Claims:1. A system for facilitating analysis of requirement document, said system comprising of:
a processor operatively coupled with a memory, the memory storing instructions executable by the processor to:
receive a first set of data packets from an input device, said first set of data packets corresponding to a first set of inputs pertaining to a format of a document;
generate from the received set of inputs, a first document with a format corresponding to a predetermined format;
receive a second set of inputs corresponding to a first set of attributes defined by a user, said first set of attributes indicative of metadata to be searched;
analyse the generated first document by mapping with the received second set of inputs and a predefined set of attributes;
identify a second set of attributes based on the mapping of the first document with the received second set of inputs and the predefined set of attributes,
wherein the second set of attributes are indicative of any inaccuracy present in the first document;
generate a second document based on rectification of the first document corresponding to the second set of attributes, wherein said second document comprises of a set of output attributes, said set of output attributes indicative of an analysis report; and,
determine a score based on the mapping of the second set of attributes and the first set of attributes,
wherein the score is indicative of strength of the second document,
wherein the strength of the document is based on response to the first set of attributes provided by the user and the predefined set of attributes to facilitate analysis of the requirement document.
2. The system as claimed in claim 1, wherein the set of inputs pertains to any or a combination of pdf, browser, text file, excel sheet, and xml file format.
3. The system as claimed in claim 1, wherein the input device is be any or a combination of a scanner, a laptop, a personal computer and any mobile computing device.
4. The system as claimed in claim 1, wherein the second document having the analysis report is displayed on a display device, said display device is any or a combination of a printer, laptop, personal computer and any mobile computing device.
5. The system as claimed in claim 1, wherein the set of output attributes of the second document comprises of any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables, number of images, pie diagram highlighting strength and score of the second document.
6. A method for facilitating analysis of requirement document, said method comprising the steps of :
receiving, at a processor, a first set of data packets from an input device, said first set of data packets corresponding to a set of inputs pertaining to a format of a document;
generating, at the processor, from the received set of inputs, a first document with a format corresponding to a predetermined format;
receiving, at the processor, a second set of inputs corresponding to a first set of attributes defined by a user, said first set of attributes indicative of metadata to be searched;
analysing, at the processor, the generated first document by mapping with the received second set of inputs and a predefined set of attributes;
identifying, at the processor, a second set of attributes based on the mapping of the first document with the received second set of inputs,
wherein the second set of attributes are indicative of inaccuracy present in the first document;
generating, at the processor, a second document based on rectification of the first document corresponding to the second set of attributes, wherein said second document comprises of a set of output attributes, said set of output attributes indicative of an analysis report; and,
determining, at the processor, a score based on the mapping of the second set of attributes and the first set of attributes,
wherein the score is indicative of strength of the second document,
wherein the strength of the document is based on the response to the first set of attributes provided by the user and the predefined set of attributes to facilitate analysis of the requirement document.
7. The method as claimed in claim 6, wherein the set of inputs pertains to any pdf, browser, text file, excel sheet and xml format.
8. The method as claimed in claim 6, wherein the predefined set of attributes comprises any or a combination of a first list of first set of parameters, a second list of second set of parameters, a third list of third set of parameters and a set of computing parameters facilitating determination of the score and strength of the second document.
9. The method as claimed in claim 6, wherein the second set of attributes are identified based on a dataset comprising of any or a combination of a dictionary, linguistic, engineering, tools related definitions having more than one interpretation.
10. The method as claimed in claim 6, wherein the set of output attributes of the second document comprises of any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables, number of images, pie diagram highlighting strength and score of the second document.

, Description:TECHNICAL FIELD
[0001] The present disclosure relates to a system and a method for facilitating analysis of requirement document and in particular, generating a refined detailed requirement analysis report.

BACKGROUND
[0002] The advanced systems of contemporary times demand that system requirements be measurable, testable, and traceable and defined to a level of detail sufficient for the system development. A system requirement is a capability needed by the user to solve a problem or to achieve an objective. In other words, requirement is a system capability that must be met or possessed by a system or system component to satisfy a contract, standard, specification, or other formally imposed documentation. Perhaps the greatest challenge being faced by system developers is to share the vision of the final product with the customer.
[0003] In the context of analysis of a certain document, there are certain systems that provide for a collective search of certain parameters in a document. For example, a collection search system is responsive to a user query against a collection of documents to provide a search report. Then, there is the system for document analysis, commenting, and reporting with state machines tailored to specific document types. As one example, the system may implement state machines that evaluate document structure instances to determine whether the document structure instances conform to pre-defined syntaxes. The state machines may include error states and final states, and messages may be associated with the error states for display when a state machine reaches the error state. Also, Word provides a tool that can be used to return simple statistics about the document. One of the statistics can be the number of lines in the document. However, these methods are not inclined to describe a system requirement in detail. These methods will not be able to search, map or document the many aspects inherent in a requirement document of a system. All stakeholders in a project such as developers, end users, system managers, and customer managers must achieve a common understanding of what the product will be and what the product will do, or someone will be surprised when it is delivered. Surprises in system are always unwanted. The requirement document analysis can be a long and repetitive process during which many delicate psychological skills are involved.
[0004] Hence, there is a requirement in the art to devise a system and a method to identify the uncertainty, accurately capture, interpret, and represent the voice of customers when specifying the requirements for a system and provide for a proper analysis report of the requirement document.

OBJECTS OF THE PRESENT DISCLOSURE
[0005] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0006] An object of the present disclosure is to provide a method and system for identifying texts in a document which are ambiguous.
[0007] An object of the present disclosure is to provide a method and system for generating a score for providing qualitative measure of the document under review.
[0008] An object of the present disclosure is to provide an approach to help reduce review efforts by an expert team.
[0009] An object of the present disclosure is to provide a solution for clarifying requirements at initial stage, so that efforts in later stages such as design, implementation, testing, integration, FAT, SAT, maintenance get reduced.
[0010] An object of the present disclosure is to reduce the time for review of a requirement document and serve as entry criteria for any technical requirements documents for expert review.

SUMMARY
[0011] The present disclosure relates to a system and method for facilitating analysis of requirement documents.
[0012] According to an embodiment, the present disclosure relates to a system facilitating analysis of requirement document, the system may include : a processor operatively coupled with a memory, the memory storing instructions executable by the processor to: receive a first set of data packets from an input device, said first set of data packets corresponding to a set of inputs pertaining to a format of a document; generate from the received set of inputs, a first document with a format corresponding to a predetermined format; receive a second set of inputs corresponding to a first set of attributes defined by a user, the first set of attributes may be indicative of metadata to be searched; analyse the generated first document by mapping with the received second set of inputs; identify a second set of attributes from the mapping of the first document and the received second set of inputs, wherein the second set of attributes are indicative of any inaccuracy present in the first document; generate a second document based on rectification of the first document corresponding to the second set of attributes, wherein the second document may include a set of output attributes, the set of output attributes indicative of an analysis report; and, determine, a score based on the mapping of the second set of attributes and the first set of attributes, wherein the score may be indicative of strength of the second document, wherein the strength of the document may be based on the response to the first attributes provided by the user and the predefined set of attributes to facilitate analysis of the requirement document.
[0013] According to an embodiment, the present disclosure provides for the system wherein the set of inputs may pertain to any file format such as pdf, browser, text file, excel sheet, xml format and the like.
[0014] According to an embodiment, the present disclosure provides for the system, wherein the input device may be any or a combination of a scanner, a laptop, a personal computer and any mobile computing device.
[0015] According to an embodiment, the present disclosure provides for the system, wherein the second document having the analysis report may be displayed on a display device, said display device may be any or a combination of a printer, laptop, personal computer and any mobile computing device.
[0016] According to an embodiment, the present disclosure provides for the system, wherein the set of output attributes of the second document can include any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables, number of images, pie diagram highlighting strength and score of the second document.
[0017] According to an embodiment, the present disclosure provides for a method for facilitating analysis of requirement document, the method may include the steps of : receiving, at a processor, a first set of data packets from an input device, the first set of data packets corresponding to a set of inputs pertaining to a format of a document; generating, at the processor, from the received set of inputs, a first document with a format corresponding to a predetermined format; receiving, at the processor, a second set of inputs corresponding to a first set of attributes defined by a user, the first set of attributes maybe indicative of metadata to be searched; analysing, at the processor, the generated first document by mapping with the received first set of attributes a predefined set of attributes; identifying, at the processor, a second set of attributes based on the mapping of the first document with the received second set of inputs, wherein the second set of attributes are indicative of inaccuracy present in the first document; generating, at the processor, a second document based on rectification of the first document corresponding to the second set of attributes, wherein the second document may include a set of output attributes, the set of output attributes indicative of an analysis report; and, determining, at the processor, a score based on the mapping of the second set of attributes and the first set of attributes, wherein the score maybe indicative of strength of the second document, wherein the strength of the document may be based on the response to the first attributes provided by the user and the predefined set of attributes to facilitate analysis of the requirement document.
[0018] According to an embodiment, the present disclosure provides for the method wherein the set of inputs may pertain to any file format such as pdf, browser, text file, excel sheet and xml format.
[0019] According to an embodiment, the present disclosure provides for the method, wherein the predefined set of attributes may include any or a combination of a first list of first set of parameters, a second list of second set of parameters, a third list of third set of parameters and a set of computing parameters facilitating determination of the score and strength of the second document.
[0020] According to an embodiment, the present disclosure may provide for the method, wherein the second set of attributes may be identified based on a dataset that may include any or a combination of a dictionary, linguistic, engineering, tools related definitions having more than one interpretation.
[0021] According to an embodiment, the present disclosure may provide for the method, wherein the output attributes of the second document may include any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables, number of images and pie diagram highlighting strength and score of the second document.

BRIEF DESCRIPTION OF THE DRAWINGS
[0022] In the figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[0023] The diagrams are for illustration only, which thus is not a limitation of the present disclosure, and wherein:
[0024] FIG. 1 illustrates an exemplary system architecture, in accordance with an embodiment of the present disclosure.
[0025] FIG. 2 illustrates an exemplary representation of a flow diagram associated with the method for facilitating analysis of requirement document in accordance with an embodiment of the present disclosure.
[0026] FIGs. 3A-3D illustrate exemplary flow diagrams of the working of the method in a stepwise manner, in accordance with an embodiment of the present disclosure.
[0027] FIGs. 4A-4E illustrate exemplary representations of the working of the proposed method in a stepwise manner, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION
[0028] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0029] The term “metadata” as is used herein, generally refers to a technical term used for data that provides information about other data. In most information technology, metadata is an underlying definition or description. Metadata summarizes basic information about data, which can make finding and working with particular instances of data easier. For example, metadata can be treated as references to data that needs to be searched.
[0030] The term “requirement document” used herein refers to a document containing all the requirements of a certain product. It is written to allow people to understand what a product should do. Requirement documents are most frequently written for software products, but can be used for any type of product and for services as well. The requirements need to be measurable, testable and traceable and defined to a level of detail sufficient for the system.
[0031] The present disclosure relates to a system and method for facilitating analysis of requirement documents.
[0032] In an embodiment, the present disclosure relates to a system facilitating analysis of requirement document, the system can include : a processor operatively coupled with a memory, the memory storing instructions executable by the processor to: receive a first set of data packets from an input device, said first set of data packets corresponding to a set of inputs pertaining to a format of a document; generate from the received set of inputs, a first document with a format corresponding to a predetermined format; receive a second set of inputs corresponding to a first set of attributes defined by a user, the first set of attributes can be indicative of metadata to be searched; analyse the generated first document by mapping with the received second set of inputs and a predefined set of attributes; identify a second set of attributes from the mapping of the first document and the received second set of inputs, wherein the second set of attributes are indicative of any inaccuracy present in the first document; generate, a second document based on rectification of the first document corresponding to the second set of attributes, wherein the second document can include a set of output attributes, the set of output attributes indicative of an analysis report; and, determine a score based on the mapping of the second set of attributes and the first set of attributes, wherein the score can be indicative of strength of the second document, wherein the strength of the document can be based on the response to the first attributes provided by the user and the predefined set of attributes to facilitate analysis of the requirement document.
[0033] In an embodiment, the present disclosure provides for the system wherein the set of inputs can pertain to any file format such as pdf, browser, text file, excel sheet, xml format and the like.
[0034] In an embodiment, the present disclosure provides for the system, wherein the input device can be any or a combination of a scanner, a laptop, a personal computer and any mobile computing device.
[0035] In an embodiment, the present disclosure provides for the system, wherein the second document having the analysis report can be displayed on a display device, the display device can be any or a combination of a printer, laptop, personal computer and any mobile computing device.
[0036] In an embodiment, the present disclosure provides for the system, wherein the set of output attributes of the second document may include any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables, number of images and pie diagram highlighting strength and score of the second document.
[0037] In an embodiment, the present disclosure provides for a method for facilitating analysis of requirement document, the method can include the steps of : receiving, at a processor, a first set of data packets from an input device, the first set of data packets corresponding to a set of inputs pertaining to a format of a document; generating, at the processor, from the received set of inputs, a first document with a format corresponding to a predetermined format; receiving, at the processor, a second set of inputs corresponding to a first set of attributes defined by a user, the first set of attributes can be indicative of metadata to be searched; analysing, at the processor, the generated first document by mapping with the received second set of inputs and a predefined set of attributes; identifying, at the processor, a second set of attributes based on the mapping of the first document with the received second set of inputs, wherein the second set of attributes can be indicative of inaccuracy present in the first document; generating, at the processor, a second document based on rectification of the first document corresponding to the second set of attributes, wherein the second document can include a set of output attributes, the set of output attributes indicative of an analysis report; and, determining, at the processor, a score based on the mapping of the second set of attributes and the first set of attributes, wherein the score can be indicative of strength of the second document, wherein the strength of the document can be based on the response to the first attributes provided by the user and the predefined set of attributes to facilitate analysis of the requirement document.
[0038] In an embodiment, the present disclosure provides for the method wherein the set of inputs can pertain to any file format such as pdf, browser, text file, excel sheet and xml format.
[0039] In an embodiment, the present disclosure provides for the method, wherein the predefined set of attributes may include any or a combination of a first list of first set of parameters, a second list of second set of parameters, a third list of third set of parameters and a set of computing parameters facilitating determination of the score and strength of the second document.
[0040] In an embodiment, the present disclosure may provide for the method, wherein the second set of attributes can be identified based on a dataset that can include any or a combination of a dictionary, linguistic, engineering, tools related definitions having more than one interpretation.
[0041] In an embodiment, the present disclosure may provide for the method, wherein the output attributes of the second document can include any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables , number of images and pie diagram highlighting strength and score of the second document.
[0042] FIG. 1 illustrates an exemplary system architecture, in accordance with an embodiment of the present disclosure.
[0043] As illustrated, the computing unit 102 can include at least one processor 104. The processor 104 can be implemented as microprocessors, microcomputers, digital signal processors and central processing units. Among other capabilities, the processor 104 are configured to fetch and execute computer-readable instructions stored in a memory 106 of the computing unit 102. The memory 106 can store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 106 can include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
[0044] The computing unit 102 can also include an interface(s) 108. The interface(s) 108 may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 108 may facilitate communication of the computing unit 102 with various devices coupled to the computing unit 102. The interface(s) 108 may also provide a communication pathway for one or more components of the computing unit 102. Examples of such components include, but are not limited to, processing unit(s) 110 and database118.
[0045] The processing unit(s) 110 can be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing unit(s) 110. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing unit(s) 110 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing unit(s) 110 may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing unit(s) 110. In such examples, the computing unit 102 can include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to computing unit 102 and the processing resource. The database118 can include data that can be either stored or generated as a result of functionalities implemented by any of the components of the processing unit(s) 110.
[0046] In an example, the processing unit(s) 110 can include a file formatting unit 112, an analysing unit 114, and other unit(s) 116. The other units(s) 116 can implement functionalities that supplement applications or functions performed by the computing unit 102 or the processing unit(s) 110.
[0047] In an embodiment, the computing unit 102 can be coupled to an input device, the input device can be configured to receive a first set of data packets, the first set of data packets can correspond to a set of inputs pertaining to a requirement document of any file format. In an exemplary embodiment, the input device can be any device coupled to any or a combination of wired, wireless and cloud based network.
[0048] In yet another embodiment, the input device can be any scanner that can scan the document and provide scanned document to the computing unit 102.
[0049] In yet another embodiment, the input device can be any device having communication ports for receiving any or a combination of pen drives, CDs, floppy disk and the like.
[0050] In an embodiment, the file formatting unit 112 of the computing unit 102 can receive a first set of data packets from the input device, the first set of data packets can correspond to a set of inputs (interchangeably referred to as input file) pertaining to a format of a document. For example, the document can be uploaded in raw format which cannot be fed to the system. The input file format can include any pdf, browser, text file, excel sheet, xml, and the like. The analysis of the document can be performed only with a predetermined file format. Thus, the file formatting unit 112 can compare the input file format with the predetermined format. If the file formatting unit 112 finds the input file with a different format, the file formatting unit 112, can convert the input file to the pre-determined file format generating the first document with the predetermined file format. The conversion to pre-determined format can also be done manually by copying contents from the input file format to the pre-determined format. For example, the set of inputs with a file format of pdf can be converted to any txt and doc file format by the file formatting unit 112.
[0051] In an embodiment, the analysing unit 114 of the computing unit 102 can receive the first document with the pre-determined format from the file formatting unit 112 on the receipt of acknowledgement from the processor 104. For example, the analysing unit 114 can start analysing the first document only after receiving Start Review acknowledgement.
[0052] In another embodiment, the analysing unit 114 can perform a set of routines to determine the inherent problems such as typos, grammar mistakes, phrase mismatch, sentence errors and the like in the first document and can provide measures to correct those. For example, the set of routines performed by the analysing unit 114 can be routines to calculate and display metadata related information.
[0053] In yet another embodiment, the analysing unit 114 can receive second set of inputs corresponding to a first set of attributes defined by a user, the first set of attributes can be indicative of metadata to be searched, wherein the metadata can be responsive to a dataset comprising of any or a combination of functional requirements, non-functional requirements and design objectives.
[0054] In an exemplary implementation, functional requirements can pertain to what a system can do. Non-functional requirements can be restrictions on the types of solutions that will meet the functional requirements while design objectives can be guides to use in selecting a solution.
[0055] In an embodiment, upon receipt of the second set of inputs, the analysing unit 114 can analyse and determine a set of second attributes corresponding to any or a combination of metadata, a set of metadata corresponding to inaccuracies present in the first document and a predefined set of attributes. The second set of attributes can be identified based on a dataset comprising of any or a combination of a dictionary, linguistic, engineering, tools related definitions having more than one interpretation while the predefined set of attributes can include a first list (interchangeably referred to as red list) a second list (interchangeably refer, a third list and a set of computing parameters to determine the score and strength of the second document. The red list may include parameters with worst impact quality. For example, words such as like, some, almost, possible, roughly and the like. The yellow list may include parameters having mild impact on quality. For example, words such as could, should, likely, might, may and the like. The green list may include parameters having good impact on quality. For example, parameters such as within range -, equal to, all the listed at , included, shall, all, except, and the like. The computational parameters corresponding to the predefined set of attributes can be then mapped with the first, second and third list to determine the second set of attributes.
[0056] The analysing unit 114 can then map the second set of attributes in the database 118 or can display in a display device coupled to the computing unit 102.
[0057] In an embodiment, the display device can be any or a combination of a printer, personal computer, a laptop, a tablet, a smart phone and a mobile computing device.
[0058] In another embodiment, the analysing unit 114 can process the second set of attributes and can provide measures for rectifying them. In an exemplary embodiment, the second document can include any or a combination of number of vacant paragraphs, number of paragraphs having contents, number of sentences, number of words, number of tables and number of images and display the analysis report on the display device. In yet another exemplary embodiment, the second document can generate an analysis report, wherein the analysis report may include a statistical diagram highlighting any or a combination of usable output attributes, inaccurate output attributes and unacceptable output attributes. In an example, an input document having 11000 words and 250 pages, wherein each page having 400 words, the generation of analysis report may take 44 seconds as displayed on the display device.
[0059] In yet another embodiment, the analysing unit 114 can, determine a score based on the mapping of the second set of attributes and the first set of attributes, wherein the score can be indicative of strength of the second document. The strength of the document can be based on a response to the first attributes provided by the user and the predefined attributes to facilitate analysis of the requirement document. For example, if only 20% of inaccuracies and 10% is unusable output attributes, then the score of the document can be 70% which is then highlighted in the analysis report.
[0060] In an exemplary embodiment, the score generated by the analysing unit 114 can also be displayed in the display device.
[0061] In yet another embodiment, the analysis report and the score generated by the analysing unit 114 can be stored in the memory 106 for future reference. In an exemplary embodiment, the second set of inputs received from the user by the analysing unit 114 can be user dependent and can be customizable.
[0062] FIG. 2 illustrates an exemplary representation of a flow diagram associated with the method 200 for facilitating analysis of requirement document in accordance with an embodiment of the present disclosure.
[0063] The order in which the method as described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method or alternate methods. Additionally, individual blocks may be deleted from the method without departing from the spirit and scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof. However, for ease of explanation, in the embodiments described below, the method may be considered to be implemented in the above described system.
[0064] In an embodiment, a method for facilitating analysis of a requirement document, the method 200 may include at block 202, a step of receiving at a processor 104, a first set of data packets, the first set of data packet corresponding to a set of inputs pertaining to a format of a document; and at block 204, a step for generating at the processor, from the received se of inputs, a first format of the document corresponding to a predetermined format.
[0065] Further, the method may include at block 206, a step for receiving at the processor, a second set of inputs corresponding to a first set of attributes defined by a user, the first set of attributes can be indicative of metadata to be searched; and at block 208, a step for analysing at the processor, by mapping the first document with the second set of inputs received and a predefined set of attributes.
[0066] Furthermore, the method may include, at block 210, a step for identifying, at the processor, a second set of attributes based on the mapping of the first document with the second set of inputs received, wherein the second set of attributes may be indicative of inaccuracy present in the first document; and at block 212, a step for generating, a second document based on rectification of the first document corresponding to the second set of attributes, wherein the second document can include a set of output attributes, the set of output attributes indicative of an analysis report; and at block 214, a step for determining, at the processor, a score based on the mapping of the second set of attributes and the first set of attributes, wherein the score may be indicative of strength of the second document, wherein the strength of the document can be based on the response to the first attributes provided by the user to facilitate analysis of the requirement document.
[0067] FIGs. 3A-3D illustrate exemplary flow diagrams of the working of the method in a stepwise manner, in accordance with an embodiment of the present disclosure.
[0068] In an exemplary embodiment, the predefined set of attributes can include a red list, a green list, a yellow list and a set of computing parameters to determine the score and strength of the second document. The red list may include parameters with worst impact quality. For example, words such as like, some, almost, possible, roughly and the like. The yellow list may include parameters having mild impact on quality. For example, words such as could, should, likely, might, may and the like. The green list may include parameters having good impact on quality. For example, parameters such as within range -, equal to, all the listed at , included, shall, all, except, and the like. As illustrated in FIG. 3A, at block 302, Get the text. Then at block 304, Count No of words in text which are from Green, Yellow and Red. At block 306, Calculate strengths of document based on calculating Strength of words and Strength of requirement and finally at block 308, Calculate overall strength of document.
[0069] For example, as illustrated in FIG. 3B, at block 310, if there are 2 red, 1 green, 1 yellow words from the red, green and yellow lists respectively, then at block 312, average strength of the words can be determined using : Word Strength =[(No of words from Red List)*weightage of red word + (No of words from Yellow List)*weightage of yellow word +(No of words from Green List)*weightage of Green word) ] /[Total no of words from Red, Yellow and Green Lists *weightage of green words].
[0070] In another example, as illustrated in FIG. 3C, the determination of strength of requirement at block 306 is illustrated from strength of words received. At block 314, if word strength > 0.66, then at block 316 Strength category of Requirement is green, Else, at block 318, if word strength > 0.33, then at block 320, Strength category of Requirement is Yellow, Else, at block 322, Strength category of Requirement is Red.
[0071] In yet another example, as illustrated from FIG. 3D from the strength of requirements at block 306, strength of document at block 308 can be determined. Hence, at block 324 Document Strength = [(No of Red requirements)*weightage of red requirement +(No of Yellow requirements)*weightage of yellow requirement + (No of Green requirements)*weightage of Green requirement ] /[Total no of requirements *weightage of green requirements].
[0072] FIGs. 4A-4E illustrate exemplary representations of the working of the proposed method in a stepwise manner, in accordance with an embodiment of the present disclosure.
[0073] As illustrated in FIG.4A, a representation of a display unit may be depicted wherein uploading a first document pertaining to a pre-determined format can take place. Once the document has been uploaded, the metadata related information can be calculated and displayed.
[0074] As illustrated in FIG.4B, representation of the user display unit may be depicted wherein once Start Review acknowledgement is received, then all the phrases corresponding to inaccuracies can be analysed and an analysis report may be displayed. As illustrated in FIG. 3B, a score, indicating strength of the document may also be displayed.
[0075] As illustrated in FIG. 4C, the representation of the display unit can depict that analysed document can be saved for future use and the saved document can have the concerned data highlighted.
[0076] Further, as illustrated in FIG. 4D, the representation of the display unit can depict that option can also be provided to user to customize phrase as per the user’s expectations. FIG. 4E illustrates the result of the analysis when customization is done.
[0077] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0078] Some of the advantages of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0079] The present disclosure provides for a method and system for identifying texts in a document which are ambiguous.
[0080] The present disclosure provides for a method and system for generating a score for providing qualitative measure of the document under review.
[0081] The present disclosure provides for an approach to help reduce review efforts by an expert team.
[0082] The present disclosure provides for a solution for clarifying requirements at initial stage, so that efforts in later stages such as design, implementation, testing, integration, FAT, SAT, maintenance get reduced.
[0083] The present disclosure provides for an approach to reduce the time for review needed for a requirement document and serve as entry criteria for any technical requirements documents for expert review.