13) LR R12,R15 USING HORNER,R12 ST R13,SAV+4 LA R13,SAV LA R7,COEF L R5,0(R7) LA R9,0 LOOP CR R9,R2 BNL OUT LA R9,1(R9) LA R7,4(R7) MR R4,R3 A R5,0(R7) B LOOP OUT LR R0,R5 LM R1,R12,24(R13) BR R14 void HORNER(tagSAPReg *Reg) { T_stm(14,12,((Reg[13].ucp+12)),Reg); Reg[12].sw = Reg[15].sw ; SAV[1] = Reg[13].sw ; Reg[13].pv = &(SAV[0]) ; Reg[7].pv = &(COEF[0]) ; Reg[5].sw = *(sWord *)Reg[7].ucp; Reg[9].sw = 0 ; LOOP: if ((Reg[9].sw) >= Reg[2].sw) goto OUT; Reg[9].sw += 1; Reg[7].sw += 4; T_mult(&Reg[4],Reg[3].sw) ; Reg[5].sw += *((sWord *)(Reg[7].ucp)); goto LOOP ; OUT: Reg[0].sw = Reg[5].sw; T_lm(1,12,((Reg[13].ucp+24)),Reg); return; }

7. Bogart Better Optimizing General-purpose Abstract Representation Translator

8. Translation by Abstraction, Transformation, and Reimplementation u Control-flow and data-flow analysis u Typing by constraint propagation u Automatic cliche recognition Abstraction Transformation Re-implementation

9. The Code Produced by Bogart void HORNER(tagSAPReg *Reg) { T_stm(14,12,((Reg[13].ucp+12)),Reg); Reg[12].sw = Reg[15].sw ; SAV[1] = Reg[13].sw ; Reg[13].pv = &(SAV[0]) ; Reg[7].pv = &(COEF[0]) ; Reg[5].sw = *(sWord *)Reg[7].ucp; Reg[9].sw = 0 ; LOOP: if ((Reg[9].sw) >= Reg[2].sw) goto OUT; Reg[9].sw += 1; Reg[7].sw += 4; T_mult(&Reg[4],Reg[3].sw) ; Reg[5].sw += *((sWord *)(Reg[7].ucp)); goto LOOP ; OUT: Reg[0].sw = Reg[5].sw; T_lm(1,12,((Reg[13].ucp+24)),Reg); return; } sWord HORNER(sWord r2sw, sWord r3sw) { sWord r5sw; sWordPtr r7swp; sWord r9sw; r7swp = (sWord *)(&COEF[0]); r5sw = *r7swp; r9sw = 0; while (r9sw < r2sw) { r9sw++; r7swp++; r5sw = r5sw*r3sw + *r7swp; } return r5sw; }

10. Accumulating Compound Expressions L R11,NIG L R5,0(R4) BAL R14,INCTAB LPR R7,R0 MR R2,R7 LR R0,R3 BR R14 Reg[11].sw = NIG; Reg[5].sw = *(sWord *)Reg[4].ucp; INCTAB(Reg); Reg[7].sw = labs(Reg[0].sw); T_mult(&Reg[2], Reg[7].sw); Reg[0].sw = Reg[3].sw; return; return r3sw * labs(INCTAB(NIG,(*r4swp))); Bogart Assembly Simulating translator

11. Example: Condition Code Support CGLOOP CH R7,0(R5,R4) SRL R2,1 BH CGADD BNH CGSUB Assembly if (Reg[7].sw == *((sHalf *)((Reg[4].ucp+Reg[5].sw)))) __CC = _CZero; else if (Reg[7].sw < *((sHalf *)((Reg[4].ucp+Reg[5].sw)))) __CC = _COne; else __CC = _CTwo; Reg[2].uw >>= 1; if (__CC & 0x4) goto CGADD; if (__CC & 0x3) goto CGSUB; Simulating translator Bogart r2sh >>= 1; temp = r4ucp + r5sh; if (r7sh > temp) goto CGADD; if (r7sh <= temp) goto CGSUB;

12. The Plan Representation CGR CH R2,GMF BL CONGR SRL R2,1 B CGR CONGR....

13. Global Type Analysis by Constraint Propagation

14. Time and Space Comparison Bogart and Simulating Translator Simulator Bogart Time (sec.) Space (bytes) BIN 63 4170 33 2802 HORNER10 3302 3 2465 RANDOM 9 5447 4 2741 SAPDBMS18 41700 9 29073 ( SAPDBMS is a central Sapiens module)

15. Time Performance on Several Platforms (For example routine BIN) IBM 370 RS/6000 AS/400 PC (DOS) 0.32— — — Original Assembly Simulator 1.741.91failed1.26 Bogart 1111 Hand Crafted 0.910.970.491.07

16. Results u Bogart produces more portable code u Bogart supports a larger portion of the source language u Bogart requires less manual work in code preparation u Bogart produces more efficient code in terms of time and space performance

17. Conclusions u Translation by abstraction produces better results than simulation on all criteria u Simulation is simpler and faster to implement u Simulated code is easier for the programmers to debug u The advantages of the abstraction approach grow in the long term u “Research-then-transfer” versus “Industry-as- laboratory” (Colin Potts, 1993)

18. New Developments: Bogart  Falcon 2000

19. Second Case: MIDAS Automatic High-Quality Reengineering of Database Programs by Temporal Abstraction Joint Work with Yossi Cohen

20. The Problem Legacy Database Software u Much legacy software is DP, many database- related programs u Conversion from older models (indexed- sequential, hierarchical, network) to relational/object-oriented databases u Need to convert: u Schema u Data u Software

21. Network vs. Relational Databases

22. Network Database Program (1) 01 MOVE 0 TO STATUS1. 02 PERFORM UNTIL STATUS1 IS NOT EQUAL TO ZERO 03 FETCH NEXT STUDENT WITHIN DEPT-OF-STUDENT 04 AT END MOVE 1 TO STATUS1 05 IF STATUS1 IS EQUAL TO 0 THEN 06 IF STUDENT-DEGREE IS EQUAL TO 2 THEN 07 MOVE 0 TO GRADES-SUM 08 MOVE 0 TO GRADES-COUNT 09 PERFORM SUM-STUDENT-GRADES 10 DIVIDE GRADES-SUM BY GRADES-COUNT 11 GIVING GRADES-AVG 12 IF GRADES-AVG > 95 THEN 13 DISPLAY..., GRADES-AVG 14 END-IF 15 END-IF 16 END-IF 17 END-PERFORM.

23. Network Database Program (2) 18 SUM-STUDENT-GRADES. 19 MOVE 0 TO STATUS2 20 PERFORM UNTIL STATUS2 IS NOT EQUAL TO ZERO 21 FETCH NEXT GRADES WITHIN STUDENT-OF-GRADES 22 AT END MOVE 1 TO STATUS2 23 IF STATUS2 IS EQUAL TO 0 THEN 24 ADD GRD-GRADE TO GRADES-SUM 25 ADD 1 TO GRADES-COUNT 26 END-IF 27 END-PERFORM.

24. Naive Translation (1) 01 EXEC SQL DECLARE CRS1 CURSOR FOR 02 SELECT... FROM STUDENT 03 WHERE DEPT-NAME = :DEPT-NAME 04 END-EXEC. 05 EXEC SQL DECLARE CRS2 CURSOR FOR 06 SELECT... FROM GRADES 07 WHERE STUDENT-ID = :STUDENT-ID 08 END-EXEC.

25. Naive Translation (2) 09 MOVE 0 TO STATUS1 10 EXEC SQL OPEN CRS1 END-EXEC 11 PERFORM UNTIL STATUS1 IS NOT EQUAL TO 0 12 EXEC SQL FETCH CRS1 INTO... END-EXEC. 13 IF SQL-STATUS = SQL-NOT-FOUND THEN MOVE 1 TO STATUS1. 14 IF STATUS1 IS EQUAL TO 0 THEN 15 IF STUDENT-DEGREE IS EQUAL TO 2 THEN 16 MOVE 0 TO GRADES-SUM 17 MOVE 0 TO GRADES-COUNT 18 PERFORM SUM-STUDENT-GRADES 19 DIVIDE GRADES-SUM INTO GRADES-COUNT GIVING GRADES-AVG 20 IF GRADES-AVG > 95 THEN 21 DISPLAY..., GRADES-AVG 22 END-IF 23 END-IF 24 END-IF 25 END-PERFORM. 26 EXEC SQL CLOSE CRS1 END-EXEC.

26. Naive Translation (3) 27 SUM-STUDENT-GRADES. 28 MOVE 0 TO STATUS2 29 EXEC SQL OPEN CRS2 END-EXEC. 30 PERFORM UNTIL STATUS2 IS NOT EQUAL TO 0 31 EXEC SQL FETCH CRS2 INTO... END-EXEC. 32 IF SQL-STATUS = SQL-NOT-FOUND 33 THEN MOVE 1 TO STATUS2. 34 IF STATUS2 IS EQUAL TO 0 THEN 35 ADD GRD-GRADE TO GRADES-SUM 36 ADD 1 TO GRADES-COUNT 37 END-IF 38 END-PERFORM. 39 EXEC SQL CLOSE CRS2 END-EXEC.

27. MIDAS: Translation by Abstraction, Transformation, and Re-implementation Abstraction Temporal Abstraction Re-implementation Network DB code Relational DB code Plan Temporal Plan

28. MIDAS Translation 01 EXEC SQL DECLARE CRS1 CURSOR FOR 02 SELECT STUDENT.STUDENT-ID, FIRST-NAME, LAST-NAME, AVG(GRADE) 03 FROM STUDENT, GRADES 04 WHERE DEGREE = 2 05 AND DEPT-NAME = :DEPT-NAME 06 AND GRADES.STUDENT-ID = STUDENT.STUDENT-ID 07 GROUP BY STUDENT.STUDENT-ID, FIRST-NAME, LAST-NAME 08 HAVING AVG(GRADE) > 95 09 END-EXEC. 10 PERFORM UNTIL SQL-STATUS = SQL-NOT-FOUND 11 EXEC SQL FETCH CRS1 INTO... END-EXEC. 12 DISPLAY..., GRADES-AVG 13 END-PERFORM

29. The Internal Representation: Query Graphs u Temporal abstraction u Generate / Join u Filter u Map u Aggregate u Wide-spectrum formalism

30. Filtering Transformation

31. Join-Down Transformation

32. Accumulation Transformation

33. Performance Results

34. Conclusions u Translation by abstraction, transformation, and re-implementation demonstrated in two domains u Query graphs as abstraction for database operations u Adapts to different schema transformations u Scalability

35. Conclusions and Future Work u Appropriate domain u Same host language u Few cliches give wide coverage u Important commercially u Generalizations u Other legacy models u OODB / 4GL as targets

36. Questions? Papers can be downloaded from http://www.idc.ac.il/yishai