04eed1b57e
record_labels returns all the possible labels for a record identified by
a pubkey, used in updating timestamp of crds values:
https://github.com/solana-labs/solana/blob/1792100e2/core/src/crds_value.rs#L560-L577
https://github.com/solana-labs/solana/blob/1792100e2/core/src/crds.rs#L240-L251
The code relies on CrdsValueLabel to be limited to a small deterministic
set of possible values for a fixed pubkey. As we expand crds values to
include duplicate shreds, this limits what the duplicate proofs can be
keyed by in the table.
In addition the computation of these labels is inefficient and will
become more so as duplicate shreds and more types of crds values are
added. An alternative is to maintain an index of all crds values
associated with a pubkey.
(cherry picked from commit c2b7115031)
Co-authored-by: behzad nouri <behzadnouri@gmail.com>
Building
1. Install rustc, cargo and rustfmt.
$ curl https://sh.rustup.rs -sSf | sh
$ source $HOME/.cargo/env
$ rustup component add rustfmt
Please sure you are always using the latest stable rust version by running:
$ rustup update
On Linux systems you may need to install libssl-dev, pkg-config, zlib1g-dev, etc. On Ubuntu:
$ sudo apt-get update
$ sudo apt-get install libssl-dev libudev-dev pkg-config zlib1g-dev llvm clang
2. Download the source code.
$ git clone https://github.com/solana-labs/solana.git
$ cd solana
3. Build.
$ cargo build
4. Run a minimal local cluster.
$ ./run.sh
Testing
Run the test suite:
$ cargo test
Starting a local testnet
Start your own testnet locally, instructions are in the online docs.
Accessing the remote development cluster
devnet- stable public cluster for development accessible via devnet.solana.com. Runs 24/7. Learn more about the public clusters
Benchmarking
First install the nightly build of rustc. cargo bench requires use of the
unstable features only available in the nightly build.
$ rustup install nightly
Run the benchmarks:
$ cargo +nightly bench
Release Process
The release process for this project is described here.
Code coverage
To generate code coverage statistics:
$ scripts/coverage.sh
$ open target/cov/lcov-local/index.html
Why coverage? While most see coverage as a code quality metric, we see it primarily as a developer productivity metric. When a developer makes a change to the codebase, presumably it's a solution to some problem. Our unit-test suite is how we encode the set of problems the codebase solves. Running the test suite should indicate that your change didn't infringe on anyone else's solutions. Adding a test protects your solution from future changes. Say you don't understand why a line of code exists, try deleting it and running the unit-tests. The nearest test failure should tell you what problem was solved by that code. If no test fails, go ahead and submit a Pull Request that asks, "what problem is solved by this code?" On the other hand, if a test does fail and you can think of a better way to solve the same problem, a Pull Request with your solution would most certainly be welcome! Likewise, if rewriting a test can better communicate what code it's protecting, please send us that patch!
Disclaimer
All claims, content, designs, algorithms, estimates, roadmaps, specifications, and performance measurements described in this project are done with the author's best effort. It is up to the reader to check and validate their accuracy and truthfulness. Furthermore nothing in this project constitutes a solicitation for investment.