1、 May 2022,IDC#US49054022 White Paper Leveraging RPA and Software Quality Automation to Help Enable Application and Business Optimization Sponsored by:UiPath Melinda-Carol Ballou Maureen Fleming May 2022 IDC OPINION High-quality,adaptive software delivered with velocity enabled organizations to dynam

2、ically shift to digitization,hybrid work,and rapid business execution during the COVID-19 pandemic and now into 2022/2023 and beyond.Automation played and continues to play a key role developers cite lack of automation as the primary inhibitor to productivity in IDCs 2021 PaaSView and the Developer

3、Survey research(of around 1,000 respondents worldwide).IDC also sees a shortage of skilled,professional developers who benefit increasingly from low-code and no-code development,as well as the emergence of citizen developers(who also have visibility into core business needs,but little or no experien

4、ce with testing).Automation in this context fuels digital transformation.We see organizations trending toward intelligent process automation(IPA)and robotic process automation(RPA),expanding beyond business areas(such as HR)into IT and software quality initiatives.As a result of this trend,this pape

5、r considers and evaluates the ways in which application testing can benefit from RPA and,at the same time,how testing can improve RPA quality as a foundation with the potential for increased business responsiveness and efficiency.Successful software testing demands repetition and consistency that ca

6、n be mind numbing for the people involved.At the same time(and in part as a result),human error undermines the accuracy of test results in ways that hide visibility into software defects that derail software quality and deployment velocity.Early approaches to automate tedious manual test cases for i

7、ncreased efficiency were a precursor to current RPA technology.Consequently,testing is an obvious opportunity for applying RPA.There is little distance between building automation with RPA and the user interface(UI)screen flows for test automation.This exemplifies connections and opportunities for e

8、volving into test automation from RPA and to improve RPA quality via test automation.Organizations can have the opportunity with significant overlap to leverage synergies and benefit from using related,connected technology in two different ways using RPA for testing and testing RPA that we are also

9、beginning to observe out in the field.IN THIS WHITE PAPER This white paper discusses the drivers to improve testing and quality through effective use of robotic process automation and also the opportunities to improve the quality,resilience,and stability of RPA 2022 IDC#US49054022 2 running in produ

10、ction.The paper covers core trends related to improving time to value,the use of automation for greater quality and developer productivity,and better collaboration and alignment for the business(leveraging process and task mining as design tools for value stream management).We will consider how data

11、,artificial intelligence(AI),and automation technologies(including RPA and testing)converge to drive cycle time improvements for DevOps leveraging RPA for software quality efficiency and improving RPA quality with coordinated testing.We will also consider the use of process and task mining to decrea

12、se lead times and the benefits of process and task mining for automation planning and how these technologies can enable broader visibility and insight into software quality.The paper lays out the opportunities to improve the quality and consistency of RPA using holistic,integrated testing approaches

13、,as well as chances to accelerate digital transformation initiatives via the benefits of RPA usage for automated testing.We will put this approach in the context of the ability to automate tests faster,to manage and test complex workflows(including coordination with agile DevOps and CI/CD pipelines

14、and low-code/no-code transitions to microservices),and to leverage the benefits of task and process mining for automation planning.At the same time,organizations rely on resilient,relevant,nimble,well-functioning RPA to run their businesses.From that perspective,this paper discusses opportunities to

15、 improve the quality and consistency of RPA and testing approaches to help create a foundation for RPA to be adaptive,responsive,and stable.We will also reflect on opportunities to accelerate digital transformation initiatives by leveraging the benefits of RPA usage for automated testing.And we will

16、 discuss the technology offerings of UiPath,along with recommended strategies to address process change,technology evaluation,and adoption.SITUATION OVERVIEW As organizations compress time frames to execute on digital transformation to drive innovation,efficiency,and an ability to respond rapidly to

17、 competition,time constraint pressures for DevOps are much greater than even a year ago.IDCs most current research shows that nearly 91%of organizations are releasing features with a lead time of a month or less,an increase of 26%compared with 2020.The number of organizations delivering features in

18、one to two weeks doubled over this period(see Figure 1).2022 IDC#US49054022 3 FIGURE 1 Lead Time Acceleration Q.With regard to development lead times,please estimate your average lead time for a feature release/change request?n=200 Source:IDCs Accelerated App Delivery Survey,August 2021 As time to v

19、alue happens sooner,organizations rely on integrated development,continuous testing,and operational capabilities with agile DevOps(and DevSecOps)strategies.Yet,even as DevOps maturity evolves,coordination across fractured Dev and Ops teams is still an issue that impedes high-speed,high-quality softw

20、are delivery.Disconnected business,software development,and quality teams are an obstacle,especially without clear ways to support collaboration and foster a shared understanding of requirements and outcomes.Effective execution demands quality staff with domain subject matter experts(SMEs)and techni

21、cal expertise and there are few team members that have both.We see increasing commitments therefore to collaborative and agile organizational structures,moving away from siloed approaches to help enable improved,agile execution moving into 2022(see Figure 2).9.5%14.5%40.5%23.5%11.5%0.5%1.0%11.5%28.5

22、%50.5%6.0%2.5%0.0%1 day26 days12 weeks34 weeks12 months36 monthsMore than 6 monthsLast year(2020)Today(2021)2022 IDC#US49054022 4 FIGURE 2 Alignment of Development with Business Strategy Q.What best describes your organizations current approach to software development?n=200 Source:IDCs Accelerated A

23、pp Delivery Survey,August 2021 Figures 1 and 2 represent significant process change faster lead times with a broader and more comprehensive understanding of the enterprise and business strategy demand process and organizational change and technologies that support that transition.To meet these deman

24、ds,organizations increasingly can refactor current DevOps strategies to include more automation,increasing use of AI to drive requirements,and greater use of low-code development to break through developer capacity bottlenecks.None of these activities are effective without also improving testing and

25、 application software quality(ASQ).All these changes require a focus on integrating software quality as part of continuous testing strategies and capabilities for DevOps.At the same time,expenses and inefficiencies associated with manual testing still abound versus the benefits(and challenges)of ada

26、ptive approaches to automated testing.In this context,we see 72.5%of organizations increasing their adoption of advanced testing and quality strategies and DevOps,such as AI leverage,integration with CI/CD pipelines,scriptless testing,model-based testing,behavior-driven development,and quality commu

27、nity of practice(see Figure 3).Meanwhile a significant minority at 27.5%uses inefficient manual testing and ad hoc automation.(We have observed the top bottlenecks for software delivery being the need for business integration,followed by manual processes and then testing and quality assurance.)To he

28、lp address these issues,11.5%27.0%43.0%18.5%10.5%8.0%47.0%34.5%Pockets of software development activity as andwhen neededSiloed software development initiatives across theorganization but lack of scale and integrationIndustrialized and integrated software developmentcapabilities with some business a

29、lignmentUnified software development capability across theentire organization with clear alignment to businessstrategyToday2022-19%+16%2022 IDC#US49054022 5 our most current research shows a commitment to adaptive test automation strategies and a growing focus on API testing and emerging engagement

30、with RPA.FIGURE 3 Software Quality Maturity Adopting Advanced Strategies Q.What best describes your organizations approach to software quality?n=200 Source:IDCs Accelerated App Delivery Survey,August 2021 The opportunity to benefit from effective quality strategies(including automation and process c

31、hanges to adopt)is also vital given the levels of complexity even within a single vertical banking system(or point of sale or healthcare)that exemplify the challenges of managing visibility into and assessment of user experience and workflow.Figure 4 indicates the key importance of a value stream fo

32、cus and progressive delivery,along with security and testing.27.5%18.5%23.5%11.0%19.5%Teams use sporadic test automation;largely relyupon manual testing;development teams arecreating unit testingQuality teams collaborate on building a qualitycommunity of practice to share testing bestpractices;incre

33、ased use of automated scripting andautomated acceptance testingDevOps teams are beginning to embrace continuoustesting to support an automated continuous deliveryprocessAdoption of more advanced testing strategies(e.g.,model-based testing and behavior-drivendevelopment BDD test data management);incr

34、eased use of scriptless test automationDevOps teams are experimenting with AI-driven testautomation;teams have achieved continuousintegration with automated build and releasemanagement2022 IDC#US49054022 6 FIGURE 4 Top Priorities in Software Development and Delivery Q.What top software development/d

35、elivery investment areas will your organization prioritize over the next 12 months?n=200 Source:IDCs Accelerated App Delivery Survey,August 2021 IDC observes opportunities to leverage machine learning(ML)and artificial intelligence for smart test creation and coordination to help address the core co

36、mplexity of these challenges.IDC research indicates increased adoption and evolution of ML/AI for intelligent analytics in this context,which is an opportunity to help address core business drivers and openings(and identify areas of frailty)as part of quality.In this way,users will be able to benefi

37、t from analysis of prior outcomes to help improve future execution over time as these capabilities evolve and offer pragmatic,actionable analytics.Benefits include the ability to help create tests for business improvement and better execution,potentially,and improve chances to coordinate systems und

38、erstanding and analysis and to help manage traffic,as well as self-learning openings.30.5%27.5%27.5%26.0%24.0%24.0%23.5%19.5%19.0%19.0%16.0%15.5%12.0%0.5%Value stream managementProgressive delivery(i.e.,feature flags and release automation)SecurityTest automationObservability,remediation,and control

39、Integration and API managementLow-code developmentServerlessContinuous integration/continuous deployment(CI/CD)MicroservicesCode repositories/artifact managementContainer operationsData operations/data pipelinesOther,please specify2022 IDC#US49054022 7 We have also seen a transformation across organ

40、izations from 2020 to 2021 moving into 2022:They have evolved from staying the course to reinvention,with the impact of the rapid shift to digitization because of the pandemic and its aftermath.While 2020 saw 29%of organizations viewing themselves as staying the course and 17%saw themselves as reinv

41、enting,in 2Q21,that shifted down to 14%as continuing to execute on existing strategies and increased to 39%as reinventing and repositioning themselves a dramatic shift(see Figure 5).FIGURE 5 Shifting to Reinvention with Digital Disruption Q.Which of the following best describes your organization?n=2

42、500 Source:IDCs PaaSView and the Developer Survey,May 2021 As part of that reinvention process,businesses are shifting organizational strategies,adopting crossform factor technology analysis and coordination with ML/AI to provide intelligent analysis and overlay of robotic process automation to auto

43、mate mundane,repetitive tasks and driving dynamic workflow.Leveraging Business Automation Technologies to Improve Software Quality and Efficiency Business units began adopting RPA to accelerate efforts to improve business process cycle times,standardize how work is completed,reduce mistakes,and impr

44、ove staff productivity.RPA itself is technology that uses a variety of techniques to mimic or play back how end users interact with their applications.Since that early adoption,RPA is now a centerpiece of automation initiatives,with both development and line-of-business staff involved with automatio

45、n efforts to replace manual,repetitive tasks with software robots.RPA has also evolved to connect workers and software robots together to augment tasks that continue to require manual efforts and is increasingly used to execute long-running 0%5%10%15%20%25%30%35%40%Market disrupter fundamentally cha

46、nging an existing marketMarket maker creating a market that did not previously existUnder reinvention reinventing and/or repositioning your organizationStaying the course continuing to execute existing strategiesTransitioning being sold/acquired/divesting/bankruptcyOther202020212022 IDC#US49054022 8

47、 workflows that link processes and people together across an organization to speed up end-to-end cycle times.Just as business units are heavily focused on improving the cycle times of business operations,IT is also pressured to improve cycle times in IT operations.Identifying where staff in IT opera

48、tions are spending time on manual,repetitive tasks is an opportunity to replace these tasks with automation.The most common response to the question about software quality maturity indicates that testing is performed sporadically and continues to rely on manual testing(refer back to Figure 3).Replac

49、ing manual steps in testing represents a target-rich environment for RPA.Examples of common manual activities involving testing that could benefit from RPA include:EnvironmenEnvironment t mmanagement:anagement:Spinning up a specific virtual machine(VM)with specific setup(An example would be running

50、a break/fix regression for an older version of code.)Test Test d data ata g generation:eneration:Using a robot assistant interactively to generate test data that also involves prompts from a user Status Status r reportingeporting:Replacing manual creation of status reports with automation along with

51、 automated delivery across different channels(Slack,Teams,and email)Test Test p plan lan g guidanceuidance:Creating a new test plan based on prior context,such as change impact,release scope,or suggestions based on failures from past releases Tester Tester c chatbothatbot:Adopting an interactive cha

52、tbot that can answer questions like,What tests failed last night?or Which of my tests need maintenance?or How many defects were found after the last release?(Automation can be used to retrieve the answers to the questions posed in the chatbot.)User User a acceptance cceptance t testingesting:Using s

53、everal different RPA techniques to guide the user through the acceptance testing processing(A bot can also be built to simulate human behavior to streamline automated acceptance testing as a preliminary step before rolling out to users.)Augmenting Software Quality with Process Discovery As teams beg

54、an using RPA,they increasingly focused on identifying ways to improve the accuracy of the automation.They began initially identifying requirements through interviews with staff and realized they were not capturing enough variation or accurate descriptions of how the steps in the process were actuall

55、y performed.This created demand for process and task mining,which collectively can be thought of as process discovery.Process mining captures the log data of enterprise applications used to execute a business process.The mining normalizes and correlates the data and presents a visualization of how a

56、 process operates in production.Typically,an existing Business Process Model and Notation(BPMN)model is used in combination with process mining to show how well the operating process conforms with the desired process represented in the BPMN model.The process improvement team then drills down into th

57、e areas of inefficiency and begins to focus on how to improve those areas while assessing the cost to improve compared with the business value impact gained by making the improvement.The output of the assessment generates a process design document(PDD),and the team also puts together a business case

58、 along with expected key performance indicator(KPI)improvements that would be achievable by implementing the improvements.2022 IDC#US49054022 9 While process mining was a significant advance in understanding precisely where inefficiency exists in a business process,there was also a need to fully und

59、erstand how manual work impacts a process.Task mining tools emerged to solve that problem.Task mining involves installing recorders on designated end-user desktops to capture everything a worker is doing over a period of time.Computer vision is applied to the aggregated streams of data to produce a

60、correlated view of how the same task is completed across a group of workers along with an understanding of variations the task can take.The automation planning team works on identifying which steps in a task are legitimate,which can be improved through better efficiency,and which ones are unnecessar

61、y.This assessment also outputs a lower-level PDD,which is used to determine how much of a manual task can be automated and which parts require workers to continue to be involved.The PDD provides fact-based input that can be used to assess the business value of improving the task using RPA,a combinat

62、ion of RPA and AI,or through a change in the UI itself.Using process and task mining to focus on the exact requirements and the expected impact from improvement can significantly enhance the accuracy,speed,and quality of the improvement.The use of process mining and task mining in combination with R

63、PA also creates a need to build and manage a pipeline of process improvement and automation opportunities,with scoring mechanisms to help determine the order of priority for completing improvement efforts.This approach can also be used to determine the developer capacity needed to deliver the benefi

64、ts in the pipeline leading to decisions about where to cut off projects or how to meet needed capacity.Successful process discovery involves close collaboration between the business and IT.Analyzing the results of both types of mining requires business subject matter expertise as well as developer e

65、xpertise.Both sides should also work on the types of KPIs needed to measure the success of improvement efforts as they unfold.The combination of the process discovery technologies and RPA used in DevOps is compelling.Process and task mining can be used for employee-,customer-,and ecosystem-facing im

66、provements as well as for recording scripts used by software quality teams that can be called on demand in production.And applying Automation Ops can help scaffold and enforce code standards and workflow and code check-ins and/or mandate percentage activity coverage needed before software can publis

67、h.On the DevOps side,organizations doing CI/CD can employ RPA in a structured way to put DevOps pipeline processes and structures in place.Capabilities such as workflow analyzer can help apply quality standards to inform users if certain rules werent followed,incorporating workflow implementation,in

68、cluding continuous testing,as part of software delivery.IDC also sees the emergence of compliance frameworks to preconfigure requirements so that those who use them can help automate compliance with regulatory demands(including related workflow).Automation planning,RPA,and quality strategies can com

69、bine and add value by creating a scaffold for conformance testing.Additional opportunities for testing and DevOps with RPA include automated task mining,impacting areas from manual to exploratory to user acceptance testing.Applying design thinking and leveraging RPA and automation also have the pote

70、ntial to make testing accessible to humanize testing approaches and engage business subject matter experts as well as citizen developers to contextualize quality.And as unpredictable human beings drift and use software in unintended and creative ways,the ability to test for the unexpected also becom

71、es more possible,by documenting usage patterns,process,and workflows(with process mining and task mining).2022 IDC#US49054022 10 This combined approach to testing can bring needed innovation and obvious efficiencies.Business teams can create bots on websites to interact with customers.Bringing robot

72、 assistants into the testing space can enable test managers to trigger RPA to combine reports for all the failed test cases from a prior nights test run rather than spending their morning hours clicking on multiple reports to find out what went wrong.RPA was invented because there were intersections

73、 people shuffling data across areas needed to manage fractured processes efficiently,which is not that different from testing across a diverse landscape with the imperative to coordinate and report across areas.Why not create an RPA that does that report for you and consistently bundle it into your

74、robot assistant for an overview of different projects?RPA can allow users to automate more tests faster and to help contextualize them.Codeless development automation can enable a transition so that developers and testers have a pathway to become automators.And the use of computer vision is an AI ap

75、proach to automate recognition to decompose and make different elements of user interfaces addressable.Users can apply test automation or RPA across traditional applications as well as legacy software,broadening what can be automated and adding resilience and mechanizing what was previously difficul

76、t and complex(like virtualized desktops and point-of-sale systems).With point-of-sale systems,for instance,with RPA,users can efficiently and more reliably manage complex workflows(where before they had to babysit test cases).Overall,IDC sees a range of use cases for benefiting testing and efficienc

77、ies of scale by leveraging RPA.Synergy Between Test Automation and RPA Test automation has much in common with RPA,especially in assets needed to interact with application user interfaces,creating real potential in leveraging the assets and skills across the RPA and testing teams to drive down the c

78、ost of maintaining both systems and combining forces to speed up delivery of results.Commercial software providers have had to learn how to communicate changes to APIs that could cause back-end systems to fail,and theres also an effort to minimize breaking changes caused by changes to APIs.This is d

79、ifferent from changes to application UIs.In that case,there is a lower obligation to communicate change;the UI tends to change often and can be more dynamic than back-end systems.That means there is a greater dependency on IT for managing UI assets for testing and for automation projects involving a

80、ccess to UI,such as using RPA software.Creating and Managing UI as Assets UI testing is required for custom applications and commercial SaaS and datacenter applications.UI changes are often made more frequently than the back-end services and corresponding connectors and APIs.Automation scripts using

81、 RPA focus on interacting with the UI of these same applications to execute an automation script.These scripts become assets that must be managed because they are used repetitively as part of automation whether for testing or for RPA.With RPA,there is a dependency on implementing the features of the

82、 application UI that can be leveraged by developers and business users building their own automation.When application UIs change,they may break an automation script.2022 IDC#US49054022 11 With test automation,there is a similar dependency and those same UI changes may also break the test.Breaks are

83、identified when an automation script fails in production or when a test fails.And these breaks need to be fixed immediately.When the testing team operates separately from the RPA,two teams are charged with fixing the UI and updating the UI asset.In both cases,the goal is identical rapidly identifyin

84、g breaking changes to a UI and fixing them immediately.It is more efficient to share the responsibility between the testing team and the automation team and leverage the UI assets developed across both platforms.Interacting with the UI to Mimic Human Actions Part of any automation that involves repl

85、acing manual activities with automation means that the possible permutations of interaction with the UI must be mapped into individually addressable actions that can be pulled into an automation script.In essence,testing software and RPA software are executing the same automations repetitively.This

86、is a substantial area of duplication with the core application UI.This area of duplication is so common that test automation vendors consider whether they should move into RPA and RPA vendors consider whether they should build their own testing capabilities.For enterprises,converging these testing a

87、nd RPA capabilities can substantially reduce the costs of change management and development of automation scripts.Using AI to Reduce Breaking Changes to UI Both testing vendors and RPA vendors focus on using computer vision and techniques such as anchoring to identify features of a UI object.Theyve

88、largely removed the dependency on location,annotations,and other identifiers to try to minimize changes in the UI that will cause their systems to break.This is another point of synergy,where leveraging the knowledge gained from testing and knowledge gained from RPA will improve the resilience of ru

89、nning scripts and automation scripts running in production.Leveraging Process Discovery to Help Optimize Automation The use of recording technology to capture an individual user performing work in addition to task mining that collects and correlates a team of workers doing the same type of task is c

90、ritical for automation accuracy.This is true of test automation and RPA.Leveraging process discovery across RPA and test automation reduces the time and effort that goes into planning to identify optimal ways to automate and legitimate variations in test scripts.Duplicating this type of complex anal

91、ysis is a tremendous waste of time and effort.Autogenerating Automation Scripts from Process Discovery RPA software provides recorder capabilities to capture keystrokes and mouse clicks.These are converted in the studio environment to automation,either wholly or partially.Process discovery software

92、adds additional capabilities to identify standard approaches and legitimate variations to apply automation across a team of end users performing the same work.RPA vendors are learning how to translate legitimate actions and variations taken by end users into actions that can be invoked in an RPA stu

93、dio.In essence,the road map is to go from process discovery directly to automation.Meanwhile,testing vendors also use process discovery.They are focused on the same outcome.The process discovery creates legitimate actions that can be taken in a script,but those same actions can be mapped to RPA acti

94、ons that will generate an automation.2022 IDC#US49054022 12 Directionally,test automation and RPA are aiming to automate the development of automation.Driving Toward Codeless Automation Test automation suites use low-code and no-code techniques to simplify development of scripts.RPA also uses the sa

95、me techniques.With the addition of autogeneration of automation scripts through recorders and process discovery,test automation and RPA will largely be executed in a codeless fashion by developers,business users,and generated scripts.This approach doesnt fully replace the need to automate in a low-c

96、ode way users have the opportunity to inject programing languages and lower-level technical capabilities to create assets that can be leveraged by an automation script.But most developers and business users will be using codeless techniques to improve how they do their jobs by applying automation wh

97、ether in testing or in replacement of repetitive manual work.The Need for Fully Featured Test Automation Suites and RPA Coordination RPA is only one of a larger set of automation technologies that are increasingly being combined by enterprises to support innovation,faster cycle times,and better cust

98、omer experience.We call this multimodal automation.This move toward leveraging a variety of technologies to achieve transformation and improvement puts even greater pressure on fully featured test automation suites.We increasingly see coordination of testing automation and quality across a range of

99、areas for effective software delivery and DevOps.Capabilities range from typical test automation with functional,regression,performance,load,and user experience to increased demand for areas such as API testing as part of microservices development.Coordinating architecture and design with testing an

100、d quality(leveraging analytics),as well as application security testing(AST)for greater resilience,is a growing imperative.As organizations deploy software across form factors and the omni-channel,digital quality becomes a vital area of focus,enabling adaptive,intuitive,well-performing,and relevant

101、digital experiences.In that context,IDC sees a confluence of the benefits that quality can bring to RPA,just as RPA brings capabilities to improve testing and quality.The four core RPA challenges are as follows:C Complexityomplexity:For organizations that have not yet adopted process or task mining,

102、business processes are complex,with multifaceted documented and undocumented variations that arent typically considered.B Brittlenessrittleness:UI dependencies with RPA mean that as the UI changes,these changes could create breaks that need to be identified and addressed.B Business dependency usines

103、s dependency and dynamismand dynamism:As organizations attain significant automation adoption,they have hundreds of procedures or more that are automated that they must maintain even as the environment changes and changes that impact robotic operations must be tested,which ties in with governance as

104、 well.G Governanceovernance:If something goes wrong,organizations need some sort of documentation trail to understand what happened,especially in verticals with strict compliance requirements like government or pharma.And as organizations scale up RPA usage,these challenges get worse.2022 IDC#US4905

105、4022 13 So how can testing help RPA?Testing brings over 20 years of experience with automation as context to accelerate the process for RPA quality.Initially,automating manual test cases back in the late 1990s seemed like an efficiency miracle.A few years later,organizations figured out that automat

106、ion needed libraries and structure for maintenance.A similar process is happening with RPA as more mature companies ask about and expand strategies for the RPA life cycle.We see some organizations experimenting with Scrum.org,in pursuit of an opportunity to bring the benefits of agile approaches to

107、RPA and incremental,iterative approaches.Creating an agile,quality,and DevOps mindset for RPA can occasionally lead to conflict between business and IT,where the business wants to respond immediately and IT wants it done properly.The key aspect here needs to be better collaboration and putting frame

108、works in place to render it easier for making such changes and transitioning well while considering the consequences of big bang versus incremental,agile development approaches.It is vital not to stymie innovation and to help put frameworks and processes in place to support RPA quality and testing.I

109、DCs recommendation is to shift to agile,adaptive approaches for RPA for effective quality and to incorporate testing as a framework for quality execution for RPA.More holistic testing of automation and the applications it enables should also be a factor.RPA developers can consider quality at a broad

110、er level than just the software at hand to include interconnections between automation,applications,and environments(e.g.,control planes,networks,and infrastructure).And once users create a range of RPA tests,they should look at regression suites to see what they need to retire and consider quality

111、across the landscape.Testing vendors capture the UI and complete UI testing on a regular basis,building a test case for that and running it through on a daily cycle.From that perspective,when you start thinking about RPA,you can understand whether its going to break somewhere on a system that you re

112、ly on.Two things should happen to prevent a break:make sure that change to the UI doesnt create a breaking point in the automation(anchors in computer is one concept)and anticipate a breaking change by doing regular test automation runs to ensure theres nothing thats changed on which the robot is de

113、pending.One of the biggest complaints about RPA is breaking changes,the source that you depend upon.For instance,UI changes occur frequently(especially in the cloud with new releases).So theres a need to figure out a process for taking communications from a cloud provider about a new version of its

114、UI,quickly fixing it,and doing test runs to make sure users have caught the changes and remediated problems that could have resulted.Building business-critical software that runs in production justifies the effort needed for testing.And at some point,oversight for compliance and conformance(meaning

115、conforms to what the model says the activity should do)that is not yet officially a governance issue will become one,as auditors become aware of risks and the need for RPA to be compliant.Some companies have taken a different approach,where they automate the applications and not the processes.For th

116、e screens on the application,they create Lego blocks that RPA and testing teams can then use and reuse.These teams can run standard tests with those components,and if they create a new version,then they update that component and leverage it,knowing that every other automation can use and rely on tha

117、t component to work.Full version control is important to be able to 2022 IDC#US49054022 14 run a regression from that version,updating it as needed,and new objects would be shared with the RPA and testing side.This trend can elevate testing from a cost center to a value center,as automation componen

118、ts built to test applications can be checked into a library for reuse by RPA and vice versa.So organizations should evaluate the ways in which RPA can benefit and enable improved testing and how quality can be applied to RPA initiatives to create an adaptive,reliable,and resilient foundation for aut

119、omation,business execution,and ongoing efforts for digital transformation as organizations journey through these challenging times.IDC also sees the emergence of organizational strategies,crossform factor technology analysis,and coordination with ML/AI to provide intelligent analysis and overlay of

120、RPA to automate mundane,repetitive tasks.Other evolving areas include the ability to leverage digital twin technology to create a virtual model of CRM,ERP,or other applications and their third-party integrations to be able to regression test a range of user journeys,including testing of customized b

121、usiness logic,policies,data fields,and workflows.An example of emerging automation support in these areas is UiPaths Test Suite.LEVERAGING INTELLIGENT AUTOMATION AND RPA FOR TESTING AND TARGETING IMPROVED RPA QUALITY WITH UIPATH TEST SUITE Company Background UiPath was founded in 2005 as DeskOver an

122、d repositioned into RPA in 2013 with the launch of its first UiPath Desktop Automation product line.By 2018,UiPath became the largest provider of RPA platform software,and in 2019,the company had nearly 30.0%share of the intelligent process automation market.With dramatic revenue growth of 80.1%in i

123、ts last fiscal year,UiPath further consolidated its RPA position as it prepared for a successful IPO(2Q21).UiPath broadened its market opportunity for RPA generally and for ASQ with three acquisitions:ProcessGold for process mining(4Q19),StepShot for task mining and process documentation(4Q19),and C

124、loud Elements(1Q21)for API-based automation.UiPath began investing in targeted test automation support as part of a broader strategy to diversify,announcing the general availability release of Test Manager in July 2020.Headquartered in New York City,UiPath has over 4,000 employees worldwide,of which

125、 about 150 are directly attributed to Test Suite and servicing the companys ASQ base of over 1,000 customers.UiPaths products in the context of this testing and RPA quality discussion include UiPath Test Suite.Company Strategy and Product Portfolio UiPaths Test Suite is made up of four tightly integ

126、rated components:Test Manager is a web application hosted by Test Management Hub to manage the testing process including assigning automation to test cases and test cases to requirements,dashboards and reporting,and manual testing.Test Management Hub also integrates Test Suite with third-party ALM t

127、ools.Studio is used to create and design automated tests via a low-code workflow editor.Prebuilt automation activities are also available from the UiPath Marketplace.2022 IDC#US49054022 15 Orchestrator executes tests,whether scheduled or build driven,through a CI/CD pipeline and analyzes the results

128、.Robots execute automated test cases on multiple machines in parallel.Natively,UiPath Test Suite supports functional and regression testing at the UI level and API level and on mobile devices.With UI-based and API-based RPA at its core,Test Suite supports testing more than 190 technologies,from lega

129、cy systems to mobile applications and devices,as well as virtualized systems with UiPath AI Computer Vision technology.For testing outside of Test Suites native capabilities,such as load testing,performance testing,and security testing,UiPath leverages integrations.For example,Studio integrates with

130、 open source technologies such as Selenium or proprietary technology such as Micro Focus UFT or Postman.Orchestrator is integrated with CI/CD pipeline tools via plug-ins and exposes a set of RESTful APIs.Test Manager enables integration with existing ALM tools such as Jira,Xray,ServiceNow,Azure DevO

131、ps,SAP Solution Manager,and qTest.Finally,Test Manager provides an SDK that can enable integration with other test tools such as HP ALM and Redmine.To differentiate its testing and ASQ portfolio,UiPath capitalizes on its technology and dominant position in the RPA market enabling timely,needed coord

132、ination and synergy for testing of RPA and for leveraging RPA as part of testing(incorporating task and process mining increasingly).As part of an enterprise automation platform,Test Suite serves both RPA testing and software application testing missions.Built on production-grade RPA technology,the

133、convergence of RPA and testing permits the sharing of skills,experience,and automation components across the enterprise.RPA itself can be highly beneficial for test automation.For example,UiPath provides predefined automations for testing tasks,such as preparing and ramping up environments or spinni

134、ng up virtual machines.In addition,UiPath empowers automated testing with a scriptless approach,giving developers and testers a pathway to become automators.UiPaths open architecture allows Test Suite to integrate all the testing activities under the same platform so that its easier to test and main

135、tain workflows.Further,the platforms openness can help make testing an integral part of the development process by connecting to ALM tools.By enabling customers to build automations faster,test a range of technologies,and proactively resolve issues,Test Suite helps ensure that applications and autom

136、ated processes are robust and resilient so customers can focus on scaling.UiPath customers with whom IDC spoke were able to apply test automation with RPA on both modern and legacy applications,expanding what could be automated and automating what was previously difficult and complex.One reference e

137、quated the time saved using UiPath for both RPA and Test Suite to a savings of$2.5 million.Customers also cited ease of adoption for regression and cross-platform testing,close connection to key business processes,and collaborative support as contributors to increasing efficiency and speed for testi

138、ng.For one customer,Test Suite helped improve release velocity from every eight months to monthly.In addition,failure rates for their releases decreased from greater than 50%to 12%,which increased users confidence and trust in its applications.Strengths The breadth,depth,and preeminence of UiPaths m

139、arket-leading RPA portfolio provide a solid foundation for the companys testing portfolio.The open architecture and API integration strategies position UiPath to expand and augment its testing portfolio functionality and offer the benefits of broad,supported products that are popularly adopted and d

140、ominant in the market.At the same time,businesses are increasingly dependent on RPA.Demand is growing for testing business-critical RPA components and capabilities that have become increasingly vital with the rise of no-code development,2022 IDC#US49054022 16 which UiPath is singularly well position

141、ed to address.UiPath has a differentiated opportunity to leverage its portfolio synergistically both for software testing efficiency and to address demand for RPA testing.Challenges While UiPaths testing portfolio is rapidly evolving for ASQ,it is still early in its maturation and relies on third-pa

142、rty and/or open source integration to provide capabilities such as performance testing and application security testing.Similarly,though the need is pressing,testing for RPA and RPA for software testing itself are still nascent and evolving,and UiPath is one of only several vendors in the market com

143、bining RPA tools,RPA testing,and ASQ.In that context,market awareness of UiPath as both an RPA provider and a software testing provider is in its early stages,and UiPath is currently investing in this area to increase market awareness.These factors can contribute to challenges in gaining traction an

144、d moving from early engagement to mainstream customers and adoption.UiPaths open architecture is a benefit of course,as are partner integrations in key areas not yet addressed by the platform.However,we expect additional investment in and continued evolution of the UiPath ASQ portfolio to enable own

145、ership and control.Overall,we see UiPath evolving its capabilities for ASQ and synergistic areas at a rapid pace and expect ongoing,significant growth and adoption as the benefits become clearer to a maturing customer and prospect base and demand increases with market evolution.ESSTENTIAL GUIDANCE A

146、ction Items for RPA and Testing IDC recommends that organizations assess organizational maturity levels to increase RPA coordination with quality and testing:Evaluate gaps in test automation and opportunities for bringing in effective RPA adoption for improved customer experience quality across tech

147、nology and workflow areas to increase coordination and to optimize business execution.Assess and appropriately leverage RPA and test automation to benefit from workflow improvements,analytics,and efficiencies of scale to streamline for velocity and quality delivery.Establish proactive design and qua

148、lity management standards with analytics across apps for agile digital quality and DevOps life cycle that encompass resilient,adaptive,secure RPA and software execution.Prioritize automation investments based on key value propositions and business criticality and adopt efficient approaches that are

149、contextualized.Gain executive leadership buy-in and support to create a high-quality and differentiated RPA and testing experience that can accelerate coordinated development and deployment along with foundational,critical workflow,organizational,and process change.Set early and continuous test stra

150、tegies to deliver quality releases and adhere to security management initiatives identify metrics/KPIs and milestones to help determine progress for software assets and progression for combined RPA and quality execution.2022 IDC#US49054022 17 CONCLUSION Process and Organizational Opportunities to Ad

151、opt Emerging Technology for Cross RPA and Testing Execution Process and organizational change are critical to coordinate teams across divergent areas,and lack of education about both the need to collaborate and the appropriate technology to execute for automation testing and RPA must be addressed(in

152、cluding a transition to and adoption of agile approaches).Technology is still evolving with effective AI/ML to offer visibility across these environments.And,at the same time,the use of AI/ML can now begin to provide unifying visibility into actionable insights to help bridge the technology and cult

153、ural gaps between these disparate teams.Reduced complexity with single-platform visibility into RPA and test data,versions,and infrastructure can potentially help enable improved execution.IDC sees a need for adaptive,intuitive reporting with sufficient breadth along with engagement for users across

154、 divergent areas of expertise and focus.This,coupled with pressing demand for testing software and RPA,can help drive increased adoption and engagement and improve software quality for business execution and digital transformation.About IDC International Data Corporation(IDC)is the premier global pr

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