Patent Publication Number: US-2016232467-A1

Title: System and method for optimizing the risk during software production release

Description:
PRIORITY CLAIM 
     This U.S. patent application claims priority under 35 U.S.C. §119 to: India Application No. 655/CHE/2015, filed Feb. 10, 2015. The entire content of the aforementioned application is incorporated herein by reference. 
    
    
     TECHNICAL FIELD 
     This disclosure relates generally to a software production release, and more particularly to a system and method for optimizing risk during software production release. 
     BACKGROUND 
     Typically, business requirements are critical activities of an enterprise that must be performed to meet organizational objectives. Such business requirements may be achieved by introducing a software solution. Typically, the software solution may include one or more software projects. Each software project may be developed by a different team and then the various projects may be brought together as a solution to meet the business requirements. The success of a software project may be measured by factors such as timely completion and actual implementation of the business requirements. However, during a software production release, effective prioritization of business requirements for optimizing risk may not be performed. Hence, the business requirements may enter into production without any impact analysis, and risk mitigation being performed. This may lead to high priority defects uncovered in the production. 
     At present, the risk analysis and prioritization is done manually by a business user, which is person dependent and error-prone. There is no systematic way for risk identification and prioritization of project requirements in the release. Slippage of highly critical defects to production cycles may cause a rollback of the release thereby leading to lack of confidence within different business stakeholders. 
     SUMMARY 
     In one embodiment, a risk determination engine to determine risk associated with the software project is disclosed. The risk determination engine may comprise a memory and a processor coupled to the memory storing processor executable instructions to receive one or more project requirements associated with the software project and one or more project defects associated with the software project; identify one or more critical project requirements and one or more critical project defects from the one or more project requirements and the one or more project defects; ascertain a requirement density for the software project based on the one or more critical project requirements and the one or more project requirements; ascertain a defect density based on the one or more critical project defects and the one or more project defects; and determine a cumulative risk score for the software project using the requirement density and the defect density. 
     In another embodiment, a method for determining risk associated with a software project is disclosed. The method may involve receiving by a risk determination engine, one or more project requirements associated with the software project and one or more project defects associated with the software project; identifying, by the risk determination engine, one or more critical project requirements and one or more critical project defects from the one or more project requirements and the one or more project defects; ascertaining, by the risk determination engine, a requirement density for the software project based on the one or more critical project requirements and the one or more project requirements; ascertaining, by the risk determination engine, a defect density based on the one or more critical project defects and the one or more project defects; and determining, by the risk determination engine, a cumulative risk score for the software project using the requirement density and the defect density. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed. 
    
    
     
       BRIEF DESCRIPTION OF THE 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. 
         FIG. 1  illustrates an exemplary diagram for an environment with risk determination engine  102  for determining risk in a software production release in accordance with various embodiments of the present disclosure. 
         FIG. 2  illustrates memory  110  which may include a facts analyzer, a density analyzer, a risk analyzer and a risk optimizer. 
         FIG. 3  illustrates a method for determining risk associated with a software project in accordance with some embodiments of the present disclosure. 
         FIG. 4  is a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     Exemplary embodiments are described with reference to the accompanying drawings. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the spirit and scope of the disclosed embodiments. It is intended that the following detailed description be considered as exemplary only, with the true scope and spirit being indicated by the following claims. 
       FIG. 1  illustrates an exemplary diagram for an environment  100  with risk determination engine  102  for determining risk in a software production release in accordance with various embodiments of the present disclosure. The software production release may comprise one or more software projects. The exemplary environment  100  may include risk determination engine  102 , a test management tool  104 , and a display  106 . Risk determination engine  102  may further include a processor  108 , a memory  110 , an input module  112 , and an output module  114 . While not shown, the exemplary environment  100  may include additional components, such as database etc which are well known to those of ordinary skill in the art and thus will not be described here. The test management tool  104  may be used to store information on how testing is to be done, plan testing activities, report the status of quality assurance activities and defect information. The display  106  may be peripheral devices used to display result of risk determination engine  102  such as a monitor, a projector, a printer. 
     The risk determination engine  102  may assist in optimizing risk in the software production release and is described with examples herein, although risk determination engine  102  may perform other types and numbers of functions. The risk determination engine  102  may include at least one input device  112  CPU/processor  108 , memory  110 , and Output Module  114 , which may be coupled together by bus  116 , although risk determination engine  102  may comprise other types and numbers of elements in other configurations. 
     Processor(s)  108  may execute one or more computer-executable instructions stored in the memory  110  for the methods illustrated and described with reference to the examples herein, although the processor(s) can execute other types and numbers of instructions and perform other types and numbers of operations. The processor(s)  108  may comprise one or more central processing units (“CPUs”) or general purpose processors with one or more processing cores, such as AMD® processor(s), although other types of processor(s) could be used (e.g., Intel®). 
     The memory  110  may comprise one or more tangible storage media, such as RAM, ROM, flash memory, CD-ROM, floppy disk, hard disk drive(s), solid state memory, DVD, or other memory storage types or devices, including combinations thereof, which are known to those of ordinary skill in the art. The memory  110  may store one or more non-transitory computer-readable instructions of this technology as illustrated and described with reference to the examples herein that may be executed by the one or more processor(s)  108 . 
     The input module  120  may receive one or more project requirements and one or more project defects from at least one of the test management module  112  or a user. The output module  160 , may link the risk determination engine  102  with peripheral devices such as a display  106 , to display the risk associated with the software project determined by the risk determination engine  102 . The output module may trigger an email to share the risk associated with the software project with the stakeholders The output module may also be connected to a web based portal to display the risk associated with the software project. 
       FIG. 2  illustrates memory  110  which may include a facts analyzer  202 , a density analyzer  204 , a risk analyzer  206  and a risk optimizer  208 . The facts analyzer  202  may receive the one or more project requirements and the one or more project defects from the input module  120 . The facts analyzer  202  may include a requirement analyzer  210  to analyze the one or more project requirements and a defect analyzer  212  to analyze the one or more project defects. The requirement analyzer  210  may analyze the one or more project requirements to identify one or more critical project requirements. Similarly, defect analyzer  212  may analyze the one or more project defects to identify one or more critical project requirements. The critical project requirements and the critical project defects may be identified based on a predefined weightage assigned to the one or more project requirements and the one or more project defects respectively. 
     Density analyzer  204  may ascertain a requirement density and a defect density based on the one or more critical project requirements and the one or more critical project defects received from fact analyzer  202 . The density analyzer  204  may include a requirement density analyzer  214  and defect density analyzer  216 . The requirement density analyzer  214  may ascertain the requirement density as a product of the one or more project requirements and the one or more critical project requirements divided by a summation of the one or more project requirements and the one or more critical project requirements. The defect density analyzer  216  may ascertain the defect density as a product of the one or more project defects and the one or more critical project defects divided by a summation of the one or more project defects and the one or more critical project defects. 
     Once the requirement density analyzer  214  and defect density analyzer  216  determine the requirement density and the defect density, risk analyzer  206  may then determine a cumulative risk score for the software project based on the requirement density and the defect density. The cumulative risk score may be determined as product of the requirement density and the defect density divided by a summation of the requirement density and the defect density. 
     The risk optimizer  208  identifies the risks involved in the software projects based on the data derived from risk analyzer  206 . The risk determination engine  102  may determine one or more levels of risk associated with the software production release based on the cumulative risk score. The one or more levels of risk may be low, medium and high. A low risk level may be determined as average of minimum cumulative risk score and medium risk level. A medium risk level may be determined as average of maximum cumulative risk score and minimum cumulative risk score. A high risk level may be determined as average of maximum cumulative risk score and medium risk level. 
     Table A illustrates an exemplary embodiment for determining risk associated with a software release. In this example, the software release may include a project 1, a project 2, and a project 3. For project 1, the requirement density may be calculated using the equation: 
     
       
         
           
             
               Requirement 
                
               
                   
               
                
               density 
             
             = 
             
               
                 ( 
                 
                   project 
                    
                   
                       
                   
                    
                   requirements 
                   × 
                   critical 
                    
                   
                       
                   
                    
                   project 
                    
                   
                       
                   
                    
                   requirements 
                 
                 ) 
               
               
                 ( 
                 
                   
                     project 
                      
                     
                         
                     
                      
                     requirements 
                   
                   + 
                   
                     critical 
                      
                     
                         
                     
                      
                     project 
                      
                     
                         
                     
                      
                     requirements 
                   
                 
                 ) 
               
             
           
         
       
     
     Thus the requirement density for project one may be calculated as: 
       Requirement density=(85×17)/(85+17)=14
 
     Similarly, the defect density may be calculated as: 
     
       
         
           
             
               Defects 
                
               
                   
               
                
               density 
             
             = 
             
               
                 ( 
                 
                   project 
                    
                   
                       
                   
                    
                   defects 
                   × 
                   critical 
                    
                   
                       
                   
                    
                   project 
                    
                   
                       
                   
                    
                   defects 
                 
                 ) 
               
               
                 ( 
                 
                   
                     project 
                      
                     
                         
                     
                      
                     defects 
                   
                   + 
                   
                     critical 
                      
                     
                         
                     
                      
                     project 
                      
                     
                         
                     
                      
                     defects 
                   
                 
                 ) 
               
             
           
         
       
     
     Thus the defect density for project one may be calculated as: 
       Requirement density=(76×56)/(76+56)=32
 
     The Cumulative risk score may be calculated as: 
     
       
         
           
             
               Cumulative 
                
               
                   
               
                
               risk 
                
               
                   
               
                
               score 
             
             = 
             
               
                 ( 
                 
                   requirement 
                    
                   
                       
                   
                    
                   density 
                   × 
                   defect 
                    
                   
                       
                   
                    
                   density 
                 
                 ) 
               
               
                 ( 
                 
                   
                     requirement 
                      
                     
                         
                     
                      
                     density 
                   
                   + 
                   
                     defect 
                      
                     
                         
                     
                      
                     density 
                   
                 
                 ) 
               
             
           
         
       
     
     Thus the cumulative risk score for project one may be calculated as: 
       Cumulative risk score=(14×32)/(14+32)=10.
 
     
       
         
           
               
               
               
               
               
             
               
                 TABLE A 
               
             
            
               
                   
               
               
                   
                 Requirement 
                 Defect 
                   
                 Risk 
               
               
                 Input Module 
                 Analyzer 
                 Analyzer 
                 Density Analyzer 
                 Analyzer 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                   
                 Total 
                 Total 
                 No. of Critical 
                 No of Critical 
                 Requirement 
                 Defect 
                 Cumulative 
               
               
                 Projects 
                 Requirement 
                 Defects 
                 Requirement 
                 defects 
                 Density 
                 Density 
                 Risk Score 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 Project 1 
                 85 
                 76 
                 17 
                 56 
                 14 
                 32 
                 10 
               
               
                 Project 2 
                 13 
                 38 
                 2.6 
                 24 
                 2 
                 15 
                 2 
               
               
                 Project 3 
                 38 
                 1 
                 7.6 
                 0 
                 6 
                 0 
                 0 
               
               
                   
               
            
           
         
       
     
     The risk determination engine  102  based on the cumulative risk score may determine low, medium and high levels of risk associated with the software project. A low risk level may indicate successful release of the software project. A medium risk level may indicate a possibility of errors post release of the software project. A high risk level may indicate a possibility of failure post release of the software project. The software projects 1, 2 and 3 may be prioritized for optimizing risk based on the cumulative risk score. The software project 1 may be prioritized as high risk. The software project 2 may be assigned medium risk level and software project 3 may be assigned low risk level. 
       FIG. 3  illustrates an exemplary flow diagram of a method of determining risk associated with the software project, according to some embodiments of the present disclosure. The method may involve receiving, by the risk determination engine  102 , the one or more project requirements associated with the software project and the one or more project defects associated with the software project at step  302 . The one or more project requirements and the one or more project defects may be received by the input module  104  from at least one of the test management tool  104 . 
     On receiving the one or more project requirements associated with the software project and one or more project defects with the software project at step  302  from the Input module  104 , one or more critical projects and one or more critical defects may be identified by the fact analyzer  202  at step  304 . The one or more critical project requirements may be identified by requirement analyzer  210  based on a predefined weightage assigned to the one or more project requirements. The one or more critical project defects may be identified by the defect analyzer  212  based on a predefined weightage assigned to the one or more project defects. 
     At step  306 , the requirement density may be ascertained by the requirement density analyzer  214 . The requirement density may be ascertained as a product of the one or more project requirements and the one or more critical project requirements divided by a summation of the one or more project requirements and the one or more critical project requirements. 
     At step  308 , the defect density may be ascertained by the defect density analyzer  216 . The defect density may be ascertained as a product of the one or more project defects and the one or more critical project defects divided by a summation of the one or more project defects and the one or more critical project defects. 
     At step  310 , the cumulative risk score may be determined by risk analyzer  206 . The cumulative risk score may be determined as a product of the requirement density and the defect density divided by a summation the requirement density and the defect density. 
     Once the cumulative risk score is determined, the software projects are prioritized based on the cumulative risk score by the risk optimizer  208 . One or more levels of risk may be determined by the risk determination engine  102  based on the cumulative risk score. The one or more levels of risk may be low, medium and high. A medium risk level may be determined as average of maximum cumulative risk score and minimum cumulative risk score. A low risk level may be determined as average of minimum cumulative risk score and medium risk level. A high risk level may be determined as average of maximum cumulative risk score and medium risk level. 
     TABLE B, illustrates an exemplary embodiment for determining risk associated with a software release. In this example, the software release may include a project 1, a project 2, and a project 3. For project 1, the requirement density may be calculated using the equation: 
     
       
         
           
             
               Requirement 
                
               
                   
               
                
               density 
             
             = 
             
               
                 ( 
                 
                   project 
                    
                   
                       
                   
                    
                   requirements 
                   × 
                   critical 
                    
                   
                       
                   
                    
                   project 
                    
                   
                       
                   
                    
                   requirements 
                 
                 ) 
               
               
                 ( 
                 
                   
                     project 
                      
                     
                         
                     
                      
                     requirements 
                   
                   + 
                   
                     critical 
                      
                     
                         
                     
                      
                     project 
                      
                     
                         
                     
                      
                     requirements 
                   
                 
                 ) 
               
             
           
         
       
     
     Thus the requirement density for project one may be calculated as: 
       Requirement density=(23×4.6)/(23+4.6)=4
 
     Similarly, the defect density may be calculated as: 
     
       
         
           
             
               Defects 
                
               
                   
               
                
               density 
             
             = 
             
               
                 ( 
                 
                   project 
                    
                   
                       
                   
                    
                   defects 
                   × 
                   critical 
                    
                   
                       
                   
                    
                   project 
                    
                   
                       
                   
                    
                   defects 
                 
                 ) 
               
               
                 ( 
                 
                   
                     project 
                      
                     
                         
                     
                      
                     defects 
                   
                   + 
                   
                     critical 
                      
                     
                         
                     
                      
                     project 
                      
                     
                         
                     
                      
                     defects 
                   
                 
                 ) 
               
             
           
         
       
     
     Thus the defect density for project one may be calculated as: 
       Requirement density=(11×8)/(11+8)=5
 
     The Cumulative risk score may be calculated as: 
     
       
         
           
             
               Cumulative 
                
               
                   
               
                
               risk 
                
               
                   
               
                
               score 
             
             = 
             
               
                 ( 
                 
                   requirement 
                    
                   
                       
                   
                    
                   density 
                   × 
                   defect 
                    
                   
                       
                   
                    
                   density 
                 
                 ) 
               
               
                 ( 
                 
                   
                     requirement 
                      
                     
                         
                     
                      
                     density 
                   
                   + 
                   
                     defect 
                      
                     
                         
                     
                      
                     density 
                   
                 
                 ) 
               
             
           
         
       
     
     Thus the cumulative risk score for project one may be calculated as: 
       Cumulative risk score=(4×5)/(4+5)=2.
 
     
       
         
           
               
               
               
               
               
             
               
                 TABLE B 
               
             
            
               
                   
               
               
                   
                 Requirement 
                 Defect 
                   
                 Risk 
               
               
                 Input Module 
                 Analyzer 
                 Analyzer 
                 Density Analyzer 
                 Analyzer 
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                   
                 Total 
                 Total 
                 No. of Critical 
                 No of Critical 
                 Requirement 
                 Defect 
                 Cumulative 
               
               
                 Projects 
                 Requirement 
                 Defects 
                 Requirement 
                 defects 
                 Density 
                 Density 
                 Risk Score 
               
               
                   
               
            
           
           
               
               
               
               
               
               
               
               
            
               
                 Project 1 
                 23 
                 11 
                 4.6 
                 8 
                 4 
                 5 
                 2 
               
               
                 Project 2 
                 145 
                 56 
                 29 
                 54 
                 24 
                 27 
                 13 
               
               
                 Project 3 
                 63 
                 54 
                 12.6 
                 42 
                 11 
                 24 
                 7 
               
               
                   
               
            
           
         
       
     
     Low, medium and high levels of risk associated with the software project may be determined by the risk determination engine  102  based on the cumulative risk score. A low risk level may indicate successful release of the software project. A medium risk level may indicate a possibility of errors post release of the software project. A high risk level may indicate a possibility of failure post release of the software project. The software projects 1, 2 and 3 are prioritized for optimizing risk based on the cumulative risk score. The software project 1 is prioritized as High Risk. The software project 2 is assigned Medium risk level. The software project 3 is assigned low risk level. 
     Computer System 
       FIG. 4  is a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. Variations of computer system  401  may be used for implementing the risk determination engine. Computer system  401  may comprise a central processing unit (“CPU” or “processor”)  402 . Processor  402  may comprise at least one data processor for executing program components for executing user- or system-generated requests. A user may include a person, a person using a device such as such as those included in this disclosure, or such a device itself. The processor 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 may include a microprocessor, such as AMD Athlon, Duron or Opteron, ARM&#39;s application, embedded or secure processors, IBM PowerPC, Intel&#39;s Core, Itanium, Xeon, Celeron or other line of processors, etc. The processor  402  may be implemented using mainframe, distributed processor, multi-core, parallel, grid, or other architectures. Some embodiments may utilize embedded technologies like application-specific integrated circuits (ASICs), digital signal processors (DSPs), Field Programmable Gate Arrays (FPGAs), etc. 
     Processor  402  may be disposed in communication with one or more input/output (I/O) devices via I/O interface  403 . The I/O interface  403  may employ communication protocols/methods such as, without limitation, audio, analog, digital, monoaural, RCA, 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), RF antennas, S-Video, 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), WiMax, or the like), etc. 
     Using the I/O interface  403 , the computer system  401  may communicate with one or more I/O devices. For example, the input device  404  may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, sensor (e.g., accelerometer, light sensor, GPS, gyroscope, proximity sensor, or the like), stylus, scanner, storage device, transceiver, video device/source, visors, etc. Output device  405  may be a printer, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light-emitting diode (LED), plasma, or the like), audio speaker, etc. In some embodiments, a transceiver  406  may be disposed in connection with the processor  402 . The transceiver may facilitate various types of wireless transmission or reception. For example, the transceiver may include an antenna operatively connected to a transceiver chip (e.g., Texas Instruments WiLink WL1283, Broadcom BCM4750IUB8, Infineon Technologies X-Gold 618-PMB9800, or the like), providing IEEE 802.11a/b/g/n, Bluetooth, FM, global positioning system (GPS), 2G/3G HSDPA/HSUPA communications, etc. 
     In some embodiments, the processor  402  may be disposed in communication with a communication network  408  via a network interface  407 . The network interface  407  may communicate with the communication network  408 . The network interface 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  408  may include, without limitation, a direct interconnection, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, etc. Using the network interface  407  and the communication network  408 , the computer system  401  may communicate with devices  410 ,  411 , and  412 . These devices may include, without limitation, personal computer(s), server(s), fax machines, printers, scanners, various mobile devices such as cellular telephones, smartphones (e.g., Apple iPhone, Blackberry, Android-based phones, etc.), tablet computers, eBook readers (Amazon Kindle, Nook, etc.), laptop computers, notebooks, gaming consoles (Microsoft Xbox, Nintendo DS, Sony PlayStation, etc.), or the like. In some embodiments, the computer system  401  may itself embody one or more of these devices. 
     In some embodiments, the processor  402  may be disposed in communication with one or more memory devices (e.g., RAM  413 , ROM  414 , etc.) via a storage interface  412 . The storage interface may connect to memory devices 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 devices may store a collection of program or database components, including, without limitation, an operating system  416 , user interface application  417 , web browser  418 , mail server  419 , mail client  420 , user/application data  421  (e.g., any data variables or data records discussed in this disclosure), etc. The operating system  416  may facilitate resource management and operation of the computer system  401 . Examples of operating systems include, without limitation, Apple Macintosh OS X, Unix, Unix-like system distributions (e.g., Berkeley Software Distribution (BSD), FreeBSD, NetBSD, OpenBSD, etc.), Linux distributions (e.g., Red Hat, Ubuntu, Kubuntu, etc.), IBM OS/2, Microsoft Windows (XP, Vista/7/8, etc.), Apple iOS, Google Android, Blackberry OS, or the like. User interface  417  may facilitate display, execution, interaction, manipulation, or operation of program components through textual or graphical facilities. For example, user interfaces may provide computer interaction interface elements on a display system operatively connected to the computer system  401 , such as cursors, icons, check boxes, menus, scrollers, windows, widgets, etc. Graphical user interfaces (GUIs) may be employed, including, without limitation, Apple Macintosh operating systems&#39; 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  401  may implement a web browser  418  stored program component. The web browser 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 HTTPS (secure hypertext transport protocol), 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  401  may implement a mail server  419  stored program component. The mail server may be an Internet mail server such as Microsoft Exchange, or the like. The mail server may utilize facilities such as ASP, ActiveX, 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  401  may implement a mail client  420  stored program component. The mail client may be a mail viewing application, such as Apple Mail, Microsoft Entourage, Microsoft Outlook, Mozilla Thunderbird, etc. 
     In some embodiments, computer system  401  may store user/application data  421 , such as the data, variables, records, etc. as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases such as Oracle or Sybase. Alternatively, such databases may be implemented using standardized data structures, such as an array, hash, linked list, struct, structured text file (e.g., XML), table, or as object-oriented databases (e.g., using ObjectStore, Poet, Zope, etc.). Such databases may be consolidated or distributed, sometimes among the various computer systems discussed above in this disclosure. It is to be understood that the structure and operation of the any computer or database component may be combined, consolidated, or distributed in any working combination. 
     The specification has described system and method for optimizing the risk during production release. The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments. 
     Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. 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., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media. 
     It is intended that the disclosure and examples be considered as exemplary only, with a true scope and spirit of disclosed embodiments being indicated by the following claims.