Data Science for Software Engineering (ds4se) is an academic initiative to perform exploratory and causal inference analysis on software engineering artifacts and metadata. Data Management, Analysis, and Benchmarking for DL and Traceability.
After completing the tutorial, a vanilla causal process will be in place. Determine how to use the traceability data in the process to include establishing a .gml graph, identifying confounding features, selecting estimation methods, and selecting a refutation method. Start by just making a causal model from the traceability data and exploring the explore the impact of pre-pre-processing technique (conventional, bpe8k, bpe32k, bpe128k) on a particular similarity measure using Information theory features as confounders).
After completing the tutorial, a vanilla causal process will be in place. Determine how to use the traceability data in the process to include establishing a .gml graph, identifying confounding features, selecting estimation methods, and selecting a refutation method. Start by just making a causal model from the traceability data and exploring the explore the impact of pre-pre-processing technique (conventional, bpe8k, bpe32k, bpe128k) on a particular similarity measure using Information theory features as confounders).
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