Answer:
There are multiple critical paths
Explanation:
The critical path method (CPM), or critical path analysis (CPA), is an algorithm for scheduling a set of project activities. It is commonly used in conjunction with the program evaluation and review technique (PERT). A critical path is determined by identifying the longest stretch of dependent activities and measuring the time required to complete them from start to finish.
The essential technique for using CPM is to construct a model of the project that includes the following:
- A list of all activities required to complete the project (typically categorized within a work breakdown structure),
- The time (duration) that each activity will take to complete,
- The dependencies between the activities and,
- Logical end points such as milestones or deliverable items.
Using these values, CPM calculates the longest path of planned activities to logical end points or to the end of the project, and the earliest and latest that each activity can start and finish without making the project longer. This process determines which activities are "critical" (i.e., on the longest path) and which have "total float" (i.e., can be delayed without making the project longer).
considering the above function of the cpm analysis because you have multiple path, there is tendency that more than path through the project network will have zero slack values.
You will type
400*2*1.5
1.5 is another way to say 1 1/2
Multiple inheritance causes Diamond problem which happens when:
Class A is parent of class B and C
Now when class D will be inherited from both Class B and C it will have all the members of class A and B which if same will confuse the compiler to import which one?
C++ solves it by using virtual keyword with them and thus telling the compiler which one to inherit.
Java has introduced the interface concept rather then allowing multiple inheritance.
Answer:
Check the explanation
Explanation:
# Step 1
the first thing to execute will be......
f = open("states.txt")
# Step 2
the second step is......
states = []
for line in f:
states.append(line.strip())
# Step 3:
the third step is to......
for state in sorted(states):
print(state)
f.close()
Answer:
This is the case of redundancy or the repeated data. It means that the same data is being repeated again and again. And its the wastage of time and memory both. The redundancy must be removed in all circumstances. However, we cannot as without it proper normalization of data is not possible.
Explanation:
The answer is self explanatory.
