A robot is not coming to take your job

softwarebuck April 25, 2021 0 Comments



Diversifying The Roles of Software Testers


With Artificial Intelligence continually evolving and maturing, it is easierto predict machines will take over most of the test execution. In doing so,companies will be able to implement efficient testing methodologies, however,this also calls for the development of new skills for QA engineers.To continually better the working relationship between man and machine,software testers will need to outsmart machines in areas that will drive moregrowth.By increasing competency in AI testing, math optimization, algorithmicanalysis, business intelligence, and neuro-linguistic programming, futuresoftware testers will have the skill set they need to step into the new rolesrequired to continually better this area of software development.Some of these new roles will require software testers to build machinelearning algorithms, understand data flow and math models, as well as toconduct predictive analysis to form new AI strategies.It is predicted that software testers will have to take on a new supervisoryrole to teach AI to execute tests, analyze certain information, and workthrough huge amounts of data in record time.Although there is still a long way to go, it is believed that AI will betaking over nearly 70% of repetitive testing space. Software testers willfocus on the remaining 30% by monitoring the progress of AI, modelingworkflow, and devising new test plans and QA strategies.

Identifying Key Areas In Need Of AI Integration


Since AI integration is still a new development, and new roles that bridge thegap between numerous business requirements and different AI functions stillneed to be formed and filled, there is currently a lack of expertise withregards to integrating AI to truly maximize profits.The real conundrum lies in identifying key business areas that require AItechnology to improve on its profitability and save on expensive resources.More often than not, individuals who excel in business do not possess adequatelevels of AI expertise to know how and where it can be implemented. On theother hand, AI professionals will also not be able to understand everycompany’s unique needs and where AI can improve on performance.

AI Testing Expertise


As we broaden our scope on intelligent testing, the skills of software testerswill continue to improve.Over time, more fields of expertise will emerge and roles within those fieldswill be filled. However, the current demand for qualified software AI testerswill continue to climb as more industries experiment with intelligent testingwhich means that the current market is running on short supply.Until the level of AI expertise needed to effortlessly grow businesses isreadily available to all companies, growth in AI application will be limited.

The new age testing is here!


With the introduction of AI and ML, software testing will become even better.AI with the help of ML can write its own line of code by stealing fromexisting software. It can also be used for test execution and maintenance.Test automation and regression testing will only be smarter, faster and betterwith the introduction of AI. The testers can stop worrying about the usualboring tasks and start concentrating on better strategies.

Will AI & ML kill software testing?


No, AI & ML will not kill software testing, it will only get better with thehelp of AI & ML. Software testers should not fear AI, instead, they should bethinking of a practical way to incorporate both AI & ML in their work, thiswill help them achieve better results. AI will help you identify bugs quickerand faster.Let’s say organizations are preferring AI testing apps over humans to run testcases. Though these AI apps will deliver precise results, they lack some ofthe key aspects such as, scalability, performance, management, documentationand security, which can be provided by humans alone.

The impact of AI & ML in software testing


We have seen the capabilities of AI and ML in the past and what it can do inthe future. The software industry, in particular, will see a lot of changes.The software testers are not here to compete with AI & ML. Rather they aregoing to help in enhancing AI and ML-based tools.In my opinion, Artificial Intelligence and Machine Learning will broaden ourhorizon and opportunities.The speed at which the organizations demand their software to be launched isoutrageous. Not to blame the organizations, the competition makes them takesuch decision. Thus, the necessity for software to be developed and testedquickly. Here are some of the changes you can expect to see in softwaretesting with the introduction of AI• AI will boost accuracy. Just like test automation, but even better.• AI will expand the overall length and scope of testing.• AI will enhance the quality of the software.• AI will ensure a faster turnaround.

Is this the end for Manual testers?


AI is a milestone in the software industry. However, it is creatinguncertainty amongst the manual testers with respect to their job. Manualtesting is one of the oldest and traditional methods of testing. However, willsoftware testing be the same way as today is the biggest question? The answeris, it will not be the same, but then you need manual intervention to designtesting strategies. In the future, both manual testing and AI will coexist.However, the software testers will need a different set of skills to survive.They should build their data science skills and should be able to understandhow Machine Learning works.

‘Catching bugs earlier’


According to QA Financial, Test Plant believes there is “a lot of talk” whenusing artificial intelligence to test, yet no one is using it in a “usefulway”, because of testers involving it straight into testing processes, insteadof using it to plan beforehand.Senior test manager at Allied Testing, Stas Milec, agreed: “Tests do not makesoftware any better. Your product might be working well, but if it’s notsomething a customer expects, then it’s the wrong product. It’s important toget people involved in the validation process throughout.“My strong believe is that AI will start playing a significant role in testing– we should see AI dynamically generating test cases, while building knowledgeabout the software developer ability, whilst learning how customers use aparticular type of software.”Analytics India revealed that AI has made its way through software testingthrough a lack of infrastructure, and the need for faster deployments,involving three main aspects – testing in real-world customer environments,user acceptance testing and manual testing.“A lot of things are going to change in the testing field with the entry ofAI. Almost 70% of testing is repetitive and AI can quickly occupy that space.The 30% left is questioning the system, and that’s what testers need to focuson. AI is the next big thing in testing, but it won’t replace humans. Thetesters working alongside AI can quickly revolutionise the way we test today,”added Vijay Shinde, founder of Software Testing Help.

‘Helping experts test effectively’


Mark Roberts, head of test at Capita IT, added: “In the software testingindustry, automation and AI provide support to the individual in theworkplace, with automation allowing individuals to focus on more meaningful,higher value activities.“However, companies such as Blue Prism have produced automation tools that goone step further and successfully automate full testing business transactionacross multiple platforms, allowing for successful automation of back officebusiness processes, which will effectively lead to a reduction in theadministrative work force.”A report by Transparency Market Research found many companies are operating inthe fields of IT robotic automation tools and IT robotic automation services.It appears the market is rising in competition, and witnessing wider changes,especially those firms with development budgets, tight training and cost-effective solutions, such as: Blue Prism, Be Informed B.V, Appian, IPSoft,Tata Consultancy Services Limited, Infosys Limited, Sutherland Global Servicesand UiPath Srl.Robert added: “AI is relatively new; it is starting to aid defect diagnosis,and is the root cause analysis, which very much relies on existing test data.However, I feel that as we get to grips with this technology, it will becomemore powerful and likely start to replace much of the analysis that is done intesting.”

‘A robot is not coming to take your job’


CEO of TestPlant, John Bates, said to the SD Times: “There’s a lot of talkcurrently about test automation. However, in reality, we’ve only automated onekey element: test execution. AI and analytics will be the catalysts to delivertrue test automation that recommends the tests to carry out, learnscontinuously, enabling it to predict business impacts enabling DevOps teams tofix issues before they occur. This will help teams to keep up with userexpectations and the pace of DevOps something they are struggling with today.”During test execution the test manager should monitor the progress as per thetest plan, and if required, he/she needs to take control actions in terms ofobjective and strategy.Bates added: “Software testers have a very key role. It is absolutelyimportant to understand AI isn’t a robot coming to take your job, but is asmart assistant instead. The software tester is still responsible formodelling the workflow that you have, and setting up the environment andtooling.”“They are just the ones reviewing the results and looking at the interface toprovide recommendations from the systems and the feedback to the developmentteam and to the business.”Johan Steyn, senior manager for enterprise software quality at Nedbank,agreed: “From the point of view of software testing and quality assurance, Isee a definite trend and a push to bring automation into the software testingtrade. Technologies around cognitive tools, artificial intelligence andmachine learning enable testing teams to test smarter and faster.”It appears that AI assists, and does not replace peoples’ jobs. Software can’tbe released quick enough, playing a large role in innovation and technology.Consumers need to assess how AI can help achieve larger outcomes by involvingAI straight into the testing process.Written by Leah AlgerDoes AI replace or assist?Does artificial intelligence (AI) replace software testers, or assist? To findout what effect AI has on tech-savvy individuals, Test Magazine reporter, LeahAlger, receives vitalising views from an array of software testersWe have witnessed the mobile and computer revolution – now similarly –artificial intelligence (AI) is unrolling its potential; not only by the waywe live, but also within the majority of industries, including softwaretesting firms.Technology is being implemented within development teams and tools to catchbugs earlier, automatically assessing and correcting code. According toCognifide, we need to accept that, within the next two years, AI techniqueswill fully dominate IT, with Amazon, Google, Facebook, IBM and Microsoft beingone of many signs.“IBM and Google aren’t the only companies applying AI techniques. Within thepast year, AI in software testing has also become feasible. Software testingmust evolve in response to the shift to agile and DevOps. No matter how manytesters you employ, it’s simply not possible for manual testing to provideagile developers immediate feedback on whether any of their constant changesimpacted the existing user experience,” wrote Tricentis in a blog post.

‘Catching bugs earlier’


According to QA Financial, Test Plant believes there is “a lot of talk” whenusing artificial intelligence to test, yet no one is using it in a “usefulway”, because of testers involving it straight into testing processes, insteadof using it to plan beforehand.Senior test manager at Allied Testing, Stas Milec, agreed: “Tests do not makesoftware any better. Your product might be working well, but if it’s notsomething a customer expects, then it’s the wrong product. It’s important toget people involved in the validation process throughout.“My strong believe is that AI will start playing a significant role in testing– we should see AI dynamically generating test cases, while building knowledgeabout the software developer ability, whilst learning how customers use aparticular type of software.”Analytics India revealed that AI has made its way through software testingthrough a lack of infrastructure, and the need for faster deployments,involving three main aspects – testing in real-world customer environments,user acceptance testing and manual testing.“A lot of things are going to change in the testing field with the entry ofAI. Almost 70% of testing is repetitive and AI can quickly occupy that space.The 30% left is questioning the system, and that’s what testers need to focuson. AI is the next big thing in testing, but it won’t replace humans. Thetesters working alongside AI can quickly revolutionise the way we test today,”added Vijay Shinde, founder of Software Testing Help.

‘Helping experts test effectively’


Mark Roberts, head of test at Capita IT, added: “In the software testingindustry, automation and AI provide support to the individual in theworkplace, with automation allowing individuals to focus on more meaningful,higher value activities.“However, companies such as Blue Prism have produced automation tools that goone step further and successfully automate full testing business transactionacross multiple platforms, allowing for successful automation of back officebusiness processes, which will effectively lead to a reduction in theadministrative work force.”A report by Transparency Market Research found many companies are operating inthe fields of IT robotic automation tools and IT robotic automation services.It appears the market is rising in competition, and witnessing wider changes,especially those firms with development budgets, tight training and cost-effective solutions, such as: Blue Prism, Be Informed B.V, Appian, IPSoft,Tata Consultancy Services Limited, Infosys Limited, Sutherland Global Servicesand UiPath Srl.Robert added: “AI is relatively new; it is starting to aid defect diagnosis,and is the root cause analysis, which very much relies on existing test data.However, I feel that as we get to grips with this technology, it will becomemore powerful and likely start to replace much of the analysis that is done intesting.”

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