Un modello integrato control-flow e data-flow per il rilevamento ...

40 3. Un modello che integra control flow e data flow
Traccia: (fd@4 = 1), (fd@10 = 1), (fd@11 = 1), (fd@6 = 2), (fd@10 = 2), (fd@11 = 2)
X =fd@4, V = 1
Y = lookup(1) = ∅
CR[fd@4][1] = CR[fd@4][1] ∩ Y = ∅ ∩ ∅ = ∅
Yn = Y ∩ NewArgs(fd@4, 1) = ∅ ∩ ∅ = ∅
CR[fd@4][1] = CR[fd@4][1] ∪ Yn = ∅ ∪ ∅ = ∅
update(fd@4, 1)
X =fd@10, V = 1
Y = lookup(1) = {fd@4}
CR[fd@10][1] = CR[fd@10][1] ∩ Y = ∅ ∩ {fd@4} = ∅
Yn = Y ∩ NewArgs(fd@10, 1) = {fd@4} ∩ {fd@4} = {fd@4}
CR[fd@10][1] = CR[fd@10][1] ∪ Yn = ∅ ∪ {fd@4} = {fd@4}
update(fd@10, 1)
X =fd@11, V = 1
Y = lookup(1) = {fd@10, fd@4}
CR[fd@11][1] = CR[fd@11][1] ∩ Y = ∅ ∩ {fd@10, fd@4} = ∅
Yn = Y ∩ NewArgs(fd@11, 1) = {fd@10, fd@4} ∩ {fd@10, fd@4} = {fd@10, fd@4}
CR[fd@11][1] = CR[fd@11][1] ∪ Yn = ∅ ∪ {fd@10, fd@4} = {fd@10, fd@4}
update(fd@11, 1)
X =fd@6, V = 2
Y = lookup(2) = ∅
CR[fd@6][2] = CR[fd@6][2] ∩ Y = ∅ ∩ ∅ = ∅
Yn = Y ∩ NewArgs(fd@6, 2) = ∅ ∩ {fd@10, fd@11, fd@4} = ∅
CR[fd@6][2] = CR[fd@6][2] ∪ Yn = ∅ ∪ ∅ = ∅
update(fd@6, 2)
X =fd@10, V = 2
Y = lookup(2) = {fd@6}
CR[fd@10][2] = CR[fd@10][2] ∩ Y = ∅ ∩ {fd@6} = ∅
Yn = Y ∩ NewArgs(fd@10, 2) = {fd@6} ∩ {fd@10, fd@11, fd@4, fd@6} = {fd@6}
CR[fd@10][2] = CR[fd@10][2] ∪ Yn = ∅ ∪ {fd@6} = {fd@6}
update(fd@10, 2)
X =fd@11, V = 2
Y = lookup(2) = {fd@10, fd@6}
CR[fd@11][2] = CR[fd@11][2] ∩ Y = ∅ ∩ {fd@10, fd@6} = ∅
Yn = Y ∩ NewArgs(fd@11, 2) = {fd@10, fd@6} ∩ {fd@10, fd@11, fd@4, fd@6} = {fd@10, fd@6}
CR[fd@11][2] = CR[fd@11][2] ∪ Yn = ∅ ∪ {fd@10, fd@6} = {fd@10, fd@6}
update(fd@11, 2)
Figura 3.11: Esecuzione dell’algoritmo su una traccia.