好的,以下是一个Python代码优化示例,它可以自动对输入的四元式进行基本块的划分,并对基本块内的代码利用DAG进行优化,生成优化后的四元式代码,并且可视化基本块和DAG图:
```python
import networkx as nx
import matplotlib.pyplot as plt
# 定义一个函数来划分基本块
def basic_block_division(quads):
basic_blocks = []
current_block = []
for quad in quads:
if len(current_block) == 0 or current_block[-1][0] == 'goto':
# 如果当前块为空或者上一条指令是跳转指令,则新建一个基本块
current_block.append(quad)
basic_blocks.append(current_block)
current_block = []
else:
current_block.append(quad)
if len(current_block) > 0:
# 将最后一个基本块添加到基本块列表中
basic_blocks.append(current_block)
return basic_blocks
# 定义一个函数来生成DAG
def generate_dag(basic_block):
dag = {}
for quad in basic_block:
if quad[0] == '=':
# 如果是赋值语句,则将右侧的变量作为父节点,左侧的变量作为子节点
if quad[3] not in dag:
dag[quad[3]] = []
dag[quad[3]].append(quad[1])
else:
# 如果不是赋值语句,则将所有变量作为父节点
for var in quad[1:]:
if var not in dag:
dag[var] = []
return dag
# 定义一个函数来优化基本块内的代码
def optimize_basic_block(basic_block):
dag = generate_dag(basic_block)
# 将DAG中只有一个父节点的节点替换为其父节点
for node in dag:
if len(dag[node]) == 1:
parent = dag[node][0]
for quad in basic_block: