WO2021133160A1 - Système et procédé d'évaluation de risques d'un projet à l'aide de réseaux neuronaux artificiels - Google Patents

Système et procédé d'évaluation de risques d'un projet à l'aide de réseaux neuronaux artificiels Download PDF

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Publication number
WO2021133160A1
WO2021133160A1 PCT/MY2020/050139 MY2020050139W WO2021133160A1 WO 2021133160 A1 WO2021133160 A1 WO 2021133160A1 MY 2020050139 W MY2020050139 W MY 2020050139W WO 2021133160 A1 WO2021133160 A1 WO 2021133160A1
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WIPO (PCT)
Prior art keywords
software application
application project
resources
project
resource
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Application number
PCT/MY2020/050139
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English (en)
Inventor
Ngip Khean CHUAN
Mohamed Redzuan ABDULLAH
Anjana Devi N KUPPUSAMY
Ashok SIVAJI
Fook Ann LOO
Original Assignee
Mimos Berhad
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Publication of WO2021133160A1 publication Critical patent/WO2021133160A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Preventing errors by testing or debugging software
    • G06F11/3668—Software testing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/70—Software maintenance or management
    • G06F8/77—Software metrics

Definitions

  • the present invention relates to the field of project risk estimation. Particularly, the present invention relates to use of artificial neural networks for assessing risk for software application testing projects.
  • Software testing is one of the essential stages in the software development lifecycle to ensure that the software application or software application upgrades developed are of high- quality and function as per requirements requested by an end user.
  • United States Patent 8375364B2 discloses a computer enabled method of estimating testing effort in a testing project by identifying a set of testing parameters and taking into account time needed for completion of a project as well as familiarity of a software tester with the application area and familiarity with the domain of the project.
  • none of the conventional systems provide risk assessment for future software application testing projects based on conditions and progress of one or more current projects or provide a cost versus risk analysis for potential projects.
  • a system for analyzing and providing risk assessment regarding a software application project comprises at least one database to store resource information and one or more on-going software application project related information; at least one input device; a processing unit and a risk assessment module.
  • the risk assessment module when executed by the processing unit is configured to: receive one or more resource related information and/or one or more software application project related information from the database and the input device; and generate a risk score for one or more resources and/or the software application project.
  • the system also comprises at least one graphical user interface communicably coupled to the input device.
  • the graphical user interface when executed by the processing unit is configured to: accept attributes related to a new software application project; provide the parameters to the risk assessment module to generate a risk score for the one or more resources; display the risk score associated with one or more resources to be utilized for completion of the new software application project; prompt a user to iteratively select one or more resources for the new software application project based on the risk score generated for the one or more resources, using the at least one input device; provide the information on the selected resources to the risk assessment module to analyze and provide risk assessment for the new software application project; and display the risk assessment associated with the new software application project.
  • a computer-implemented method for analyzing and providing risk assessment regarding a software application project comprises the following steps: accepting attributes related to a new software application project through a graphical user interface; processing the accepted attributes to generate a risk score for the one or more resources using an risk assessment module; displaying the risk score associated with one or more resources to be utilized for completion of the new software application project on the graphical user interface; accepting selection of one or more resources for the new software application project based on the risk score generated for the one or more resources using at least one input device and analyzing and providing risk assessment for the new software application project based on the selected one or more resources using the risk assessment module.
  • the present invention provides an artificial neural network assisted Human-Computer Interaction, HCI tool which when used typically during early project stage, where information is sparser and less concrete, can enable a project manager to derive a potential project configuration with least risks and subsequently make an informed decision on whether to take or reject a project at this early stage.
  • HCI tool when used typically during early project stage, where information is sparser and less concrete, can enable a project manager to derive a potential project configuration with least risks and subsequently make an informed decision on whether to take or reject a project at this early stage.
  • FIGURE 1 illustrates components for a system for project risk assessment, in accordance with an embodiment of the present invention.
  • FIGURE 2 illustrates an artificial neural network implementation for project risk assessment, in accordance with an embodiment of the present invention.
  • FIGURE 3 is a flowchart showing steps for analyzing and providing risk assessment for a software application project, in accordance with an embodiment of the present invention.
  • FIGURE 4 illustrates an exemplary graphical user interface showing risk scores generated for each resource, in accordance with an embodiment of the present invention.
  • FIGURE 5 illustrates an exemplary graphical user interface showing risk assessment generated for a new software application project, in accordance with an embodiment of the present invention.
  • the present invention may be embodied as a system, method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware or programmable instructions) or an embodiment combining software and hardware aspects that may all generally be referred to herein as an “unit,” “module,” or “system.”
  • FIGURE 1 illustrates an exemplary architecture in which or with which proposed system (100) analyzes and provides risk assessment for a software application testing project.
  • proposed system 100
  • FIGURE 1 illustrates an exemplary architecture in which or with which proposed system (100) analyzes and provides risk assessment for a software application testing project.
  • the system (100) comprises at least one database (102) to store resource related information and information on current condition and progress of one or more on-going software testing application projects.
  • the resource related information and information on current condition and progress of one or more on-going software testing application projects may be manually updated into the database (102). Alternatively, this information may be derived from other sources such as existing project management databases, testers personnel management database, or software defect management database.
  • the term “resource” refers to individuals or workforce which are assigned to carry out designed tasks in the software application project.
  • the term resource may also be extended to non-human assets such as machines, servers or workstations.
  • the resources are software application project testers and the resource related information stored in the database (102) includes the following parameters for each one of the software testers: rate of test issues generated per five testing days, number of words per issue per five testing days, number of pictures per issue per five testing days, tester’s mobility rate, tester’s working experience and tester’s distance from one or more future projects.
  • the software application project related information includes project’s potential workload demand.
  • the “per five testing days” typically are the last five days a tester has raised issues in a defect management system hosted by an organization. These five days may be consecutive days or any five days selected for the testers in any random order.
  • the parameter ‘the number of words per issue per five testing days’ is a count of textual description provided by a tester for different stakeholders. For instance, feedback for management stakeholder may be how the defects impact management bottom line Key Performance Index (KPIs) like cost to fix the defects, time taken to fix the defects, recommendation of a subject matter expert, in an emerging field such as deep learning algorithm, artificial intelligence, big data analytics or space exploration. Further, the parameter ‘number of pictures per issue per five testing days’ is a numerical value which captures a count of the pictures captured during testing to provide visualization or visual cues to supplement the issues generated by the tester.
  • KPIs Key Performance Index
  • tester s working experience’ is a numerical value based on either number of years of experience in testing or number of professional certifications or number of academic qualifications obtained by the tester.
  • the parameter tester’s distance from one or more future projects is a numerical value measured in miles, kilometers, hours or even days of travel.
  • mobility rate is a rating, given based on kind of transportation that the tester is using to get to testing site including but not limited to car, motorcycle and public transport. For instance, for travel within a city, mobility rate of motorcycle may exceed that of a car. However, for out-of-city travel, a car would have better mobility than the motorcycle. Also, depending on location of the testing site, better public transport availability would yield a higher score.
  • the score for the mobility rate is generated based on the following factors including: 1) the tester could drive a car 2) the tester could drive a motorcycle and 3) the track record of punctuality.
  • the underlying data for the score for mobility rate may be captured automatically either in the form of a mobile application or a tester radio frequency identification (RFID) tag or manually in the form of a score card.
  • RFID radio frequency identification
  • the scoring may be in a form of employee productivity metrics which would assign higher points given for willingness and capability of driving a car, motorcycle or being resourceful in carpooling or using public transportation. Likewise, higher points will be assigned to a tester based on punctuality recorded in arriving for client meetings. Conversely, points may be deducted for tester’s with lack of mobility or unavailability to work at a remote site. Points may also be deducted for missing or not being punctual for meetings.
  • the system (100) also includes at least one input device (104) and at least one graphical user interface (112) which are communicably coupled to facilitate Human Computer Interaction (HCI) and enable project managers to analyze and asses risk associated with a potential software application project.
  • HCI Human Computer Interaction
  • the system (100) includes a processing unit (106).
  • the at least one processing unit (106) may be implemented as one or more computing device including microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate digital signals based on operational instructions.
  • the at least one processing unit (106) is configured to fetch and execute computer-readable instructions stored in at least one memory unit (108) to analyzing and providing risk assessment regarding a software application project.
  • the processing unit (106) includes one or more interfaces which enables the processing unit (106) to communicate with external devices as well as the input device (104) and the graphical user interface (112) to accept attributes related to a new software application project and facilitate analysis and risk assessment for the new software application project.
  • the interface also facilitates optical, wired or wireless communication with external communication networks and hardware devices to enable the processing unit (106) and the graphical user interface (112) to be hosted in the same premises, disturbed over geographical remote premises or hosted over a virtual appliance such as the cloud.
  • the at least one memory unit (108) may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, magnetic tapes, compact disc read-only memories (CD-ROMs), and magneto-optical disks, or other type of media/machine-readable medium suitable for storing electronic instructions (e.g., computer programming code, such as software or firmware).
  • the memory unit (108) may include modules and data.
  • the modules include routines, programs, objects, components, data structures and the like, which perform particular tasks or implement particular abstract data types.
  • the module may include a risk assessment module (110).
  • the memory unit (108) may not be limited with the aforementioned module (110) but may include other programs or coded instructions that supplement applications and functions of the system (100).
  • the risk assessment module (110) provided in the memory (108) when executed by the processing unit (106) is configured to receive one or more resource related information and/or one or more software application project related information from the database (102) and the input device (104) and generate a risk score for one or more resources and/or the software application project.
  • the risk assessment module (110) employs an artificial neural network (ANN) which includes at least seven inputs nodes, one hidden layer, and one output, which is the risk score as seen in FIGURE 2.
  • the inputs provided to the ANN are retrieved from the database (102) and include rate of test issues generated per five testing days, number of words per issue per five testing days, number of pictures per issue per five testing days, tester’s mobility rate, tester’s working experience, tester’s distance from a future project, and project’s potential workload demand.
  • the inputs provided to the ANN are entered manually by the project manager using the input device (104). All the ANN inputs and output values are normalized to a value between 0 and 1 .
  • the ANN uses a three-layer back propagation (BP) network, wherein the output value of 0 or 1 is iteratively generated until a robustness goal is met. For instance, the robustness goal may be having an error of less than 5%.
  • BP back propagation
  • the system (100) includes at least one graphical user interface (112) communicably coupled to the input device (104).
  • the graphical user interface (112) when executed by the processing unit (106) is configured to accept attributes related to a new software application project via one or more input devices (104).
  • the attributes related to a new software application project include rate of test issues generated per five testing days by each resource, number of words per issue per five testing days by each resource, number of pictures per issue per five testing days, tester’s mobility rate, tester’s working experience, tester’s distance from a future project and potential workload demand of the new software application project.
  • These attributes received via the input device (104) are provided to the processing unit (106) which further provides it to the risk assessment module (110) to generate a risk score for the one or more resources.
  • the generated risk score associated with one or more resources to be utilized for completion of the new software application project is then received and displayed on the graphical user interface (112).
  • the graphical user interface (112) prompts a user (or project manager) to iteratively select one or more resources for the new software application project based on the risk score generated for the one or more resources, using the at least one input device (104).
  • the input device (104) may take the form of a touchscreen-based input, a keyboard-based input or a pointing device-based input such that a project manager is capable of having a drag and drop interaction for selection of one or more resources for the new software application project.
  • the graphical user interface (112) is further configured to provide the information on the selected resources to the risk assessment module (110) to analyze and provide risk assessment for the new software application project; and display the risk assessment associated with the new software application project.
  • the project manager may iteratively select different combinations of resources based on their scores to assess the risk score generated for the new software application project.
  • FIGURE 1 represents the major components of the system (100) for analyzing and providing risk assessment for a software application project, but these components may be combined or divided depending on the particular design without limiting the scope of the present disclosure.
  • FIGURE 3 represents a method for analyzing and providing risk assessment for a software application project.
  • the method comprises the steps of maintaining a database for storing information regarding software testers as well as one or more on-going software application project related information.
  • the method is initiated by accepting the attributes related to a new software application project through an input device communicably coupled to a graphical user interface.
  • These attributes include rate of test issues generated per five testing days by each resource, number of words per issue per five testing days by each resource, number of pictures per issue per five testing days by each resource, resource’s mobility rate, resources’ working experience, resource’s distance from a future project and potential workload demand of the new software application project.
  • the value of these attributes may be derived from other sources such existing project management databases, testers personnel management database, or software defect management database.
  • step (1002) the attributes received for the new software application project as well as existing resource related information and on-going software application project(s) related information are provided to a risk assessment module to generate a risk score for each one of the resources or software testers.
  • the risk score for the resources is then displayed on the graphical user interface (step 1004), as seen in FIGURE 4.
  • the graphical user interface prompts the user (or project manager) to select one or more resources to be utilized for completion of the new software application project.
  • the user is allowed to perform a drag-and-drop interaction in order to assign the testers to the new project.
  • the selected one or more resources are provided to the risk assessment module to calculate a risk score for the new software application project. This time the input comprises the average value of all testers within the same project. The risk score is then displayed to the user as seen in FIGURE 5.
  • an exemplary graphical user interface (112) is presented.
  • Line 305 separates the graphical user interface (112) into two parts: a left side for current events and a right side for new events.
  • step (1002) is completed, on the left side there are five testers (301) displayed in two ongoing project projects (302). Meanwhile there are two testers (303) that are not involved in any projects.
  • Each tester (301 , 303) has been provided a space to display the tester risk score as calculated in step (1002).
  • the graphical user interface (112) also has space to display additional information to identify the testers (301 , 302, 303) such as by their name and profile picture.
  • On the right side there is one new project (304).
  • the new project (304) has empty space at the moment as the risk assessment for the new software application project is pending.
  • the graphical user interface (112) is presented as seen in FIGURE 4, one skilled in the art would appreciate that the present layout is not limiting and other layouts of the graphical user interface (112) can be achieved to display the outcome as per the teachings of the present invention.
  • FIGURE 5 shows a layout of the graphical user interface (112) after the step (1008) is completed.
  • two tester user interface objects (311 , 312) have been dragged and dropped from 301 and 303 into the new project window (304).
  • Window labelled by reference numeral (310) as seen in Figure 5 shows the new state of the graphical user interface (112).
  • the tester user interface objects moved are testers (311) and (312).
  • the new software application project (304) changes to a new project (313) where a risk score is displayed based on the testers dropped into this new software application project (304). For instance, a 70% risk score would indicate that if the new project is accepted then there are 70% chances that the project timelines and workload demands can be met.
  • the graphical user interface (112) also has the option of saving various scores generated for the resources and the projects for future reference or comparison.
  • the graphical user interface (112) further enables the user (or project manager) to hide tester user interface objects or on-going projects from the graphical user interface (112) so that they may be not available for selection.
  • the user is given the opportunity to iteratively drag and drop resources (or testers) to the project window (304) to generate a new risk score for assessing the risk of undertaking a new software application project (step 1010).
  • the selection of testers can be done to check for various combinations to decide on whether to undertake the new project. Flence, the steps (1006 to 1010) can be repeated until the user (or project manager) decides to undertake the project based on the latest resource selection or declines the new project (step 1012).
  • the present invention can take the form of a computer program product accessible from a machine-readable media providing programming code for use by the system (100).
  • the software and/or computer program product can be hosted in the environment of FIGURE 1 to implement the teachings of the present invention.
  • An apparatus for practicing various embodiments of the present invention may involve one or more computers (or one or more processors within a single computer) and storage systems containing or having network access to computer program(s) coded in accordance with various methods described herein, and the method steps of the invention could be accomplished by modules, routines, subroutines, or subparts of a computer program product.

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Abstract

Sont divulgués un système (100) et un procédé d'analyse et de fourniture d'évaluation de risques concernant un projet d'application logicielle. Le système (100) comprend au moins une base de données (102) servant à stocker des informations relatives à des ressources et une ou plusieurs informations associées à un projet d'application logicielle en cours ; au moins un dispositif d'entrée (104) ; une unité de traitement (106) ; un module d'évaluation de risques (110) servant à recevoir une ou plusieurs informations relatives à une ressource et/ou une ou plusieurs informations relatives à un projet d'application logicielle provenant de la base de données (102) et du dispositif d'entrée (104) en vue de générer un score de risque pour une ou plusieurs ressources et/ou le projet d'application logicielle ; et au moins une interface utilisateur graphique (112) servant à accepter des attributs associés à un nouveau projet d'application logicielle et à afficher un score de risque pour ladite une ou plusieurs ressources et à fournir une évaluation de risques destinée au nouveau projet d'application logicielle sur la base des scores de risque.
PCT/MY2020/050139 2019-12-24 2020-11-09 Système et procédé d'évaluation de risques d'un projet à l'aide de réseaux neuronaux artificiels WO2021133160A1 (fr)

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MYPI2019007769 2019-12-24

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140282354A1 (en) * 2013-03-15 2014-09-18 International Business Machines Corporation Automated team assembly system and method
US20160224896A1 (en) * 2015-02-03 2016-08-04 International Business Machines Corporation Group generation using sets of metrics and predicted success values
CN107274071A (zh) * 2017-05-24 2017-10-20 华为技术有限公司 组建团队的方法及装置

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140282354A1 (en) * 2013-03-15 2014-09-18 International Business Machines Corporation Automated team assembly system and method
US20160224896A1 (en) * 2015-02-03 2016-08-04 International Business Machines Corporation Group generation using sets of metrics and predicted success values
CN107274071A (zh) * 2017-05-24 2017-10-20 华为技术有限公司 组建团队的方法及装置

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