pith. sign in
Pith Number

pith:4A66SVTM

pith:2026:4A66SVTMKB6EBAUHC5WUVORVQ7
not attested not anchored not stored refs resolved

Assistance to Autonomy: A Systematic Literature Review of Agentic AI across the Software Development Life Cycle

Helena Holmstr\"om Olsson, Jan Bosch, Spyridon Alvanakis Apostolou

Output verifiability enables agentic AI adoption mainly in later software development phases.

arxiv:2605.15245 v1 · 2026-05-14 · cs.SE

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{4A66SVTMKB6EBAUHC5WUVORVQ7}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp
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

output verifiability is the primary enabler of agentic adoption: later SDLC phases, whose outputs are objectively evaluable through executable feedback, demonstrate the highest maturity and industrial presence, while earlier phases remain almost exclusively academic proofs-of-concept.

C2weakest assumption

The 92 manually verified primary studies, after multi-agent screening of over 1600 candidates, form a representative and unbiased sample whose thematic synthesis accurately reflects dominant patterns and industrial practices without significant omission of key work.

C3one line summary

Systematic review of agentic AI in the SDLC finds output verifiability drives industrial adoption in later phases, with Planner-Executor-Reviewer as the dominant pattern, plus a new multi-agent LLM screening pipeline for high-volume SLRs.

References

33 extracted · 33 resolved · 2 Pith anchors

[1] IEEE Access13, 18912–18936 (2025), https://ieeexplore.ieee.org/abstract/document/10849561 2025
[2] In: 2025 IEEE International Conference for Women in Innovation, Technology & Entrepreneurship (ICWITE) 2025
[3] Akbar, M.A., Khan, A.A., Hamza, M., et al.: Agentic AI in Software Engineering: Practitioner Perspectives Across the Software Development Life Cycle (Sep 2025), https://papers.ssrn.com/abstract=552015 2025
[4] Future Internet17(9) (Sep 2025),https://www.mdpi.com/1999-5903/ 17/9/404 2025
[5] Measuring the impact of early-2025 AI on experienced open-source developer productivity.CoRR, abs/2507.09089 2025
Receipt and verification
First computed 2026-05-20T00:00:48.191146Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

e03de9566c507c408287176d4aba3587e81f53a0350e1152fac2a68dad25ea55

Aliases

arxiv: 2605.15245 · arxiv_version: 2605.15245v1 · doi: 10.48550/arxiv.2605.15245 · pith_short_12: 4A66SVTMKB6E · pith_short_16: 4A66SVTMKB6EBAUH · pith_short_8: 4A66SVTM
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/4A66SVTMKB6EBAUHC5WUVORVQ7 \
  | 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: e03de9566c507c408287176d4aba3587e81f53a0350e1152fac2a68dad25ea55
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "c822a3c777ef25c5b783d3bd72caa2f4622c258121f4405ad81a57d5f06874aa",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.SE",
    "submitted_at": "2026-05-14T10:46:51Z",
    "title_canon_sha256": "0d8a86953e9acbb52a7a4bbd1d59b34156da75890d3b03f60803ba1401b8ba13"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.15245",
    "kind": "arxiv",
    "version": 1
  }
}