World Congress 2023 Sep 27, 2023

Are you still programming unit tests or already generating?

Johannes Bergsmann , Daniel Bauer

Are your AI-generated unit tests just reinforcing your own syntax mistakes? Discover how to automatically generate intelligent, risk-based unit tests directly from system requirements instead.

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#1 about 2 min

Bridging developers, testers, and requirements engineers in testing

Transforming source code testing into a visualized platform enhances collaboration between technical and business teams.

#2 about 2 min

Incorporating black box methods into unit testing

Extending black box interface methodologies to unit tests addresses critical requirement logic gaps missed by source code analysis.

#3 about 4 min

Applying equivalence class and boundary value analysis

Reducing redundant test cases requires identifying requirement-based value ranges and explicitly testing inner and upper boundaries.

#4 about 3 min

Advancing through unit testing maturity levels

Shifting from arbitrary code coverage targets to risk-based testing strategies establishes more meaningful software quality metrics.

#5 about 3 min

Writing effective tests over chasing maximum coverage

Achieving complete code coverage without applying functional validation rules fails to guarantee robust software implementation.

#6 about 3 min

Generating test code through an intermediate model

Parsing interface signatures into a version-controlled intermediate dataset enables structured generation of standard unit testing code.

#7 about 6 min

Defining semantic test cases with pairwise combinations

Injecting requirement-based input boundaries into test automation systematically derives critical edge cases without manual enumeration.

#8 about 2 min

Visualizing testing workflows with standalone modeling tools

Transitioning test management to a standalone graphical canvas enables visual collaboration on complex scenarios and decision flows.

#9 about 4 min

Automating deterministic test components without generic AI

Prompting generative models for unit tests often reflects existing code biases rather than explicitly validating true software requirements.

#10 about 5 min

Handling local analysis, codebase updates, and environment compatibility

Running deterministic generators securely on local developer machines allows rapid test recalibration when refactoring source parameters.

Matching moments

7:57 min

Demonstrating automated unit test generation for legacy java

Neel Sundaresan Neel Sundaresan +1 · World Congress 2026 Europe

2:39 min

Evaluating automated approaches for generating unit test cases

Evelyn Haslinger · LIVE

3:32 min

Iterating automated unit test generation with coverage metrics

Eric Jadi Eric Jadi +1 · World Congress 2025

1:51 min

Bridging the gap between AI code generation and verification

Christian Heilmann Christian Heilmann +3 · World Congress 2026 Europe

59 sec

Automating epic generation and semantic analysis for test management

Rene Schenk Rene Schenk · World Congress 2026 Europe

2:27 min

Using automated tests to validate AI generated codebases

YK Sugi YK Sugi · World Congress 2025

Upcoming sessions on this topic

Open session

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September 25, 2026 · 11:40–12:10

Stage 2

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September 25, 2026 · 13:30–14:00

Stage 7

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Open session

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September 24, 2026 · 13:30–14:00

Stage 1

How AI Agents Tripled Our Test Coverage on a 1.8M-Line iOS Codebase

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Open session

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September 24, 2026 · 14:50–15:20

Stage 3

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Open session

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Outdoor Stage

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