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f-labs-io
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SpecSuite-Core

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test-driven-development

mutation-testing

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tzafrir commited on 1 day ago

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@@ -63,7 +63,7 @@ Each row is one spec version (4 specs × 2 versions). The `spec_yaml` field cont
 ```python
 from datasets import load_dataset
-specs = load_dataset("tzafrir/SpecSuite-Core", "specs")
 # Get SupportOps v1
 spec = specs["train"].filter(lambda x: x["spec_id"] == "supportops_v1")[0]
@@ -77,7 +77,7 @@ print(spec["spec_yaml"])    # Full YAML specification
 Each row is a mutation intent: a description of a plausible behavioral failure that the test suite should detect.
 ```python
-mutations = load_dataset("tzafrir/SpecSuite-Core", "mutations")
 # All critical mutations
 critical = mutations["train"].filter(lambda x: x["severity"] == "critical")
@@ -92,7 +92,7 @@ Categories: `policy_violation`, `process_violation`, `business_logic_violation`,
 Each row is one end-to-end TDAD pipeline run with metrics across all 4 evaluation dimensions.
 ```python
-results = load_dataset("tzafrir/SpecSuite-Core", "results")
 for r in results["train"]:
     print(f"{r['spec']}/{r['version']}: VPR={r['vpr_percent']}% HPR={r['hpr_percent']}% MS={r['mutation_score']}% ${r['total_cost_usd']:.2f}")

 ```python
 from datasets import load_dataset
+specs = load_dataset("f-labs-io/SpecSuite-Core", "specs")
 # Get SupportOps v1
 spec = specs["train"].filter(lambda x: x["spec_id"] == "supportops_v1")[0]
 Each row is a mutation intent: a description of a plausible behavioral failure that the test suite should detect.
 ```python
+mutations = load_dataset("f-labs-io/SpecSuite-Core", "mutations")
 # All critical mutations
 critical = mutations["train"].filter(lambda x: x["severity"] == "critical")
 Each row is one end-to-end TDAD pipeline run with metrics across all 4 evaluation dimensions.
 ```python
+results = load_dataset("f-labs-io/SpecSuite-Core", "results")
 for r in results["train"]:
     print(f"{r['spec']}/{r['version']}: VPR={r['vpr_percent']}% HPR={r['hpr_percent']}% MS={r['mutation_score']}% ${r['total_cost_usd']:.2f}")