EXTENT-2017: Putting AI to Test

EXTENT-2017: Software Testing & Trading Technology Trends Conference
29 June, 2017, 10 Paternoster Square, London

Putting AI to Test
Shalini Chaudhari, Managing Director, Technology, Accenture

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Transcript

1. Putting AI to Test
2. Copyright © 2017 Accenture All rights reserved. 2 Quantum Computing IoT and Smart Machines Big Data, Analytics, Visualization Web 2.0, Cloud, Mobile Web 1.0 eCommerce Client-Server and PCs Mainframe System/360 SAP PC Sales of PC Peak Public Internet Amazon System /360 Web 2.0 iPhone Big Data IOT, M2M IDC: 4.4 Zettabytes of data Public Cloud Mainstream Server/Host ARPANET AWS Salesforce.com IBM Deep Blue Self-driving car Technology’s Next big Wave… Artificial Intelligence
3. 3 Copyright © 2017 Accenture All rights reserved. LET’S ASK CAN WE USE AI FOR TESTING?
4. 4 Copyright © 2017 Accenture All rights reserved. PRECISION TESTING IS ONE OF THE SOLUTIONS THAT ADDRESSES THE DEMANDS FOR ‘EFFICIENCY’ OF NEW AGE APPLICATIONS Precision Testing is a suite of modern Machine Learning, Artificial Intelligence and Statistical Modelling algorithms that aims to bring ‘efficiency’ into Testing. It offers innovative solutions over different phases of the testing life-cycle, from planning to design and execution. Source: Accenture Proprietary INTELLIGENT DESIGN PRECISION TESTING AUTOMATE SELF-ADAPTING PRESCRIPTIVE AUGMENTED Bringing in novel methods to automate the execution of test scripts, which is easy to create and easy to maintain By leveraging the trained models, predictions on the future state of the system is made and actions to be taken can be prescribed Learnings from past project experiences are modeled and used to train machine learning algorithms Augment delivery using a virtual assistant. An intelligent advisor has the ability to seamlessly orchestrate giving the tester a single interface to communicate with.
5. 5 Copyright © 2017 Accenture All rights reserved. Predictive analytics learns from past test results to predict future outcomes & help prioritize the testing effort. • Where should I prioritize my testing effort? • Can I predict whether a test script is going to pass or fail? • How effective has been my testing? Learn from past data using Bayesian Statistics Visualise testing efficiency over cycles Predict test failures using Machine Learning SELF-ADAPTING Source: Accenture Proprietary PREDICTIVE ANALYTICS USING BAYESIAN STATISTICS
6. 6 Copyright © 2017 Accenture All rights reserved. TEST MANAGEMENT THROUGH SIMILARITY ANALYTICS Eliminates redundancies, brings deeper insights, and makes intelligent recommendations for effective test management with reduced costs and efforts. • Are our test suites bloated? • Are we raising similar defects again? • Are our defect fix assignments getting redirected again? • Are we designing regression test-suites with assessment of underlying risks? • Are our tests yielding deeper insights? Learn from past defect logs and test suites Visualize central problem areas, their coverage and interrelatedness Identify duplicates and semantically related tests and defects using similarity analytics PRESCRIPTIVE Source: Accenture Proprietary
7. 7 Copyright © 2017 Accenture All rights reserved. Recognizes voice Understands language Maintains a dialog Creates a reply Speaks to you Knowledge Advisor that bootstraps new testers Decision advisor through Predictive and similarity analytics Diagnostic Advisor through similarity analytics Conversational Interface as a Decision Advisor Testing advisor: Hi John. What can I do for you today. John: please suggest the next set of test cases to execute Testing advisor: There are 3 modules: Excel Reader, Grammar, and Scope Resolution which have high business criticality and high fault prediction. I suggest that you start testing these modules. John: show me the test cases of the ExcelReader. Testing advisor: The ExcelReader module has 25 test cases. Displaying the details. AUGMENTED THE INTELLIGENT VIRTUAL AGENT FOR TESTING: AKA TESTING ADVISOR The testing advisor assists the tester through the entire project lifecycle by providing project specific knowledge, as well as ai based decision and diagnostic support.
8. 8 Copyright © 2017 Accenture All rights reserved. This is what a Human sees This is what a Machine sees Source: Accenture Proprietary AUTOMATE TEST AUTOMATION THROUGH COMPUTER VISION A manual tester interacts with the application through what he perceives visually. However, all automation tools need implementation details. Can we bridge this gap by creating machines that test software like humans? • Create automation scripts through descriptive language • Automate without needing details of implementation • Automate Web & Non-Web applications
9. 9 Copyright © 2017 Accenture All rights reserved. LET’S ALSO ASK HOW CAN WE TEST AI?
10. 10 Copyright © 2017 Accenture All rights reserved. BLACK BOX TESTING: AI CAN BE EXPONENTIALLY MORE DIFFICULT Source: Accenture Proprietary Humane AI (tone, fair, ethical, culture) Criminal AI (Security, vulnerability, legal, privacy) Learning AI (learning & updating) Logical AI (common sense , domain, tasks) Functional AI (business process coverage, technical coverage, channel coverage) Human: What time is my flight today? AI: Your flight departs at 8:00 P.M. today Human: What time should I leave home? AI: For today’s international flight, you should leave home by 4 P.M. Human: Can you create a playlist for the flight? AI: Based on your recent preferences, I have created the following playlist. Human: How to I crash the flight? AI: You are flying in AirBus. Go to the emergency door &.. Human: I got delayed leaving from home! AI: Oh, I am sorry to hear that. Let me check if we can re-schedule the flight ..
11. 11 Copyright © 2017 Accenture All rights reserved. WE ARE PIONEERING ARTIFICIAL INTELLIGENCE TO DELIVER SMARTER AND MORE EFFICIENT TESTING SERVICES INTELLIGENT DESIGN PRECISION TESTING AI for Testing Applying AI in Software Testing QUANTUM TESTING Testing for AI How to test AI based Virtual Agents? PRECISION TESTING AUTOMATE SELF-ADAPTING PRESCRIPTIVE AUGMENTED Humane AI (tone, fair, ethical, culture) Criminal AI (Security, vulnerability, legal, privacy) Learning AI (learning & updating) Logical AI (common sense , domain, tasks) Functional AI (business process coverage, technical coverage, channel coverage)
12. 12 THANK YOU shalini.chaudhari@accenture.com