specific method · filed under data curation

Containerized coding-environment construction with self-testing and trace removal

A separate agent prepares and tests a coding environment in an isolated container, removes solution-leaking traces, and packages the result as an image layer.

source: 1
model: 1
lab adopt it: 1
strongest: used

How sources treat it

One count per evidence span, weakest treatment to strongest.

used 2

Documented in

DeepSeek-V4.1-Flash

Evidence

2 spans quoted from the sources, strongest treatment first.

Next, a separate agent sets up dependencies, the initial working directory, test code, and task descriptions in an isolated container, performs self-testing, removes any traces that could leak the task solution, and packages the environment as a new image layer.

usedunclearin DeepSeek-V4.1-FlashDeepSeek

DeepSeek V41 Tech Report·DeepSeek

a separate agent sets up dependencies, the initial working directory, test code, and task descriptions in an isolated container, performs self-testing, removes any traces that could leak the task solution, and packages the environment as a new image layer

useddata curationin DeepSeek-V4.1 RL training dataDeepSeek

DeepSeek V41 Tech Report·DeepSeek

Filed alongside

Other methods under data curation :: synthetic data.

Agentic data synthesis pipeline Knowledge distillation for synthetic data Automated data synthesis and environment-construction pipelines Automatic synthesis of task-oriented RL environments Counterfactual data augmentation Recycling filtered documents into image-text pairs Automated batch synthesis of RL training data Coding environments from GitHub issue–PR pairs Container buildability and verifiability check Corpus rephrasing with fidelity verification Dynamic multi-agent synthetic-data generation loop End-to-end synthetic environment generation Environment, toolset, task, and solution synthesis pipeline Failure-case and negative-feedback-driven environment generation Heterogeneous answer-generation agents Iterative task-difficulty escalation Knowledge-graph-guided task synthesis Large-scale environment synthesis and curation Long-context data synthesis by permutation and concatenation Matching synthesis-pipeline complexity to teacher capability Metadata-conditioned synthetic generation Mocked tools for agent environments Modular synthetic-data pipeline composition Multi-agent collaborative environment construction