Refactor CI test sharding: Dynamic bin-packing to replace hardcoded suites #40

Problem

The current test sharding strategy across CI workflows (build_pull_request.yml, build_container.yml) and the local test runner (run_tests_parallel.sh) is based on hardcoded, statically balanced package lists with a fallback catch-all.

While sharding is necessary (to parallelize the heavy 40+ minute single-job integration test load across 9 VMs), the current implementation has several severe drawbacks:

1. Static drift and Coverage Black Holes: Statically defined packages easily drift. We recently discovered and fixed a coverage black hole where newly added suites fell through the cracks of the hand-crafted inclusions and the catch-all.
2. Three Sources of Truth: The shard lists are duplicated across three different files (build_pull_request.yml, build_container.yml, and run_tests_parallel.sh).
3. Fragile Catch-all: The catch-all mechanism has package-level vs class-level semantic traps.
4. Manual Rebalancing: As tests grow, shards become unbalanced (e.g., historical splits between v6 and v2_x), requiring manual intervention.

Proposed Solution

Instead of maintaining three hardcoded lists, we should introduce a single dynamic script (.github/scripts/compute_shards.py) to handle the shard distribution automatically using timing-based bin-packing.

The script will:

1. Enumerate all suite classes dynamically to guarantee mathematically complete coverage (eliminating the need for a catch-all).
2. Read previous timing data (which is already generated per-class by the report jobs) from a cache or artifact.
3. Bin-pack the suites into N evenly distributed shards using a greedy algorithm.
4. Output a matrix JSON string.

Both GitHub Action workflows can use jobs.<id>.outputs + fromJSON() to dynamically generate their matrix, and the local run_tests_parallel.sh can call the same script to distribute local shards.

This unifies the shard generation into a single source of truth, guarantees 100% test coverage by construction, and ensures optimal CI time without manual rebalancing.