FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION (See section 10, rule 13)
1. Title of the Invention:
“A SYSTEM AND A METHOD FOR GENERATING BUSINESS
REQUIREMENT DOCUMENT”
2. APPLICANT (S) -
(a) Name : Zensar Technologies Limited
(b) Nationality : Indian
(c) Address : Plot #4, Zensar Knowledge Park, MIDC, Kharadi,
Off Nagar Road, Pune, Maharashtra - 411014, India
The following specification particularly describes the invention and the manner in which it is to be performed.

TECHNICAL FIELD
The present disclosure relates in general to generation of Business Requirement Document (BRD) from an existing information technology (IT) enabled system.
BACKGROUND
Various technologies for transforming a particular technology-based code (like COBOL, JOVIAL, FORTRAN, PERL and other related Programming Languages) to any other technology-based code are present. However, such kind of code conversion requires a person who has deep knowledge about both the programming languages. As there are numerous existing software languages, it becomes a tedious task to find a person who is skillful in existing software language as well as in latest programming language.
This issue becomes more severe when one has to generate Business Requirement Document (BRD) from an existing system or a legacy system which are running on some older technology. For generating the BRD, it is required to understand existing or legacy software code running on the existing/legacy system to figure out the functionality implemented by the existing/legacy system. Hence, there is a long-felt need of a system and a method to generate the BRD from the existing/legacy system.
SUMMARY
In one non-limiting embodiment of the present disclosure, a method of generating Business Requirement Document (BRD) from an existing IT enabled system is disclosed. The method comprises fetching, after establishing a connection with the existing IT enabled system, a software code pertaining to the existing IT enabled system from its memory. The method further comprises generating pre-BRD data by using a Natural Language Processing (NLP) technique. The pre-BRD data is generated by analyzing a plurality of syntax present in the software code. Further, the pre-BRD data comprises a plurality of operational steps, indicating step by step operation of the existing IT enabled system, corresponding to the plurality of syntax being analyzed. The method further comprises analyzing the pre-BRD data in relative to a plurality of rules in order to determine functional flow of the pre-BRD data. The method further comprises converting the pre-

BRD data into the BRD representing the functional flow determined for the pre-BRD data in form of one or more natural language sentences by using the NLP technique.
In another embodiment of the present disclosure a BRD generating system for generating Business Requirement Document (BRD) from an existing IT enabled system is disclosed. The system comprises a memory for storing a set of instructions and a processor coupled with the memory. The processor upon executing the set of instructions, stored in the memory, is configured to fetch, after establishing a connection with the existing IT enabled system, a software code pertaining to the existing IT enabled system from its memory. The processor is further configured to generate pre-BRD data by using a Natural Language Processing (NLP) technique. The pre-BRD data is generated by analyzing a plurality of syntax present in the software code. Further, the pre-BRD data comprises a plurality of operational steps, indicating step by step operation of the existing IT enabled system, corresponding to the plurality of syntax being analyzed. The processor is further configured to analyze the pre-BRD data in relative to a plurality of rules in order to determine functional flow of the pre-BRD data. Further, the processor converts the pre-BRD data into the BRD representing the functional flow determined for the pre-BRD data in form of one or more natural language sentences by using the NLP technique.
The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:

FIG. 1 shows an exemplary environment 100 illustrating system for generating a Business Requirement Document (BRD), in accordance with some embodiments of the present disclosure;
FIG. 2 shows a detailed block diagram 200 illustrating the BRD generating system, in accordance with some embodiments of the present disclosure;
FIG. 3 show a flowchart 300 illustrating a method of generating Business Requirement Document (BRD), in accordance with some embodiments of the present disclosure; and
FIG. 4 illustrates a block diagram of an exemplary computer system 400 for implementing embodiments consistent with the present disclosure.
It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, and the like represent various processes which may be substantially represented in computer readable medium and executed by a computer or processor, whether or not such computer or processor is explicitly shown.
DETAILED DESCRIPTION
In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternative falling within the spirit and the scope of the disclosure.
The terms “comprises”, “comprising”, “includes”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, device, apparatus, system or method that comprises a list of components or steps does not include only those components or steps but

may include other components or steps not expressly listed or inherent to such setup or device or apparatus or system or method. In other words, one or more elements in a system or apparatus or device proceeded by “comprises… a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or method.
The present disclosure relates to a method and a Business Requirement Document (BRD) generating system for generating the BRD from an existing IT enabled system. According to embodiments of present disclosure, the BRD generating system fetches a software code from a memory of the existing IT enabled system for analyzing. It may be understood to a skilled person that the existing IT enabled system may be a legacy system or any existing system on which the software code is running. According to the embodiments of the present disclosure, the software code running on the existing IT enabled system may be in different technologies/languages like COBOL, JOVIAL, FORTRAN, PERL, JAVA, C, C++ and the like.
For generating the BRD, the software code running on the existing IT enabled system need to be analyzed. During the analysis, a plurality of syntax is identified from the software code. The identified plurality of syntax is further analyzed with pre-stored syntax meanings present in a form of natural language sentence stored in a pre-stored reference table. The pre-stored reference table provides a mapping between pre-stored syntaxes and corresponding syntax meanings in the form of natural language sentences. Based on the analysis, pre-BRD data is generated which comprises operational steps, indicating step by step operation of the existing IT enabled system, corresponding to the plurality of syntax being analyzed.
The pre-BRD data generated is further analyzed in relative to a plurality of rules to determine functional flow of the pre-BRD data. While performing the analysis with the rules, the BRD generating system also learns about one or more rules, amongst the plurality of rules, which are essential for executing a task and generating the BRD. The learning is further implemented while generating BRD of another existing IT enabled system in future.
When the pre-BRD data is generated, the BRD generating system understands about the functional flow of the system. However, the functional flow is to be documented in a form of sentences. For this, the BRD generating system converts the generated pre-BRD data into the BRD

representing the functional flow of the pre-BRD data in form of one or more natural language sentences by using the NLP technique.
In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings that form a part hereof, and in which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
FIG. 1 shows an exemplary environment 100 illustrating system for generating a Business Requirement Document (BRD), in accordance with some embodiments of the present disclosure.
The environment 100 includes a BRD generating system 102 which is implemented to analyse software code running on existing IT enabled system 104 to generate BRD 108. The existing IT enabled system 104 may include any existing or legacy system having the software code in existing/legacy programming languages such as COBOL, JOVIAL, FORTRAN, PERL, JAVA, C, C++ and the like. According to an embodiment of present disclosure, the BRD generating system 102 fetches the software code from the memory of the existing IT enabled system 104. The software code fetched by the BRD generating system 102 may comprise plurality of syntax for performing a task. An example of the software code is shown in block 112. It can be observed that, the software code comprises an IP address of a server and a “for loop” syntax for order processing i.e., task associated with the software code.
Now, the BRD generating system 102 analyses the fetched software code line by line to generate pre-BRD data 106 with the help of Natural Language Processing (NLP) technique. An example of the pre-BRD data 106 is shown in block 114. It can be observed from blocks 112 and 114 that, the block 114 is showing the operational flow of the software code of block 112, corresponding to the existing IT enabled system 104, in form of natural language sentence.

Further, the pre-BRD data 106 generated is analysed in relative to a plurality of rules in order to determine functional flow of the pre-BRD data 106. While analyzing the pre-BRD data 106 with the plurality of rules, the BRD generating system 102 also learns about which rules are essential for executing the task. Considering the task of “order processing”, the BRD generating system 102 learns that some set of rules are to be followed for performing the task, while some rules indicates the additional steps for performing the same task. The advantage of such learning is that, the BRD generating system 102 may implement the learning while generating BRD of another existing IT enabled system. Further, the BRD generating system 102 converts the pre-BRD data 106 into the BRD 108 representing the functional flow determined for the pre-BRD data 106 in form of one or more natural language sentences by using the NLP technique. An example of the BRD is shown in block 116.
Now figure 1 is explained in conjunction with figure 2 to describe how the BRD generating system 102 is implemented for generating the BRD 108. According to an embodiment of present disclosure, the BRD generating system 102 may comprise input/output interface 202, a processor 204, a memory 206, and units 210. The I/O interface 202 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, input device, output device and the like. The I/O interface 202 may allow the BRD generating system 102 to interact with the user directly or through other devices. The memory 206 is communicatively coupled to the processor 204. Further, the memory 206 stores data 208 which comprises software code 212 which is fetched from the existing IT enabled system 104, pre-stored reference table 214, rules 110, and NLP dictionary. Further, the units 210 comprises a fetching unit 218, a generating unit 220, an analysing unit 222 and a converting unit 224.
Suppose a user wants to generate BRD of an existing IT enabled system 104 or a legacy system, in which, the software code is running, it becomes a challenge for him/her to understand the functionality being embedded by developers of the existing IT enabled system 104 and accordingly generate the BRD from the understanding. This is because, the existing code may be of older technology from which the generation of the BRD may not be feasible. Without having the BRD, the user may not be able to understand the actual functioning of the software code running on the existing IT enabled system 104.

For this, the fetching unit 218, at first, may fetch the software code 212 from the existing IT enabled system 104 after establishing a connection with the existing IT enabled system 104. However, according to another embodiment, the existing IT enabled system 104 may itself transmits the software code 212, over a communication link, to the BRD generating system 102. The fetched software code 212 is then stored in the memory 206 of the BRD generating system 102 for further processing.
Post fetching the software code 212, the next task is to understand the functioning of the software code 212 for which a line by line analysis needs to be done upon the software code 212. In one embodiment, the line by line analysis may be performed by using an interpreter. For this, a plurality of syntax present in the software code 212 is identified. This way, the software code 212 is broken down into a set of codes which are nothing, but the syntaxes present in the software code 212. Now, the next task is to derive a meaning from the syntaxes which may be understood by the user who may not be able to understand the coding language. For this, each of the identified syntax are correlated with pre-stored syntax meanings present in a form of natural language sentence stored in a pre-stored reference table 214. According to an embodiment, the pre-stored reference table 214 may be pre-learnt table having a mapping between the plurality of pre-stored syntax and corresponding syntax meanings. Hence, referring to the pre-stored reference table 214 helps the generating unit 220 to generate the pre-BRD data 106 by using a Natural Language Processing (NLP) technique. As can be seen from the example block 114, that the pre-BRD data 106 comprises a plurality of operational steps, indicating step by step operation performed by the existing IT enabled system 104, corresponding to the plurality of syntax being analyzed.
For example, the pre-BRD data 106 generated, for the analyzed software code 212, in a form of natural language sentences are (i) the software code is enabling the existing IT enabled system to connect with external server having IP address of 10.55.12.21 and to port 5000, (ii) the “for loop” opened for 10 iterations, (iii) query build to fetch data from order table, and (iv) query execution for data fetch from orders table. From this, it can be observed that how the existing IT enabled system 104 connects with external databases stored in external servers for performing the

order processing task. It may be understood to a person skilled in art that the above given pre-BRD data 106 is just an example, and hence does not limit the scope of the present disclosure.
Now, once the pre-BRD data 106 is generated, the next task is to determine its functional flow. For this, the analyzing unit 222 analyzes the pre-BRD data 106 in relative to a plurality of rules 110 in order to determine functional flow of the pre-BRD data 106. Considering the case of order processing, the rules may be, for example, (i) checking the credit card information availability, (ii) checking whether the credit is validated, (iii) One-time SMS based verification or Each time SMS based verification before processing the order.
From the above analysis, the BRD generating system 102 also learns about which rules are essential and which rules are extra for the order processing. For example, the point number (iii) provides the rule for SMS based verification. However, the “One-time SMS based verification” rule may require lesser steps to be followed compared to “Each time SMS based verification” rule. Thus, the BRD generating system 102 is able to analyze these rules and understand about the functionality of the existing IT enabled system 104, irrespective of the numbers of steps followed in the rule. Further, the BRD generating system 102 may also be able to implement the learning while generating BRD of another existing IT enabled system.
Once the pre-BRD data 106 is analyzed with the rules 110, the next step is to generate the BRD 108. For this, the converting unit 224 may convert the pre-BRD data 106 into the BRD 108 representing the functional flow determined for the pre-BRD data 106 in form of one or more natural language sentences by using the NLP technique. An example of the BRD 108 generated is shown in block 116 of figure 1. On comparing the blocks 112 to 116, it can be observed that how the BRD generating system 102 analyzes the existing IT enabled system 104 and generates pre-BRD data 106, and thereafter the BRD 108.
Further, the BRD generating system 102 also learns about the converting of the pre-BRD data 106 into the BRD 108. The BRD generating system 102 also updates the internal NLP dictionary 216, based on the learning, stored in the memory 208. According to embodiments of present disclosure, the NLP dictionary 216 may be referred for conversions of future pre-BRD data into future BRD data 108.

FIG. 3 show a flowchart 300 illustrating a method of generating Business Requirement Document (BRD), in accordance with some embodiments of the present disclosure.
As illustrated in figure 3, the method 300 includes one or more blocks illustrating a method for generating BRD from the existing IT enabled system. The method 300 may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, and functions, which perform specific functions or implement specific abstract data types.
The order in which the method 300 is 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. Additionally, individual blocks may be deleted from the methods 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.
At block 302, a fetching unit 218 may fetch the software code 212 from the existing IT enabled system 104. The software code 212 is stored in the memory 206 of the existing IT enabled system 104.
At block 304, a generating unit 220 may generate pre-BRD data 106 by using NLP technique. The pre-BRD data is generated by analyzing the plurality of syntax present in the software code 212. The pre-BRD data comprises plurality of operational steps, indicating step by step operation of the existing system, corresponding to the plurality of syntax being analysed.
At block 306, an analysing unit 222 may analyse the pre-BRD data 106 in relative to the plurality of rules 110 in order to determine functional flow of the pre-BRD data 106.
At block 308, a converting unit 224 may convert the pre-BRD data 106 into BRD 108 representing the functional flow determined for the pre-BRD data 214 in the form of one or more natural language sentences by using the NLP technique.
Computer System

Fig.4 illustrates a block diagram of an exemplary computer system 400 for implementing embodiments consistent with the present invention. In an embodiment, the computer system 400 can be a server which can be used for generating the BRD. According to an embodiment, the computer system 400 may fetch the software code 410 from the existing IT enabled system 102. The computer system 400 may comprise a central processing unit (“CPU” or “processor”) 402. The processor 402 may comprise at least one data processor for executing program components for executing user- or system-generated business processes. The processor 402 may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc.
The processor 402 may be disposed in communication with one or more input/output (I/O) devices (411 and 412) via I/O interface 401. The I/O interface 401 may employ communication protocols/methods such as, without limitation, audio, analog, digital, stereo, IEEE-1394, serial bus, Universal Serial Bus (USB), infrared, PS/2, BNC, coaxial, component, composite, Digital Visual Interface (DVI), high-definition multimedia interface (HDMI), Radio Frequency (RF) antennas, S-Video, Video Graphics Array (VGA), IEEE 802.n /b/g/n/x, Bluetooth, cellular (e.g., Code-Division Multiple Access (CDMA), High-Speed Packet Access (HSPA+), Global System For Mobile Communications (GSM), Long-Term Evolution (LTE) or the like), etc.
Using the I/O interface 401, the computer system 400 may communicate with one or more I/O devices (411 and 412).
In some embodiments, the processor 402 may be disposed in communication with a communication network 409 via a network interface 403. The network interface 403 may communicate with the communication network 409. The network interface 403 may employ connection protocols including, without limitation, direct connect, Ethernet (e.g., twisted pair 10/100/1000 Base T), Transmission Control Protocol/Internet Protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc. The communication network 409 can be implemented as one of the different types of networks, such as intranet or Local Area Network (LAN) and such within the organization. The communication network 409 may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further,

the communication network 409 may include a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc.
In some embodiments, the processor 402 may be disposed in communication with a memory 405 (e.g., RAM 413, ROM 414, etc. as shown in FIG. 4) via a storage interface 404. The storage interface 404 may connect to memory 405 including, without limitation, memory drives, removable disc drives, etc., employing connection protocols such as Serial Advanced Technology Attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), fiber channel, Small Computer Systems Interface (SCSI), etc. The memory drives may further include a drum, magnetic disc drive, magneto-optical drive, optical drive, Redundant Array of Independent Discs (RAID), solid-state memory devices, solid-state drives, etc.
The memory 405 may store a collection of program or database components, including, without limitation, user/application data 406, an operating system 407, web browser 408 etc. In some embodiments, the computer system 400 may store user/application data 406, such as the data, variables, records, etc. as described in this invention. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle or Sybase.
The operating system 407 may facilitate resource management and operation of the computer system 400. Examples of operating systems include, without limitation, Apple Macintosh OS X, UNIX, Unix-like system distributions (e.g., Berkeley Software Distribution (BSD), FreeBSD, Net BSD, Open BSD, etc.), Linux distributions (e.g., Red Hat, Ubuntu, K-Ubuntu, etc.), International Business Machines (IBM) OS/2, Microsoft Windows (XP, Vista/7/8, etc.), Apple iOS, Google Android, Blackberry Operating System (OS), or the like. I/O interface 401 may facilitate display, execution, interaction, manipulation, or operation of program components through textual or graphical facilities. For example, I/O interface may provide computer interaction interface elements on a display system operatively connected to the computer system 400, such as cursors, icons, check boxes, menus, windows, widgets, etc. Graphical User Interfaces (GUIs) may be employed, including, without limitation, Apple Macintosh operating systems’ Aqua, IBM OS/2, Microsoft Windows (e.g., Aero, Metro, etc.), Unix X-Windows, web interface libraries (e.g., ActiveX, Java, JavaScript, AJAX, HTML, Adobe Flash, etc.), or the like.

In some embodiments, the computer system 400 may implement a web browser 408 stored program component. The web browser 408 may be a hypertext viewing application, such as Microsoft™ Internet Explorer, Google™ Chrome, Mozilla™ Firefox, Apple™ Safari™, etc. Secure web browsing may be provided using Secure Hypertext Transport Protocol (HTTPS) secure sockets layer (SSL), Transport Layer Security (TLS), etc. Web browsers may utilize facilities such as AJAX, DHTML, Adobe Flash, JavaScript, Java, Application Programming Interfaces (APIs), etc. In some embodiments, the computer system 400 may implement a mail server stored program component. The mail server 416 may be an Internet mail server such as Microsoft Exchange, or the like. The mail server 416 may utilize facilities such as Active Server Pages (ASP), ActiveX, American National Standards Institute (ANSI) C++/C#, Microsoft .NET, CGI scripts, Java, JavaScript, PERL, PHP, Python, WebObjects, etc. The mail server may utilize communication protocols such as Internet Message Access Protocol (IMAP), Messaging Application Programming Interface (MAPI), Microsoft Exchange, Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), or the like. In some embodiments, the computer system 400 may implement a mail client 415 stored program component. The mail client 415 may be a mail viewing application, such as Apple™ Mail, Microsoft™ Entourage, Microsoft™ Outlook, Mozilla™ Thunderbird, etc.
Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present invention. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., non-transitory. Examples include Random Access Memory (RAM), Read-Only Memory (ROM), volatile memory, nonvolatile memory, hard drives, Compact Disc (CD) ROMs, Digital Video Disc (DVDs), flash drives, disks, and any other known physical storage media
Advantages of the embodiment of the present disclosure are illustrated herein.
In an embodiment, the present disclosure provides a method for generating the BRD even of the existing IT enabled system belongs to older or outdated technology.

In an embodiment, the present disclosure eliminates the requirement human effort for understanding the software code to generate the BRD.
The terms "an embodiment", "embodiment", "embodiments", "the embodiment", "the embodiments", "one or more embodiments", "some embodiments", and "one embodiment" mean "one or more (but not all) embodiments of the invention(s)" unless expressly specified otherwise.
The terms "including", "comprising", “having” and variations thereof mean "including but not limited to", unless expressly specified otherwise.
The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.
The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.
A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the invention.
When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device or article or a different number of devices/articles may be used instead of the shown number of devices or programs. The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the invention need not include the device itself.
Finally, the language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the invention be limited not by

this detailed description, but rather by any claims that issue on an application based here on. Accordingly, the embodiments of the present invention are intended to be illustrative, but not limiting, of the scope of the invention, which is set forth in the following claims.
While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.

Referral Numerals:

Reference Number Description
100 ENVIRONMENT
102 BRD GENERATING SYSTEM
104 EXISTING IT ENABLED SYSTEM
106 PRE-BRD DATA
108 BRD
110 RULES
112 EXAMPLE OF SOFTWARE CODE
114 EXAMPLE OF PRE-BRD DATA
116 EXAMPLE OF BRD DATA
202 I/O INTERFACE
204 PROCESSOR
206 MEMORY
208 DATA
210 UNITS
212 SOFTWARE CODE
214 PRE-STORED REFERENCE TABLE
216 NLP DICTIONARY
218 FETCHING UNIT
220 GENERATING UNIT
222 ANALYZING UNIT
224 CONVERTING UNIT
400 EXEMPLARY COMPUTER SYSTEM
401 I/O INTERFACE OF THE EXEMPLARY COMPUTER SYSTEM
402 PROCESSOR OF THE EXEMPLARY COMPUTER SYSTEM
403 NETWORK INTERFACE
404 STORAGE INTERFACE
405 MEMORY OF THE EXEMPLARY COMPUTER SYSTEM

406 USER/APPLICATION
407 OPERATING SYSTEM
408 WEB BROWSER
409 COMMUNICATION NETWORK
410 SOFTWARE CODE
411 INPUT DEVICES
412 OUTPUT DEVICES
413 RAM
414 ROM
415 MAIL CLIENT
416 MAIL SERVER
417 WEB SERVER

We claim:
1. A method of generating Business Requirement Document (BRD) from an existing IT
enabled system (104), the method comprising:
fetching, by a BRD generating system (102), after establishing a connection with the existing IT enabled system (104), software code (212) pertaining to the existing IT enabled system (104) from a memory;
generating, by the BRD generating system (102), pre-BRD data (106) by using a Natural Language Processing (NLP) technique, wherein the pre-BRD data (106) is generated by analyzing a plurality of syntax present in the software code (212), and wherein the pre-BRD data (106) comprises a plurality of operational steps, indicating step by step operation of the existing IT enabled system (104), corresponding to the plurality of syntax being analyzed;
analyzing, by the BRD generating system (102), the pre-BRD data (106) in relative to a plurality of rules (110) in order to determine functional flow of the pre-BRD data (106); and
converting, by the BRD generating system (102), the pre-BRD data (106) into the BRD (108) representing the functional flow determined for the pre-BRD data (106) in form of one or more natural language sentences by using the NLP technique.
2. The method as claimed in claim 1, wherein the pre-BRD data (106) is generated by:
identifying the plurality of syntax from the software code (212); and
correlating each of the plurality of syntax with a plurality of pre-stored syntax meanings present in a form of natural language sentence stored in a pre-stored reference table (214) comprising the plurality of pre-stored syntax and corresponding syntax meaning.
3. The method as claimed in claim 1, further comprising, based on the analyzing of the pre-
BRD data (106) in relative to the plurality of rules (110),
learning about one or more rules, amongst the plurality of rules (110), essential for executing a task and generating the BRD (108).
4. The method as claimed in claim 3, further comprising implementing the learning while
generating BRD (108) of another existing IT enabled system (104).

5. The method as claimed in claim 1, further comprising:
learning about the converting of the pre-BRD data (106) into the BRD (108); updating an internal NLP dictionary (216) based on the learning; and
referring to the internal NLP dictionary (216) during future conversions of future pre-BRD data into future BRD.
6. A business requirement document (BRD) generating system (102) for generating BRD
(108) from an existing IT enabled system (104), the BRD generating system (102) comprising:
a memory storing a set of instructions; and
a processor coupled with the memory, wherein the processor upon executing the set of instructions is configured to:
fetch, after establishing a connection with the existing IT enabled system (104), software code (212) pertaining to the existing IT enabled system (104) from a memory;
generate pre-BRD data (106) by using a Natural Language Processing (NLP) technique, wherein the pre-BRD data (106) is generated by analyzing a plurality of syntax present in the software code (212), and wherein the pre-BRD data (106) comprises a plurality of operational steps, indicating step by step operation of the existing IT enabled system (104), corresponding to the plurality of syntax being analyzed;
analyze the pre-BRD data (106) in relative to a plurality of rules (110) in order to determine functional flow of the pre-BRD data (106); and
convert the pre-BRD data (106) into the BRD (108) representing the functional flow determined for the pre-BRD data (106) in form of one or more natural language sentences by using the NLP technique.
7. The BRD generating system (102) as claimed in claim 6, further generates the pre-BRD
data (106) by:
identifying the plurality of syntax from the software code (212); and
correlating each of the plurality of syntax with a plurality of pre-stored syntax meanings present in a form of natural language sentence stored in a pre-stored reference table (214) comprising the plurality of pre-stored syntax and corresponding syntax meaning.

8. The BRD generating system (102) as claimed in claim 6, is further configured to, based on
the analyzing of the pre-BRD data (106) in relative to the plurality of rules (110),
learn about one or more rules, amongst the plurality of rules (110), essential for executing a task and generating the BRD (108).
9. The BRD generating system (102) as claimed in claim 8, is further configured to implement
the learning while generating BRD (108) of another existing IT enabled system (104).
10. The BRD generating system (102) as claimed in claim 6, is further configured to:
learn about the converting of the pre-BRD data (106) into the BRD (108);
update an internal NLP dictionary (216) based on the learning; and
refer to the internal NLP dictionary (216) during future conversions of future pre-BRD data (106) into future BRD.