1. Carnegie Mellon 1 This Week: Integers Integers  Representation: unsigned and signed  Conversion, casting  Expanding, truncating  Addition, negation, multiplication, shifting Summary

2. Carnegie Mellon 2 Sign Extension Task:  Given w-bit signed integer x  Convert it to w+k-bit integer with same value Rule:  Make k copies of sign bit:  X = x w–1,…, x w–1, x w–1, x w–2,…, x 0 k copies of MSB X X w w k

3. Carnegie Mellon 3 Sign Extension Example Converting from smaller to larger integer data type C automatically performs sign extension short int x = 15213; int ix = (int) x; short int y = -15213; int iy = (int) y;

4. Carnegie Mellon 4 Summary: Expanding, Truncating: Basic Rules Expanding (e.g., short int to int)  Unsigned: zeros added  Signed: sign extension  Both yield expected result Truncating (e.g., unsigned to unsigned short)  Unsigned/signed: bits are truncated  Result reinterpreted  Unsigned: mod operation  Signed: similar to mod  For small numbers yields expected behaviour

5. Carnegie Mellon 5 This Week: Integers Integers  Representation: unsigned and signed  Conversion, casting  Expanding, truncating  Addition, negation, multiplication, shifting Summary

6. Carnegie Mellon 6 Negation: Complement & Increment Claim: Following Holds for 2’s Complement ~x + 1 == -x Complement  Observation: ~x + x == 1111…111 == -1 10010111 x 01101000 ~x+ 11111111

7. Carnegie Mellon 7 Complement & Increment Examples x = 15213 x = 0

8. Carnegie Mellon 8 Unsigned Addition Standard Addition Function  Ignores carry output Implements Modular Arithmetic s= UAdd w (u, v)=u + v mod 2 w u v + u + v True Sum: w+1 bits Operands: w bits Discard Carry: w bits UAdd w (u, v)

9. Carnegie Mellon 9 Visualizing (Mathematical) Integer Addition Integer Addition  4-bit integers u, v  Compute true sum Add 4 (u, v)  Values increase linearly with u and v  Forms planar surface Add 4 (u, v) u v

10. Carnegie Mellon 10 Visualizing Unsigned Addition Wraps Around  If true sum ≥ 2 w  At most once 0 2w2w 2 w+1 UAdd 4 (u, v) u v True Sum Modular Sum Overflow

11. Carnegie Mellon 11 Mathematical Properties Modular Addition Forms an Abelian Group  Closed under addition 0  UAdd w (u, v)  2 w –1  Commutative UAdd w (u, v) = UAdd w (v, u)  Associative UAdd w (t, UAdd w (u, v)) = UAdd w (UAdd w (t, u ), v)  0 is additive identity UAdd w (u, 0) = u  Every element has additive inverse  Let UComp w (u ) = 2 w – u UAdd w (u, UComp w (u )) = 0

12. Carnegie Mellon 12 Two’s Complement Addition TAdd and UAdd have Identical Bit-Level Behavior  Signed vs. unsigned addition in C: int s, t, u, v; s = (int) ((unsigned) u + (unsigned) v); t = u + v  Will give s == t u v + u + v True Sum: w+1 bits Operands: w bits Discard Carry: w bits TAdd w (u, v)

13. Carnegie Mellon 13 TAdd Overflow Functionality  True sum requires w+1 bits  Drop off MSB  Treat remaining bits as 2’s comp. integer –2 w –1 –1 –2 w 0 2 w –1 True Sum TAdd Result 1 000…0 1 011…1 0 000…0 0 100…0 0 111…1 100…0 000…0 011…1 PosOver NegOver

14. Carnegie Mellon 14 Visualizing 2’s Complement Addition Values  4-bit two’s comp.  Range from -8 to +7 Wraps Around  If sum  2 w–1  Becomes negative  At most once  If sum < –2 w–1  Becomes positive  At most once TAdd 4 (u, v) u v PosOver NegOver

15. Carnegie Mellon 15 Characterizing TAdd Functionality  True sum requires w+1 bits  Drop off MSB  Treat remaining bits as 2’s comp. integer u v < 0> 0 < 0 > 0 Negative Overflow Positive Overflow TAdd(u, v)

16. Carnegie Mellon 16 Mathematical Properties of TAdd Isomorphic Group to unsigneds with UAdd  TAdd w (u, v) = U2T(UAdd w (T2U(u ), T2U(v)))  Since both have identical bit patterns Two’s Complement Under TAdd Forms a Group  Closed, Commutative, Associative, 0 is additive identity  Every element has additive inverse

17. Carnegie Mellon 17 Multiplication Computing Exact Product of w-bit numbers x, y  Either signed or unsigned Ranges  Unsigned: 0 ≤ x * y ≤ (2 w – 1) 2 = 2 2w – 2 w+1 + 1  Up to 2w bits  Two’s complement min: x * y ≥ (–2 w–1 )*(2 w–1 –1) = –2 2w–2 + 2 w–1  Up to 2w–1 bits  Two’s complement max: x * y ≤ (–2 w–1 ) 2 = 2 2w–2  Up to 2w bits, but only for (TMin w ) 2 Maintaining Exact Results  Would need to keep expanding word size with each product computed  Done in software by “arbitrary precision” arithmetic packages

18. Carnegie Mellon 18 Unsigned Multiplication in C Standard Multiplication Function  Ignores high order w bits Implements Modular Arithmetic UMult w (u, v)=u · v mod 2 w u v * u · v True Product: 2*w bits Operands: w bits Discard w bits: w bits UMult w (u, v)

19. Carnegie Mellon 19 Code Security Example #2 SUN XDR library  Widely used library for transferring data between machines void* copy_elements(void *ele_src[], int ele_cnt, size_t ele_size); ele_src malloc(ele_cnt * ele_size)

20. Carnegie Mellon 20 XDR Code void* copy_elements(void *ele_src[], int ele_cnt, size_t ele_size) { /* * Allocate buffer for ele_cnt objects, each of ele_size bytes * and copy from locations designated by ele_src */ void *result = malloc(ele_cnt * ele_size); if (result == NULL) /* malloc failed */ return NULL; void *next = result; int i; for (i = 0; i < ele_cnt; i++) { /* Copy object i to destination */ memcpy(next, ele_src[i], ele_size); /* Move pointer to next memory region */ next += ele_size; } return result; }

21. Carnegie Mellon 21 XDR Vulnerability What if:  ele_cnt = 2 20 + 1  ele_size = 4096 = 2 12  Allocation= ?? How can I make this function secure? malloc(ele_cnt * ele_size)

22. Carnegie Mellon 22 Signed Multiplication in C Standard Multiplication Function  Ignores high order w bits  Some of which are different for signed vs. unsigned multiplication  Lower bits are the same u v * u · v True Product: 2*w bits Operands: w bits Discard w bits: w bits TMult w (u, v)

23. Carnegie Mellon 23 Power-of-2 Multiply with Shift Operation  u << k gives u * 2 k  Both signed and unsigned Examples  u << 3==u * 8  u << 5 - u << 3==u * 24  Most machines shift and add faster than multiply  Compiler generates this code automatically 001000 u 2k2k * u · 2 k True Product: w+k bits Operands: w bits Discard k bits: w bits UMult w (u, 2 k ) k 000 TMult w (u, 2 k ) 000

24. Carnegie Mellon 24 leal(%eax,%eax,2), %eax sall$2, %eax Compiled Multiplication Code C compiler automatically generates shift/add code when multiplying by constant int mul12(int x) { return x*12; } t <- x+x*2 return t << 2; C Function Compiled Arithmetic OperationsExplanation

25. Carnegie Mellon 25 Unsigned Power-of-2 Divide with Shift Quotient of Unsigned by Power of 2  u >> k gives  u / 2 k   Uses logical shift 001000 u 2k2k / u / 2 k Division: Operands: k 000  u / 2 k  Result:. Binary Point 0 0000

26. Carnegie Mellon 26 shrl$3, %eax Compiled Unsigned Division Code Uses logical shift for unsigned For Java Users  Logical shift written as >>> unsigned udiv8(unsigned x) { return x/8; } # Logical shift return x >> 3; C Function Compiled Arithmetic Operations Explanation

27. Carnegie Mellon 27 Signed Power-of-2 Divide with Shift Quotient of Signed by Power of 2  x >> k gives  x / 2 k   Uses arithmetic shift  Rounds wrong direction when u < 0 001000 x 2k2k / x / 2 k Division: Operands: k 0 RoundDown(x / 2 k ) Result:. Binary Point 0

28. Carnegie Mellon 28 Correct Power-of-2 Divide Quotient of Negative Number by Power of 2  Want  x / 2 k  (Round Toward 0)  Compute as  (x+ 2 k -1)/ 2 k   In C: (x + (1 > k  Biases dividend toward 0 Case 1: No rounding Divisor: Dividend: 001000 u 2k2k /  u / 2 k  k 1 000 1 011. Binary Point 1 000111 +2 k –1 111 1 111 Biasing has no effect

29. Carnegie Mellon 29 Correct Power-of-2 Divide (Cont.) Divisor: Dividend: Case 2: Rounding 001000 x 2k2k /  x / 2 k  k 1 1 011. Binary Point 1 000111 +2 k –1 1 Biasing adds 1 to final result Incremented by 1

30. Carnegie Mellon 30 testl %eax, %eax jsL4 L3: sarl$3, %eax ret L4: addl$7, %eax jmpL3 Compiled Signed Division Code Uses arithmetic shift for int For Java Users  Arith. shift written as >> int idiv8(int x) { return x/8; } if x < 0 x += 7; # Arithmetic shift return x >> 3; C Function Compiled Arithmetic Operations Explanation

31. Carnegie Mellon 31 Arithmetic: Basic Rules Addition:  Unsigned/signed: Normal addition followed by truncate, same operation on bit level  Unsigned: addition mod 2 w  Mathematical addition + possible subtraction of 2w  Signed: modified addition mod 2 w (result in proper range)  Mathematical addition + possible addition or subtraction of 2 w Multiplication:  Unsigned/signed: Normal multiplication followed by truncate, same operation on bit level  Unsigned: multiplication mod 2 w  Signed: modified multiplication mod 2 w (result in proper range)

32. Carnegie Mellon 32 Arithmetic: Basic Rules Unsigned ints, 2’s complement ints are isomorphic rings: isomorphism = casting Left shift  Unsigned/signed: multiplication by 2 k  Always logical shift Right shift  Unsigned: logical shift, div (division + round to zero) by 2 k  Signed: arithmetic shift  Positive numbers: div (division + round to zero) by 2 k  Negative numbers: div (division + round away from zero) by 2 k Use biasing to fix

33. Carnegie Mellon 33 This Week: Integers Integers  Representation: unsigned and signed  Conversion, casting  Expanding, truncating  Addition, negation, multiplication, shifting Summary

34. Carnegie Mellon 34 Properties of Unsigned Arithmetic Unsigned Multiplication with Addition Forms Commutative Ring  Addition is commutative group  Closed under multiplication 0  UMult w (u, v)  2 w –1  Multiplication Commutative UMult w (u, v) = UMult w (v, u)  Multiplication is Associative UMult w (t, UMult w (u, v)) = UMult w (UMult w (t, u ), v)  1 is multiplicative identity UMult w (u, 1) = u  Multiplication distributes over addtion UMult w (t, UAdd w (u, v)) = UAdd w (UMult w (t, u ), UMult w (t, v))

35. Carnegie Mellon 35 Why Should I Use Unsigned? Don’t Use Just Because Number Nonnegative  Easy to make mistakes unsigned i; for (i = cnt-2; i >= 0; i--) a[i] += a[i+1];  Can be very subtle #define DELTA sizeof(int) int i; for (i = CNT; i-DELTA >= 0; i-= DELTA)... Do Use When Performing Modular Arithmetic  Multiprecision arithmetic Do Use When Using Bits to Represent Sets  Logical right shift, no sign extension