Habr•July 31, 2026•🇷🇺Translated from Russian

Bridging Manual and Automated Testing: InfoWatch Engineer Outlines Unified Quality Process

InfoWatch senior test engineer Mikhail Shalepo has shared a comprehensive internal regulation that connects manual and automated testing into one coherent quality process. The article uses the metaphor of an “orange” to describe the overlapping area of functional verification where the two testing approaches must deliver a single, reliable signal about product state.

Shalepo notes that when automation volume, environments, and mandatory runs remain small, teams often rely on shared context. As the product grows, this implicit understanding disappears, creating the need for explicit rules on selecting automation candidates, validating new tests, defining mandatory regression sets, classifying failures, and recording manual compensation.

Core Principles of the Regulation

The document distinguishes between process rules—who decides, what result is recorded, and who owns the next step—and specific engineering decisions for individual features. It establishes that manual testers review the purpose of an automated scenario rather than its code, and that every failure must receive an owner and follow-up action before a run is considered resolved.

The regulation is split into two blocks: development and verification of new functionality, and full regression testing before release. Both blocks follow the same three-stage structure—preparation, execution, and completion—producing clear artifacts at each step.

Feature Development Block

Before a sprint, manual testers and automation engineers meet to discuss scenarios worth automating. Decisions are turned into backlog tasks instead of remaining informal promises. During the sprint, the manual testing team acts as the customer of automation meaning, while smoke tests must pass before any build reaches manual verification. At sprint end, coverage status is recorded directly in TMS Scale to keep the single source of truth up to date.

Pre-Release Regression Block

Before regression begins, teams align on the full scope of checks, supported configurations, and exit criteria. During execution, automated results are triaged jointly with developers; every failure is classified, assigned an owner, and linked to a task or defect. Manual compensation is documented only when an automated signal cannot be restored quickly. At the end of regression, the team produces a connected set of artifacts that allow full reconstruction of the release decision without relying on chat history.

Shalepo emphasizes that the regulation does not guarantee zero defects or automatically shorten regression time. Its value lies in making the basis for release decisions observable and repeatable across the team.

Related articles

Securitylab•Other

BGP Anycast and Traffic Filtering: How Distributed DDoS Protection Works

Powerful DDoS attacks can leave servers intact while blocking user access by overwhelming network links or equipment before traffic reaches applications. Scaling server resources offers little help in such cases. One effective defense distributes incoming traffic across multiple geographically dispersed scrubbing centers using BGP Anycast, which advertises the same IP addresses from different locations. Routers then direct packets to the nearest or most appropriate node based on BGP policies. This architecture allows each center to filter malicious traffic locally before forwarding clean data to the protected infrastructure. The approach proves especially useful against volumetric attacks but requires careful management of routing, load distribution, and application health checks. Providers such as Qrator Labs and Akamai Prolexic operate large anycast networks with multi-terabit capacity.

Securitylab•Other

Freedom Holding Corp Builds Integrated Financial Ecosystem Across Banking, Insurance, Telecom and AI

Freedom Holding Corp., listed on Nasdaq under FRHC, has grown from a brokerage founded by Timur Turlov into a diversified group operating in 24 countries with its core market in Kazakhstan. The company now encompasses Freedom Bank Kazakhstan, Freedom Life and Freedom Insurance, Freedom Telecom, Freedom Cloud, and the Arbuz marketplace, all unified through the Freedom SuperApp launched in April 2024. In the financial year ended 31 March 2026 the group reported revenue of $2.19 billion and net profit of $153.3 million, while banking assets reached $5.36 billion. Freedom Holding is also investing heavily in AI infrastructure, planning a 100 MW sovereign data center and a $2 billion AI hub in partnership with NVIDIA and the Kazakh government. The company has expanded into Tajikistan, Turkey and is seeking licenses in Georgia and France while maintaining strong growth in deposits and active users.

AntiMalware•Other

Russia Proposes Fines Up to 5 Million Rubles for Social Networks and Online Cinemas Failing to Restrict Content Discrediting Traditional Values

A Russian State Duma committee has recommended adopting a bill that introduces administrative fines for owners of social networks and online cinemas who fail to limit access to content deemed to discredit traditional Russian spiritual and moral values. The legislation builds on existing requirements by adding financial penalties enforced by Roskomnadzor following decisions from the Ministry of Culture. First-time violations could result in fines of up to 20,000 rubles for individual platform owners, 200,000 rubles for officials, and 1 million rubles for companies. Repeat offenses would escalate these amounts significantly, reaching up to 300,000 rubles, 800,000 rubles, and 5 million rubles respectively. A separate provision targets online cinema operators for distributing such works, with corporate fines capped at 700,000 rubles initially and 3 million rubles for subsequent violations. Platforms can avoid liability if they remove the content within 24 hours after the rental certificate is revoked. Cases would be initiated by the Ministry of Culture for distribution issues and Roskomnadzor for non-compliance, with district courts handling proceedings.

AntiMalware•Other

Yandex Plus Points Expand Beyond Ecosystem but Spending Amount Set Automatically

Yandex has enabled subscribers of Yandex Plus to spend accumulated points at more than 10,000 partner locations outside its own services. The points are now accepted by external stores, cafes, pharmacies and other merchants connected to Yandex Pay. Users must have an active Yandex Plus subscription and select Yandex Pay at checkout to trigger the option. The system automatically determines how many points can be applied to each purchase, with the remaining balance paid by card. It is not possible to choose the exact number of points manually or to both spend and earn points on the same transaction. The feature can however be combined with loyalty bonuses offered directly by the merchant. Yandex plans to continue expanding the list of participating partners, including smaller retailers.