Experience protocol buffer on android

Aug 15, 20169 likes2,185 views

The document introduces Protocol Buffers and how to use them on Android. It discusses the benefits of Protocol Buffers such as speed, size, and compatibility. It also provides a demo comparing the performance of Protocol Buffers to GSON, showing that Protocol Buffers are faster and produce smaller data sizes. The document concludes by mentioning some drawbacks of Protocol Buffers and providing references for further information.

HELLO!
I am Richard Chang
Android Engineer
Worked for HTC, Movial, VMFive and AndroVideo
You can find me via chiel99 AT gmail.com

Outline
● Introduce Protocol Buffers
● Why Protocol Buffers
● How to use Protocol Buffers
● Protocol buffer meets Android
● Demo
● Reference
https://github.com/chiel99/ExperienceProtobuf

Protocol buffers are Google's
language-neutral, platform-neutral,
extensible mechanism for serializing
structured data
From: https://developers.google.com/protocol-buffers/

Benefits
● Speed
○ Fast
● Size
○ Small
○ Serialize to binary-format stream
● Backward Compatible
● Multiple programming language support
○ C++ / Java / Python / C# / Go...etc
● Easy to define the data schema

Usages
● Install protoc (protocol buffer compiler) and related libs
○ steps
● Write a .proto file
● Use protoc to generate the Java/C++/Python... source code
○ protoc --cpp_out=./cpp --java_out=./java sample.proto
● Add related libs to your project
● Put the generated source code to your project
● writeTo() and parseFrom()
● Happy coding with Protocol Buffers!

Protocol Buffers meet Android
● AOSP/external/protobuf/
○ protoc => aprotoc
○ AOSP is not following the latest version
● Dex 65535 method count issue
● Apk size issue

Protocol Buffers for Java
Lite version Micro version Nano version
Lib size 128 KB 21 KB 43 KB
Generated Java
class size*
7~8x 1.2~1.3x 1x
Object creation Builder Constructor Constructor
Object
operations
Builder /
Setter / Getter
Setter / Getter public member
Repeated
objects
List List Array

Speed and Size comparison with GSON
● Speed
○ Serialize: ~10x faster (40 ms v.s 400 ms)
○ Deserialize: ~2x faster (15 ms v.s 30 ms)
● Serialized data size
○ ~2x smaller (24 KB v.s 45 KB)
● Lib size
○ ~10x smaller (21 KB v.s 232 KB)

Drawbacks
● Human unreadable format
● Need tool (protoc) to generate source code
● Most network services are JSON based?

Thanks!
Any questions?
You can find the sample code on github:
https://github.com/chiel99/ExperienceProtobuf

Reference
● https://developers.google.com/protocol-buffers/
● https://github.com/android/platform_external_protobuf
● AOSP: frameworks/native/opengl/libs/GLES_trace
● https://github.com/square/wire
● https://github.com/Biuni/PokemonGO-Pokedex

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Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe. We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved? Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security. Talk from SciFiDevCon 2025 https://www.scifidevcon.com/courses/2025-scifidevcon/contents/680efa43ae4f5

Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup

In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals. This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft. What You’ll Learn in Part 2: Explore real-world nonprofit use cases and success stories. Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!

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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora

Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.

Interactive odoo dashboards for sales, CRM , Inventory, Invoice, Purchase, Pr...AxisTechnolabs

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Adobe Marketo Engage Champion Deep Dive - SFDC CRM Synch V2 & Usage DashboardsBradBedford3

Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025. Key Takeaways: Improved Salesforce CRM User Experience: Learn how self-service visibility enhances satisfaction. Utilize Salesforce CRM Synch Dashboards: Explore real-time weekly activity data. Monitor Performance Against Limits: See threshold limits for each product level. Get Usage Over-Limit Alerts: Receive notifications for exceeding thresholds. Learn About Improved Salesforce CRM Scale: Understand upcoming cloud-based incremental sync.

Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev

If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic? Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search. Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval. GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.

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How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik

This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements. Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows. We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure. The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.

Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell

It's time you stopped letting your telemetry data pressure your budgets and get in the way of solving issues with agility! No more I say! Take back control of your telemetry data as we guide you through the open source project Fluent Bit. Learn how to manage your telemetry data from source to destination using the pipeline phases covering collection, parsing, aggregation, transformation, and forwarding from any source to any destination. Buckle up for a fun ride as you learn by exploring how telemetry pipelines work, how to set up your first pipeline, and exploring several common use cases that Fluent Bit helps solve. All this backed by a self-paced, hands-on workshop that attendees can pursue at home after this session (https://o11y-workshops.gitlab.io/workshop-fluentbit).

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