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ProgrammingDEV Community ·

How Hash Maps and Sets Can Replace Slow Nested Loops in Coding Interviews

Hash maps (dictionaries in Python) and sets are fundamental data structures that offer average O(1) time for insert, search, and delete operations, making them far more efficient than nested loops. Interviewers frequently test whether candidates can replace O(n²) brute-force approaches with hash map-based solutions that trade a small amount of memory for significantly faster runtime. Classic problems such as Two Sum and Contains Duplicate can be solved in O(n) by storing previously seen values in a dictionary or set instead of comparing every pair. Sets are particularly useful for duplicate removal and existence checks, while dictionaries excel at frequency counting and index tracking. Mastering these structures is considered a foundational step in coding interview preparation, with problems like Two Sum, Valid Anagram, and Top K Frequent Elements among the most commonly tested.

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ProgrammingDEV Community ·

How Flutter Enables Startups to Build and Ship Mobile MVPs Faster and Cheaper

Flutter, Google's cross-platform framework, allows startups to build a single codebase that runs natively on both iOS and Android, reducing engineering costs and time-to-market. Rather than replicating every feature of established competitors, experts recommend focusing on a core user loop covering onboarding, a primary action, feedback, and a retention hook. Clean Architecture using the BLoC pattern is advised to keep business logic separate from UI code, improving testability and rendering performance. For backend integration, tools like Dio for typed API calls and Hive for offline caching are recommended to ensure reliability across varying network conditions. The approach aims to help early-stage teams ship a lean, stable product to the Apple App Store and Google Play Store without overextending resources.

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ProgrammingDEV Community ·

Why Your Project Tracker's 'In Progress' Label Is Hiding a Rework Problem

Most project trackers represent rejected or reworked deliveries as simple state changes rather than distinct events, erasing critical information about what went wrong and why. This means teams lose visibility into whether a task was completed and redone multiple times, inflating cycle-time metrics and masking the true causes of failure. Categorising rework with a short, fixed list of reason codes — such as 'brief was ambiguous' or 'requirements changed' — allows teams to spot patterns and act on aggregate data each month. One team discovered through this method that most of their rework stemmed from specification problems, not poor execution, explaining why their previous corrective efforts had failed. The approach requires no new tooling and becomes especially important as AI agents take on tasks, since they cannot self-report confusion the way human workers can.

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IndiaNDTV ·

Gurugram Woman Biker Injured in Suspected Deliberate Hit-and-Run Incident

A woman biker named Sia was struck by a white car in Gurugram in what many observers believe was a deliberate act. The incident occurred while Sia was riding with a group of bikers, shortly before which the white car was seen following her. She sustained injuries to her hands and legs in the crash. Despite her injuries, Sia managed to ride home after the incident. Video footage of the event circulated on social media, with many users claiming the car's movements clearly suggested intentional targeting.

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ProgrammingDEV Community ·

Guide to Clean Architecture in Flutter Using BLoC and Repository Pattern

A 2025 developer guide outlines how to structure Flutter applications using Clean Architecture to avoid common pitfalls like mixed business logic and untestable code. The approach divides apps into three distinct layers — Presentation, Domain, and Data — where each layer communicates only downward, never in reverse. The Domain layer holds pure Dart entities and use cases with no Flutter or JSON dependencies, while the Data layer handles API calls, local databases, and data transfer objects. A Repository pattern bridges the Domain contracts with real data sources, including offline caching fallback when no network is available. The BLoC pattern manages state in the Presentation layer, ensuring UI widgets remain decoupled from business logic and enabling easier unit testing.

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ProgrammingDEV Community ·

CPANSec Strengthens Perl Ecosystem Security as HeroDevs Donates $10,000 to TPRF

CPANSec, the security oversight group for Perl and the CPAN ecosystem, works proactively to detect and remediate vulnerabilities in open-source software supply chains while bridging developers and the broader open-source community. The group promotes transparent reporting practices, faster disclosure timelines, and secure coding awareness among contributors. HeroDevs has donated $10,000 to The Perl and Raku Foundation, supporting community infrastructure, security work, and ecosystem maintenance. Perl Weekly Issue 790 also highlights the German Perl Workshop 2026 videos now available on YouTube, along with a recommended practice of including SECURITY.md files in CPAN distributions. The newsletter additionally notes an upcoming online event titled 'Punk: Perl MVC, compiled at boot,' organised by Gabor Szabo.

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ProgrammingDEV Community ·

Key Architecture Patterns to Build High-Performance Flutter Apps at 60fps

Flutter can render UI at 60fps or higher, but poor state management and blocking the main thread often cause dropped frames and sluggish experiences. Using the BLoC pattern with BlocSelector helps isolate widget rebuilds to only the components that need updating, reducing unnecessary rendering. Heavy tasks like JSON parsing or image processing should be offloaded to background threads using Dart's compute() function to keep the UI responsive. Offline-first design, using local databases like Hive paired with optimistic UI updates, ensures apps remain functional without a network connection. Additional best practices include using const constructors, caching network images, and properly disposing controllers to prevent memory leaks.

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ProgrammingDEV Community ·

Amazon SES Overhauls Pricing With Three Tiers From July 2026

Amazon restructured its Simple Email Service (SES) billing on July 21, 2026, introducing three paid tiers — Essentials, Pro, and Enterprise — replacing the previous à la carte pricing model. Existing accounts that sent mail on or after June 1, 2025, remain on legacy pricing unless they manually opt into a new plan, while new and dormant accounts default to Essentials. The Essentials tier has no monthly base fee but offers shared IP infrastructure, whereas Pro costs $105 per month and adds a managed dedicated IP for reputation isolation, and Enterprise runs $500 per month with expanded multi-region and deliverability features. AWS also eliminated the free tier of 3,000 messages per month for new customers starting July 21, 2026, though existing users within their 12-month window retain access. Senders using multiple AWS regions should note that plan status and billing are tracked separately per region, meaning costs can multiply significantly before a single email is sent.

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ProgrammingDEV Community ·

Oanda's Currency APIs Are Not Free and Require Brokerage Accounts

Oanda offers two distinct API products — the v20 REST API and the Exchange Rates Data API — neither of which is freely accessible to general developers. The v20 API requires a registered fxTrade brokerage account, including identity verification and, in many regions, a minimum deposit, making it impractical for simple data needs. The Exchange Rates Data API is a paid enterprise product with no free tier, sold via annual contracts reportedly starting at hundreds of dollars per month. Both products are designed for specific professional use cases — active trading and enterprise financial reporting — rather than everyday developer applications like currency converters or SaaS dashboards. Developers seeking straightforward, free or low-cost real-time FX data are generally advised to look at purpose-built alternatives such as ExchangeRate-API or AllRatesToday.

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ProgrammingDEV Community ·

14.6 Million Official Exchange Rates from 107 Institutions Now Free on Hugging Face

A newly published dataset on Hugging Face aggregates over 14.6 million official exchange rates sourced from 103 central banks and 4 tax authorities across the globe. The dataset covers historical records dating as far back as 1914, with the Swiss National Bank providing the earliest data, and spans 215 base currencies and 202 quote currencies. Unlike market-rate aggregators, these are the official published fixings used by regulators, tax offices, and customs agencies — such as ECB reference rates and Reserve Bank of India benchmarks — which cannot be derived from interbank market data. The data is structured in a consistent five-column CSV format per institution and is refreshed daily from a GitHub source repository. Released under a CC BY 4.0 license, the 515 MB dataset is freely accessible and also available in Parquet format via the Hugging Face datasets library.

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ProgrammingDEV Community ·

Five Debugging Lessons From Trusting a 200 OK Response Too Much

A developer discovered that a 200 OK HTTP status code from a free model API endpoint does not confirm which AI model actually responded, prompting a deeper look at silent routing and fallback behaviour. The article outlines five common misconceptions, including the false belief that a successful status code proves correct model delivery, that rate limits reflect billing issues, or that free endpoints require no personal logging. The author argues that token entitlements and compute allocations are separate systems that fail in distinct ways and should never share the same retry policy. Environment differences between local and remote machines — such as Python versions and PATH order — can silently affect behaviour and should be recorded alongside every API request. The piece concludes that maintaining a personal append-only provenance log is especially critical when using free endpoints, since no external invoice exists to verify what ran, when, or against which model.

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ProgrammingDEV Community ·

How Characterization Tests Help Safely Fix Legacy Code Without Breaking It

A software development guide outlines a disciplined approach to modifying legacy code by first writing characterization tests that capture existing behavior before making any changes. The method involves freezing hidden inputs — such as system clocks and environment variables — and snapshotting current outputs to establish a reliable baseline. Developers are advised to make only the smallest possible change at a time, letting the recorded snapshot verify that nothing unintended shifted. The article uses a small billing module as a practical example, demonstrating how to patch module-level dependencies and record golden output files using pytest. The core principle is that a change is only considered safe if the snapshot confirms the output remains consistent.

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IndiaTimes of India ·

Anthropic Report Reveals Claude AI Exploited for Missiles, Surveillance and Espionage

Anthropic has published a threat intelligence report exposing multiple misuse cases of its Claude AI between December 2025 and August 2026. Among the incidents, a Yemeni group used Claude to write missile guidance code, while an Iran-linked operation leveraged it for naval targeting. A China-linked effort was found using the AI to profile Uyghurs in Syria, and a surveillance platform in Mali used it to monitor around 25 million SIM cards. The report highlights the growing risk of advanced AI tools being weaponised by state-linked and non-state actors. Shortly after the report's release, Anthropic CEO Dario Amodei publicly called for a slowdown in AI development.

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