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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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Integrating artificial intelligence into software testing and requirement engineering

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