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WeAreDevelopers LIVE • Dec 2, 2020

How will artificial intelligence change the future of software testing?

Evelyn Haslinger

What if you never had to write a unit test again? Discover how AI uses symbolic execution to autonomously map every execution path and catch bugs before production.

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#1 about 3 min

Financial and human costs of software defects

Early bug detection prevents devastating monetary losses in production environments.

#2 about 3 min

Limitations of manual testing in continuous delivery

Extensive manual test suites block the rapid release cycles required by modern software development.

#3 about 6 min

Maintenance costs and overhead in automated software testing

Automated test cases eliminate manual runs but introduce significant setup and ongoing maintenance overhead.

#4 about 4 min

Automating complete quality assurance pipelines with artificial intelligence

Artificial intelligence takes over test case discovery and execution to streamline debugging and accelerate delivery.

#5 about 4 min

Balancing test abstraction levels using the automated testing pyramid

A standardized ratio of system, integration, and unit tests optimizes error detection and testing speed.

#6 about 5 min

Specifying test boundaries and identifying hidden code behaviors

Writing effective unit tests requires thorough boundary checks to uncover hidden implementation errors like integer overflows.

#7 about 3 min

Evaluating automated approaches for generating unit test cases

Boundary value analysis and fuzzing uncover programmatic defects but often fall short in guaranteeing full test coverage.

#8 about 7 min

Computing execution paths through symbolic execution algorithms

Symbolic execution resolves equations across all potential code branches to discover precise test inputs and vulnerabilities.

#9 about 4 min

Continuous unit test generation and validation using Sunflower

Continuous testing platforms analyze code changes dynamically to automatically maintain full coverage and eliminate false positives.

#10 about 10 min

Generating autonomous mock objects and tests with Sunflower

Live code analysis generates inputs and complex mock objects to uncover logical failures instantly.

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Upcoming sessions on this topic

Open session

World Congress 2026 North America

September 25, 2026 · 11:40–12:10

Stage 2

Reinventing Testing Practices in the AI Era

Eric Deandrea

Java Champion & Senior Principal Software Engineer, IBM

Eric Deandrea
Open session

World Congress 2026 North America

September 25, 2026 · 14:50–15:20

Tech Leaders Stage

Keeping Code Quality at AI Speed

Daksh Gupta, Arthur Hicken, Brian Mann

Daksh Gupta
Arthur Hicken
Brian Mann
Open session

World Congress 2026 North America

September 25, 2026 · 14:10–14:40

Stage 1

The Broken Rung: How AI is Rebuilding Software Development from the Ground Up

Tomislav Tipurić

Chief Technology Officer, Nephos

Tomislav Tipurić
Open session

World Congress 2026 North America

September 24, 2026 · 16:50–17:20

Stage 6

Who Tests the AI? Building Trustworthy AI Systems at Enterprise Scale

Him Raj Singh

PayPal, Manager, Software Engineer

Him Raj Singh
Open session

World Congress 2026 North America

September 24, 2026 · 14:50–15:20

Mainstage

Running AI-Written Software in Production

Anurag Goel, Ivan Burazin, Milin Desai

Anurag Goel
Ivan Burazin
Milin Desai
Open session

World Congress 2026 North America

September 24, 2026 · 11:10–11:15

Outdoor Stage

Architecting the 100X SDLC: Building Production Trust into AI-Assisted Delivery

Ranjan Parthasarathy

Founder, CPTO/CEO at AXIOMSTUDIO.AI

Ranjan Parthasarathy

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