[INSTRUCTIONS]

You are a program-analysis assistant. Perform a **static** data-dependence analysis on a given code snippet, treating each branch or loop condition as potentially taking any outcome, without using semantic or symbolic execution to prune paths.


## 1. Data Dependence Definition

   Data dependence captures the influence of data flow between variables.

   We denote each variable instance as `(var,lineNumber)`, meaning the variable `var` defined or updated at `lineNumber`.

   >  **Direct Data Dependence**
   A variable instance `(varB,lineB)` is **directly** data-dependent on `(varA,lineA)` if `lineA` writes to `varA`. Then, without overwritting the value of `varA`, `lineB` reads `varA` and compute the value of `varB`. In other words, the value of `(varB,lineB)` relies on the value produced at `(varA,lineA)`. In addition, changing the execution order of `(varA,lineA)` and `(varB,lineB)` would alter their results.


   A variable instance `(varB,lineB)` is data-dependent on `(varA,lineA)` if there is a **transitive** (indirect) chain of **direct** data dependencies from `(varA,lineA)` to `(varB,lineB)`. This is equivalent to saying that `(varA,lineA)` has data dependence over `(varB,lineB)`, meaning the value written at `(varA,lineA)` can propagate to `(varB,lineB)` through a sequence of read/write operations.


## 2. Output Format
   When asked "Which variable instances have data dependence over `(targetVar, targetLine)`? List all such variables.", respond:
   ```json
   {
    "DataDependenceSources": [
      ["valA", lineA],
      ["valB", lineB],
      ...
    ]
   }
   ```

  If you believe there is no variables have data dependence over `(targetVar, targetLine)`, respond:
   ```json
   {
    "DataDependenceSources": []
   }
   ```
  

## 3. Intraprocedural Data Dependence
   All dependence analysis is performed within **a single function**. We do not track dependencies across function boundaries. The analysis only applies to variables and control structures inside the **specified function**.

## 4. Example Code Snippet

### Example 1

```python
1    total = 0
2    value = 1
3    step = value
4    if step > 1:
5        value += 3
6    while total <= 10:
7        total += value
8        difference = total - step
9        step += 1
10   final_result = total * 2
```


#### Example Question 1.1:
Which variable instances have data dependence over `(step,9)`? List all such variables.


**Analysis**:
- Line 9: `step += 1`, meaning `(step,9)` is directly data-dependent on `(step,3)` (or `(step,9)` itself) because step is updated based on its previous value.
- Line 3: `step = value`, meaning `(step,3)` is directly data-dependent on `(value,2)`.
Therefore, there exists a transitive data dependence chain from `(value,2)` to `(step,9)` through `(step,3)`. 


**Output**:
```json
   {
    "DataDependenceSources": [
      ["step", 9],
      ["step", 3],
      ["value", 2],
    ]
   }
```





#### Example Question 1.2 
Which variable instances have data dependence over `(total,7)`? List all such variables.


**Analysis**:
- Line 7: `total += value`, meaning `(total,7)` reads from `total` at line 1 or 7 (itself), and `value` from either `(value,2)` or `(value,5)`.
- Line 5: `value` is updated in `value += 3`, meaning `(value,5)` depends on `(value,2)` (or `(value,5)` itself). However, this update is inside an if statement, which means it may or may not execute depending on runtime conditions.
- Line 2: value is initialized at `(value,2)`.


At this point, whether `(total,7)` depends on `(value,5)` depends on whether line 4 (`if step>1`) is `true`. Since this is a static analysis, all possible paths are considered without analyzing actual reachability. This means line 5 is treated as both possibly executed and possibly not executed.

- If line 4 evaluates to `true`, `(total,7)` depends on `(value,5)`, forming the trace: `(value,2) -> (value,5) -> (total,7)`. 
- If line 4 evaluates to `false`, `(total,7)` directly depends on `(value,2)`, forming the trace: `(value,2) -> (total,7)`



**Output**:
```json
   {
    "DataDependenceSources": [
      ["total", 1],
      ["total", 7],
      ["value", 5],
      ["value", 2]
    ]
   }
```



### Example 2

```python
1    arr = [1, 2, 3]
2    x = 5
3    if x > 2:
4        arr[0] = x   
5    for i in range(3):
6        arr[i] += 1  
7        temp = arr[i]  
8        y = temp + 1  
9    result = arr[-1]
```

#### Example Question 2.1:
Which variable instances have data dependence over `(arr,6)`? List all such variables.



**Analysis**
- Line 6: `arr[i] += 1` modifies `arr[i]`, but i varies during the loop execution.
   - If `i == 0`, `arr[i]` refers to `arr[0]`, which was updated in line 4 (or line 6 itself), establishing a dependence chain `(arr,4)` -> `(arr,6)`.
   - If `i != 0`, `arr[i]` does not refer to `arr[0]`, meaning it depend on `(arr,1)` (or `(arr,6)` itself), not `(arr,4)`.
   - However, since static analysis considers all possible paths without resolving i’s runtime value, we must assume `arr[i]` could be `arr[0]`, leading to a possible dependence.
- Line 4: `arr[0] = x`, meaning `(arr,4)` depends on `(x,2)`.
- Line 2: `x` is initialized at `(x,2)`.




**Output**:
```json
   {
    "DataDependenceSources": [
      ["arr", 6],
      ["arr", 4],
      ["arr", 1],
      ["i", 5],
      ["x", 2]
    ]
   }
```


#### Example Question 2.2:
Which variable instances have data dependence over `(temp,7)`? List all such variables.


**Analysis**:
- Line 7: `temp = arr[i]`, meaning temp depends on `i`, since `i` determines which element of arr is accessed. And `arr[i]` can only refer to `(arr,6)` as they have the same index.
- Line 5: `i` is initialized and iterates over the range 0 to 3.


**Output**:
```json
   {
    "DataDependenceSources": [
      ["arr", 6],
      ["i", 5],
    ]
   }
```

#### Example Question 2.3:
Which variable instances have data dependence over `(result,9)`? List all such variables.

**Analysis**:
- Line 9: `result = arr[-1]`, meaning result depends on `arr[-1]`, which is arr[2], possibly get updated at line 6 (or line 1).
  - If it is from line 6: `arr[i] += 1`, `arr[i]` is modified based on the value of `i`. Line 5: `i` iterates over 0 to 3.
  - If it is from line 1: `arr = [1, 2, 3]`, it is initialized at line 1 without any other data dependencies.

**Output**:
```json
   {
    "DataDependenceSources": [
      ["arr", 6],
      ["arr", 1],
      ["i", 5],
    ]
   }
```

---

[YOUR TURN]

Below is **your target snippet**. 

```Python
1   import sys,math,collections
2   from collections import defaultdict
3   def file():
4       sys.stdin = open('input.py', 'r')
5       sys.stdout = open('output.py', 'w') 
6   def get_array():
7       l=list(map(int, input().split()))
8       return l
9   def get_ints():   
10      return map(int, input().split())
11  def get_3_ints():   
12      a,b,c=map(int, input().split())
13      return a,b,c    
14  def sod(n):
15      n,c=str(n),0
16      for i in n: 
17          c+=int(i)
18      return c    
19  def isPrime(n):
20      if (n <= 1):
21          return False
22      if (n <= 3):
23          return True
24      if (n % 2 == 0 or n % 3 == 0):
25          return False
26      i = 5
27      while(i * i <= n):
28          if (n % i == 0 or n % (i + 2) == 0):
29              return False
30          i = i + 6
31      return True
32  def getFloor(A, x):
33      (left, right) = (0, len(A) - 1)
34      floor = -1
35      while left <= right:
36          mid = (left + right) // 2
37          if A[mid] == x:
38              return A[mid]
39          elif x < A[mid]:
40              right = mid - 1
41          else:
42              floor = A[mid]
43              left = mid + 1
44      return floor
45  def chk(aa,bb):
46  	f=0
47  	for i in aa:
48  		for j in bb:
49  			if(j[0]>=i[0] and j[1]<=i[1]):
50  				f+=1
51  			elif(j[0]<=i[0] and j[1]>=i[1]):	
52  				f+=1
53  			elif(i[0]==j[1] or i[1]==j[0]):
54  				f+=1
55  			else:
56  				continue
57  	return f	
58  def maxSumRangeQuery(nums, req):
59      l = []
60      for _ in range(len(nums)+1):
61          l.append(0)
62      nums.sort(reverse=True)
63      for i in req:
64          l[i[0]]+=1
65          l[i[1]+1]-=1
66      for i in range(1,len(l)):
67          l[i]+=l[i-1]
68      l=l[:-1]    
69      d=collections.defaultdict(list)
70      for i in range(len(l)):
71          d[l[i]].append(i)
72      di=collections.OrderedDict(sorted(d.items()))   
73      k=0
74      ans = []
75      for _ in range(len(nums)):
76          ans.append(0)
77      for i in di:
78          for j in di[i]:
79              ans[j]=nums[len(nums)-k-1]
80              k+=1
81      c=0
82      for i in req:
83          st=ans[i[0]:i[1]+1]
84          c+=sum(st)
85      return c%(10**9+7)
86  def main():
87  	c=0
88  	a,b=get_ints()
89  	while(a>0):
90  		a-=b
91  		c+=1
92  	print(c)	
93  if __name__ == '__main__':
94      main()
```


**Question**: Which variable instances have data dependence over `(ans,79)` in function `maxSumRangeQuery`? List all such variables.

**Output**:


Ground truth answer: yes