Schedule

We'll talk about the schedule, sessions and share information.

How do you measure the real impact of GenAI in testing at the scale of 1,000+ QA engineers and separate actual value from the “wow” effect? We’ll share the metric framework and results from real implementations: LLMs for generating test documentation, accelerating E2E automation, and AI agents running regression tests.

Using practical examples, we will show which solutions really help speed up runs and why generative AI tips should be tested with engineering experience.

We will tell you what problems appeared, how we learned to reproduce the defect, how we stepped on a rake, and how it all ended (or did not end).

LLM-as-a-Judge in AI agent testing automation — let's discuss why this practice is vital, which models to choose, why LLM-as-a-Judge will deceive you with its simplicity, and how to start writing regression automation for your AI agents.

Let's systematize the approach to testing in game development. I'll show you how test design techniques are used in gamedev and share patterns of approaches to key game mechanics.

Testing the Smile Payment service.

Security check and search for biometric system vulnerabilities.

The market is changing, companies are reviewing their teams, and the requirements for specialists are becoming different. At the QA cozy talk, we will honestly discuss why employees are actually being fired, what signals may appear in advance, and which specialists will be in demand in the coming years. This is an open conversation where you can not only listen, but also ask questions, argue and share your experiences.

Poorly secured test repositories are not just a future threat that will materialize sooner or later. This is a current, actively exploited security breach. And as the protection of the production code strengthens, this gap will only widen, making attacks on tests more attractive to intruders. The question is not whether there will be an attack, but when it will affect your company.

I will tell you about the current state of mutation testing tools for programming languages. What new scientific papers have been published? Which tools are relevant where? My task is to provide an overview of the topic without going into details of specific tools or languages.

We will discuss how to implement AI in a company if you do not have large resources and free ML teams. I'll show you the free Roo Code AI assistant, as well as an unusual approach to writing feature evaluation agents, commit analysis, and requirements testing.

Let's talk about how to implement the contractual approach gradually and without unnecessary complication.

Let's recall the times when the grass was greener and JUnit was a very simple library.

The practice of building an agent-based system for mobile regression: interaction with the device, model selection, and a set of engineering techniques that reduce non-determinism and help validate the result without self-deception.

How Ozon Bank launched its ATM network, the testing challenges that emerged, and how the team approached UI regression automation for ATMs.

Let's build a simple RAG bot based on Heisenbug conference program.

The classic "how to reproduce this?" dilemma has been resolved! This talk introduces my browser extension that handles action recording, captures errors, and helps to produce bug reports automatically — no more manual note-taking or relying on memory.

This talk focuses on the practice of testing applications based on large language models (LLM) using the DeepEval tool. It will cover the automation of quality assessment using the LLM-as-a-Judge approach, specialized metrics, and the integration of testing into the development process to ensure the reliability and predictability of system operation.

Let's talk about testing the security of IoT devices and embedded firmware, based on the OWASP Firmware Security Testing Methodology, and create a checklist with device security checks.

A talk on how we test copilots and agents.

What do hiring managers at big tech companies really think about controversial situations in technical interviews? Where is the line of “acceptable help,” and what should you do if it feels like something is going wrong?

In this interactive format, experts will break down real cases without pre-prepared answers, and the audience will decide whose position is more convincing.

I will tell you how to build a simple and convenient tool for measuring the energy consumption of various electrical appliances and integrate it into your infrastructure.

Errors occur at all stages of software development. The sooner we find out, the cheaper it is to fix them. At WS, testers will learn how to identify errors in requirements before the development stage. This will reduce the number of potential errors, the time and effort of the team to fix them.

An AI is losing context during codebase growth. I will demonstrate a few ways to manage it and make your work more comfortable.

We will tell you how T-Bank developed a tool for chaos testing and integrated it into the daily work of teams and SDLC processes.

You will learn how to organize a compact, convenient and scalable laboratory for test benches using telecommunication racks as a platform.

Summing up the results of the conference, remembering the highlights and talking about plans.