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README.md

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-license: cc-by-sa-4.0
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+---
+license:  cc-by-sa-4.0
+---
+
+# DeepSeek-Coder-1.3B – Clean DSC Model (DSCc)
+
+This repository hosts **DSCc**, a fine-tuned version of **DeepSeek-Coder-1.3B** trained for **Python function generation** from docstrings and function signatures, using a *cleaned* subset of The Stack.
+
+The model is part of the study:
+
+> **Quality In, Quality Out: Investigating Training Data’s Role in AI Code Generation**  
+> 33rd IEEE/ACM International Conference on Program Comprehension (ICPC 2025)
+
+DSCc is specifically trained on a **Semgrep-filtered dataset** that removes many low-quality and syntactically incorrect functions, allowing us to study how training data quality impacts code generation performance.
+
+---
+
+## Model description
+
+- **Base model:** DeepSeek-Coder-1.3B (Python-focused code LLM)
+- **Task:** Python code generation
+- **Input:** Python function **docstring + signature**
+- **Output:** The corresponding **function body** in Python
+
+In our experiments, the model is conditioned on a prompt consisting of:
+- A natural-language docstring describing the function behavior
+- The Python function signature
+
+and is then asked to generate the rest of the function body.
+
+---
+
+## What does the model do?
+
+The model generates **Python functions** that implement the behavior described in the docstring and implied by the signature. Typical use cases:
+
+- Synthesizing a function implementation from a high-level description
+- Suggesting implementations for partially specified functions
+- Exploring how training data quality affects generated code (correctness, style, quality issues)
+
+
+### “Clean” training set (for DSCc)
+
+The initial training set contains ~4.4M pairs. To construct the **clean dataset**:
+
+- We run **Semgrep** (static analysis) on all training functions.
+- Semgrep detects:
+  - Low-quality patterns
+  - Potentially problematic constructs
+  - Syntactically incorrect functions
+- All flagged low-quality / invalid functions are removed.
+
+This yields:
+
+- **`clean_training_set.json` — ~4.2M pairs**
+  - Derived from The Stack
+  - But with many quality issues and syntax errors filtered out.