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UID:pretalx-devconf-us-2026-PVT7YE@pretalx.devconf.info
DTSTART;TZID=EST:20260924T160000
DTEND;TZID=EST:20260924T163500
DESCRIPTION:In many enterprise change management processes\, risk assessmen
 t is still performed manually\, while recurring low-risk change patterns m
 ay be pre-authorized or assigned default classifications. This paper prese
 nts an automated\, quantitative risk assessment framework for software cha
 nge requests that combines large language model (LLM) evaluations of chang
 e artifacts with rule-based operational risk scoring. With this system\, r
 isk is divided into two orthogonal dimensions: change risk\, which evaluat
 es plaintext change plans\, test plans\, rollback plans\, based on a combi
 nation of LLM inference and timing and blast radius heuristics\; and asset
  risk\, which uses operational metrics such as code coverage\, availabilit
 y\, incident history\, and open defects to assess the operational health o
 f the target software asset. These scores are adjusted by configurable mul
 tipliers for environment type\, asset business criticality\, and peak even
 t periods. Deployed within a large financial technology organization and i
 ntegrated with an ITSM platform\, a messaging platform\, and operational m
 etrics databases\, the framework has evaluated tens of thousands of change
  requests in production. This paper describes the system architecture\, th
 e scoring algorithms\, the LLM integration strategy\, and discusses design
  decisions that allow the framework to operate reliably at enterprise scal
 e while remaining interpretable and auditable.
DTSTAMP:20260727T165045Z
LOCATION:Ladd Room (Capacity 170)
SUMMARY:A Hybrid LLM and Rule-Based Risk Assessment Framework for Enterpris
 e Software Change Management - James Gilmore
URL:https://pretalx.devconf.info/devconf-us-2026/talk/PVT7YE/
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