Pith Number

pith:52IGHM4V

pith:2026:52IGHM4VOCP357G3DHHHJNTUD5

not attested not anchored not stored refs resolved

CA2: Code-Aware Agent for Automated Game Testing

David Meger, Joshua Romoff, Valliappan Chidambaram Adaikkappan, Vincent Martineau

Reinforcement learning agents that observe call stack traces test games more effectively than agents limited to game state alone.

arxiv:2605.13918 v1 · 2026-05-13 · cs.SE · cs.LG

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\pithnumber{52IGHM4VOCP357G3DHHHJNTUD5}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Our results show that incorporating code signals like the call stack enables more effective and targeted game testing.

C2weakest assumption

That the call stack can be extracted efficiently and that its addition to the observation space produces a genuine policy improvement rather than an artifact of the specific environments or reward design.

C3one line summary

CA2 integrates call stack information into RL agents for game testing and shows consistent gains over baselines that ignore code signals.

References

33 extracted · 33 resolved · 9 Pith anchors

[1] C. Politowski, F. Petrillo, and Y.-G. Guéhéneuc.A Survey of Video Game Testing. 2021. arXiv:2103.06431 [cs.SE].url:https://arxiv.org/abs/2103.06431 2021

[2] Technical Challenges of Deploying Reinforcement Learning Agents for Game Testing in AAA Games 2023 · doi:10.1109/cog57401.2023.10333194

[3] Playing Atari with Deep Reinforcement Learning 2013 · arXiv:1312.5602

[4] Mastering Diverse Domains through World Models 2024 · arXiv:2301.04104

[5] C. Gordillo, J. Bergdahl, K. Tollmar, and L. Gisslén.Improving Playtesting Coverage via Curiosity Driven Reinforcement Learning Agents. 2021. arXiv:2103 . 13798 [cs.LG].url: https://arxiv.org/abs/2103 2021

Receipt and verification

First computed	2026-05-17T23:39:18.726467Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ee9063b395709fbefcdb19ce74b6741f5efa8d1e0a944eff7bed2d991b74ae38

Aliases

arxiv: 2605.13918 · arxiv_version: 2605.13918v1 · doi: 10.48550/arxiv.2605.13918 · pith_short_12: 52IGHM4VOCP3 · pith_short_16: 52IGHM4VOCP357G3 · pith_short_8: 52IGHM4V

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/52IGHM4VOCP357G3DHHHJNTUD5 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ee9063b395709fbefcdb19ce74b6741f5efa8d1e0a944eff7bed2d991b74ae38

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "da6e7a52ec028f434af6eacf5bc284c1aeca146c4ef803fe4943992bcb0e6bbf",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.SE",
    "submitted_at": "2026-05-13T12:52:35Z",
    "title_canon_sha256": "c82ab882d0584c2c20c679ca7d122672c6f39060a2fb4e46a4b0b079142ba6c0"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13918",
    "kind": "arxiv",
    "version": 1
  }
}