LINE news
The latest AI and developer news from LINE, with short summaries.
Visit website →LINE App Unifies Group Chats
LINE has unified its Rooms and Groups into a single **Group Chat**.
Improving Code Quality - #69: My Code Quality Tips
Good code should be easier to read than to write, and should be designed so that it's hard to use incorrectly.
Distributed Mobile Team Collaboration: Code/Design Reviews, Architecture Discussions, and Continuous Practice
Mobile engineers from Tokyo and HCMC strengthened collaboration through joint reviews and design exercises at FIXIT.
Improving Code Quality - Session 68: Tests Can Be a Double-Edged Sword
Injecting excessive logic for the sake of testing can make tests complex and risks missing verification of actual interactions.
Improving Code Quality - Episode 67: Too many error representations are also a problem
Error representations should be unified into one rather than scattered across many, so that the call site stays simple.
Improving Code Quality - Episode 66: Firm but Still Anxious
Validation should be completed at the time of object creation or update, not at the time of use.
Building the Cloud of the Future
LY Corp is building **Flava**, a new private cloud platform that integrates the clouds of Yahoo! JAPAN and LINE.
Code Quality Improvement - Session 65: Collection Isn't Just List
Considering the characteristics of Collections and appropriately using Set and Map instead of List can improve code clarity and stability.
The Journey Toward Infinite Scale: The Evolution of LY Corporation's Observability Platform
LY Corporation is building an observability platform that improves metrics storage efficiency and integrates AI to manage large-scale infrastructure.
Code Quality Improvement - Session 64: Keeping Primary Constructors Simple
Kotlin primary constructors should be kept simple to match the class's properties, with complex logic separated into secondary constructors or factory functions.
Improving Code Quality - Session 63: The Betrayal of Values
Including collection index information in a data model causes data inconsistency during filtering, so such data should only be generated when needed, such as at the UI layer.
Code Quality Improvement - Session 62: Two Hair-Raising Cases
This proposes ensuring idempotency in functions to reduce the hassle of state checks and increase code predictability.
Safety Is a Given, Cost Savings Are a Bonus: Why AI Services Need Dedicated Guardrails
AI services need a separate, dedicated guardrail system to compensate for the limitations of the system prompt approach.
Improving Code Quality - Session 61: This Function Is Only for One Caller
This analyzes the concurrency issues that occur when function state is managed as an object's property, and presents two design approaches to resolve them.
Building a Multi-Agent Pipeline for NL-to-SQL Analysis
To overcome the limitations of the existing MCP approach, we built an A2A-based NL-to-SQL analysis pipeline in which specialized agents collaborate with one another.
Improving Code Quality - Session 60: Don't Hammer Down Every Protruding Nail
Be wary of over-applying the SLAP principle, as it can harm the readability of the main logic.
Improving Code Quality - Session 59: A Class Facade Made of Water
Rather than excessively separating a class's responsibilities, it's important to keep the interface simple from the caller's perspective.
Improving Code Quality - Session 58: The Things Words Can't Fully Express
Implicit dependency relationships within code should be isolated at the function or class level to prevent runtime errors.
Improving Code Quality - Session 57: Seeing Is Believing
During code review, you should examine the caller and callee code together to prevent duplication or omission of conditional filters.
Improving Code Quality - Session 56: 80% Expectations
When writing JSON unit tests, you should verify structure abstractly rather than comparing strings directly, in order to increase the flexibility and accuracy of the tests.