Method and system for identifying common requirements from applications

1. A method for identifying common requirements from applications, the method comprising:

receiving, by a requirements identification device, a plurality of requirements from

a plurality of applications, wherein each of the plurality of requirements corresponds to a functionality in one of the plurality of applications, and wherein the plurality of requirements are identified from the plurality of applications through a code analysis technique;

for at least two of the plurality of requirements,

determining, by the requirements identification device, a similarity index

through each of a set of analysis techniques, wherein the set of analysis techniques comprises a process driven analysis technique, a data driven analysis technique, and a consumer driven analysis technique;

calculating, by the requirements identification device, a final similarity index based on the similarity index determined through each of a set of analysis techniques, wherein the final similarity index is a weighted average of the similarity index determined through each of a set of analysis techniques;

generating, by the requirements identification device, a similarity matrix for the plurality of requirements based on the final similarity index, wherein elements of the

similarity matrix are final similarity indices corresponding to the plurality of requirements; and

generating, by the requirements identification device, a hierarchical cluster tree for the plurality of requirements based on the final similarity index corresponding to each of the plurality of requirements; and

identifying at least one cluster of requirements from the plurality of requirements through the hierarchical cluster tree, wherein the at least one cluster of requirements

comprises each of the at least two of the plurality of requirements, wherein for each of the at least one cluster,

comparing a top-ranked requirement with remaining of at least two of the plurality of requirements; and

identifying one or more unique elements from the remaining of the at least two of the plurality of requirements, wherein the one or more unique elements are absent in the top-ranked requirement;

identifying the plurality of requirements from each of the plurality of applications through a code analysis technique.

2. The method of claim 1 , wherein the final similarity index corresponding to the at least two of the plurality of requirements within the at least one cluster is above a predefined threshold.

3. The method of claim 2 , further comprising:

for each of the at least one cluster,

assigning a rank to each of the at least two of the plurality of requirements based on a set of performance parameters; and

selecting the top-ranked requirement from the at least two of the plurality of requirements.

4. The method of claim 3 , further comprising generating a common application using the top-ranked requirement from each of the at least one cluster.

5. The method of claim 4 , further comprising, one of:

for each of the at least one cluster,

creating a new requirement, corresponding to each of the one or more unique elements, in the common application; or

adding the one or more unique elements to the top-ranked requirement in the common application.

6. The method of claim 1 , further comprising transforming elements of each of the at least two of the plurality of requirements into technology agnostic elements prior to determining the similarity index through each of the set of analysis techniques.

7. A system for identifying common requirements from applications, the system comprising a processor; and

a memory communicatively coupled to the processor, wherein the memory stores processor instructions, which when executed by the processor, cause the processor to:

receive a plurality of requirements from a plurality of applications, wherein each of the plurality of requirements corresponds to a functionality in one of the plurality of applications;

for at least two of the plurality of requirements, determine a similarity index through each of a set of analysis techniques,

wherein the set of analysis techniques comprises a process driven analysis technique, a data driven analysis technique, and a consumer driven analysis technique;

calculate a final similarity index based on the similarity index determined through each of a set of analysis techniques, wherein the final similarity index is a weighted average of the similarity index determined through each of a set of analysis techniques;

generate a similarity matrix for the plurality of requirements based on the final similarity index, wherein elements of the similarity matrix are final similarity indices corresponding to the plurality of requirements; and

generate a hierarchical cluster tree for the plurality of requirements based on the final similarity index corresponding to each of the plurality of requirements; and

identify at least one cluster of requirements from the plurality of requirements through the hierarchical cluster tree, wherein the at least one cluster of requirements comprises each of the at least two of the plurality of requirements, wherein for each of the at least one cluster, comparing a top-ranked requirement with remaining of at least two of the plurality of requirements; and identifying one or more unique elements from the remaining of the at least two of the plurality of requirements, wherein the one or more unique elements are absent in the top-ranked requirement;

wherein the processor instructions, on execution, further cause the processor to identify the plurality of requirements from each of the plurality of applications through a code analysis technique.

8. The system of claim 7 , wherein the final similarity index corresponding to the at least two of the plurality of requirements within the at least one cluster is above a predefined threshold.

9. The system of claim 8 , wherein the processor instructions, on execution, further cause the processor to:

for each of the at least one cluster,

assign a rank to each of the at least two of the plurality of requirements based on a set of performance parameters; and

select the top-ranked requirement from the at least two of the plurality of requirements.

10. The system of claim 9 , wherein the processor instructions, on execution, further cause the processor to generate a common application using the top-ranked requirement from each of the at least one cluster.

11. The system of claim 10 , wherein the processor instructions, on execution, further cause the processor to, one of:

for each of the at least one cluster,

create a new requirement, corresponding to each of the one or more unique elements, in the common application; or

add the one or more unique elements to the top-ranked requirement in the common application.

12. The system of claim 7 , wherein the processor instructions, on execution, further cause the processor to transform elements of each of the at least two of the plurality of requirements into technology agnostic elements prior to determining the similarity index through each of the set of analysis techniques.

13. A non-transitory computer-readable medium storing computer-executable instructions for identifying common requirements from applications, the computer-executable instructions configured for:

receiving a plurality of requirements from a plurality of applications, wherein each of the plurality of requirements corresponds to a functionality in one of the plurality of applications;

for at least two of the plurality of requirements, determining a similarity index through each of a set of analysis techniques,

wherein the set of analysis techniques comprises a process driven analysis technique, a data driven analysis technique, and a consumer driven analysis technique;

calculating a final similarity index based on the similarity index determined through each of a set of analysis techniques, wherein the final similarity index is a weighted average of the similarity index determined through each of a set of analysis techniques;

generating a similarity matrix for the plurality of requirements based on the final similarity index,

wherein elements of the similarity matrix are final similarity indices corresponding to the plurality of requirements; and generating a hierarchical cluster tree for the plurality of requirements based on the final similarity index corresponding to each of the plurality of requirements; and

identifying at least one cluster of requirements from the plurality of requirements through the hierarchical cluster tree,

wherein the at least one cluster of requirements comprises each of the at least two of the plurality of requirements, wherein for each of the at least one cluster,

comparing a top-ranked requirement with remaining of at least two of the plurality of requirements; and

identifying one or more unique elements from the remaining of the at least two of the plurality of requirements, wherein the one or more unique elements are absent in the top-ranked requirement;

identifying the plurality of requirements from each of the plurality of applications through a code analysis technique.

14. The non-transitory computer-readable medium of claim 13 , wherein the final similarity index corresponding to the at least two of the plurality of requirements within the at least one cluster is above a predefined threshold.

15. The non-transitory computer-readable medium of claim 14 , wherein the computer-executable instructions are further configured for:

for each of the at least one cluster,

assigning a rank to each of the at least two of the plurality of requirements based on a set of performance parameters; and

selecting the top-ranked requirement from the at least two of the plurality of requirements.

16. The non-transitory computer-readable medium of claim 15 , wherein the computer-executable instructions are further configured for generating a common application using the top-ranked requirement from each of the at least one cluster.