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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## neo #318 +/- ##
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- Coverage 70.19% 67.19% -3.01%
- Complexity 2493 2496 +3
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Files 275 288 +13
Lines 15462 16518 +1056
Branches 2307 2424 +117
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+ Hits 10854 11099 +245
- Misses 3689 4438 +749
- Partials 919 981 +62 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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CaelmBleidd
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.github/workflows/build-and-test.yml
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| RETRY_DELAY=3 # Delay between retries in seconds | ||
| BRANCH="neo/2025-04-14" | ||
| #BRANCH="neo/2025-04-14" | ||
| BRANCH="lipen/grpc" |
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This PR introduces a Protobuf-based EtsIR loader that communicates with the local ArkAnalyzer gRPC server, replacing the previous JSON-based approach.
Currently, this PR contains two different implementations of Protobuf models of EtsIR: auto-generated (via Gradle plugin that wraps
protoc) and manual-written (withkotlinx-serialization-protobuf).protoc) from.protomodels.In addition, this PR contains the implementation of an HTTP client (using Ktor) for sending requests to a HTTP ArkAnalyzer server, internally using either JSON or ProtoBuf format. This shows the benefits of having the proto-model written with kotlinx-serialization, and not standalone auto-generated files. However, currently there is no simple way of easily switching between HTTP and gRPC protocols, so by using Ktor as a client, we are limited to HTTP-based solutions --- most importantly, from the ArkAnalyzer side as well, where we already began integrating gRPC server (after discussing that gRPC is indeed more suitable and future-proof for our means). Thus, we probably end up deleting all Ktor-related code from this PR, and the kx-serialization model as well, since it can't be (easily) used in auto-generated gRPC client/server stubs instead of the auto-generated messages.
Overall, we have two possible final solutions:
protoc) Java classes for model, Kotlin type-safe wrappers, auto-generated gRPC client/server stubs. Works with Java 8.Note: the description above mentions both client and server, though in this particular PR we only have to introduce a client for the ArkAnalyzer gRPC server. However, the same arguments will be applicable when we are going to develop the USVM server for the type inference. This PR is just a playground for all these possibilities.