An empirical study of 1,004 bugs in template engine-based applications finds abnormal rendering results as the most common symptom (48.61%) and documents 17 root causes with fix patterns that often involve host-side logic changes.
Investigating the bugs in reinforcement learning programs: Insights from stack overflow and github.Automated Software Engineering, 33(1):9
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.SE 2years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
RL Developer Memory is a feedback-normalized, safety-gated memory architecture for RL coding agents that logs contextual decisions and applies conservative off-policy gates to maintain 80% decision accuracy and full hard-negative suppression on a 200-case benchmark.
citing papers explorer
-
Understanding Bugs in Template Engine-Based Applications: Symptoms, Root Causes, and Fix Patterns
An empirical study of 1,004 bugs in template engine-based applications finds abnormal rendering results as the most common symptom (48.61%) and documents 17 root causes with fix patterns that often involve host-side logic changes.
-
Feedback-Normalized Developer Memory for Reinforcement-Learning Coding Agents: A Safety-Gated MCP Architecture
RL Developer Memory is a feedback-normalized, safety-gated memory architecture for RL coding agents that logs contextual decisions and applies conservative off-policy gates to maintain 80% decision accuracy and full hard-negative suppression on a 200-case benchmark.