Skip to main content
Que➤ Write a function which will Reverse the given linked list.



Comments

Post a Comment

Popular Posts

Adaptive Software Development (ASD)

Adaptive Software Development (ASD) :- Adaptive Software Development(ASD) has been proposed by Jim High smith as technique for building complex software and system. ASD focus on human collaboration and team self-organization. Jim High smith defines an ASD "Life Cycle" that consist of three phases  Speculation Collaboration learning  During speculation, the project is initiated and adaptive cycle planning is conducted. Adaptive cycle planning uses project Initiation information,the customer's mission statement ,basic requirements and project constraint to define the set of release cycles that will be required for the project. Collaboration encompasses communication and team-work but it also enphasizes individualism because individual creativity plays an important role in collaborative thinking.It is all above all,a matter of trust. people working together must trust one another to comment without war help without irritation work as hard as ...
Post a Comment
Read more

Kruskal’s Minimum Spanning Tree Algorithm & Programme

PROBLEM :                  Kruskal's algorithm is a minimum-spanning-tree algorithm which finds an edge of the least possible weight that connects any two trees in the forest. It is a greedy algorithm in graph theory as it finds a minimum spanning tree for a connected weighted graph adding increasing cost arcs at each step. To understand Kruskal's algorithm let us consider the following example − Step 1 - Remove all loops and Parallel Edges Remove all loops and parallel edges from the given graph. In case of parallel edges, keep the one which has the least cost associated and ove all others. Step 2 - Arrange all edges in their increasing order of weight The next step is to create a set of edges and weight, and arrange them in an ascending order of weightage (cost). Step 3 - Add the edge which has the least weightage Now we start adding edges to the graph beginning from the one which has the least weight. Th...
Post a Comment
Read more

Dynamic Programming - 0/1 Knapsack Problem

➤ Greedy algo does not give optimal solution everytime.       Exa. Consider  n=3 and Capacity W=30               w={20,10,5}               p={180,80,50}               p/w={9,8,10}               greedy solution={1,0,1} ➝ profit =180+50=230               optimal solution={1,1,0} ➝ profit=180+80=260 Algo :-  w[i] gives weight of ith item. p[i] gives value(profit) of ith item. sol[i][j] gives the maximum profit for i items and j capacity(sub problem) Use Desktop Version Of This Site For Better View. for(j=0 to m) ➝ No Capicity No Packets      sol[0][j]=0 for(i=0 to m) ➝ No Items      sol[i][0]=0 for(i=1 to n)       for(j=1 to m)           if(w[i] > j)      ...
Post a Comment
Read more