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Software programming requires both API reference (know-what) knowledge andprogramming task (know-how) knowledge. Lots of programming know-what andknow-how knowledge is documented in text, for example, API referencedocumentation and programming tutorials. To improve knowledge accessibility andusage, several recent studies use Natural Language Processing (NLP) methods toconstruct API know-what knowledge graph (API-KG) and programming task know-howknowledge graph (Task-KG) from software documentation. Although beingpromising, current API-KG and Task-KG are independent of each other, and thusare void of inherent connections between the two types of knowledge. Ourempirical study on Stack Overflow questions confirms that only 36% of the APIusage problems can be answered by the know-how or the know-what knowledgealone, while the rest questions require a fusion of both. Inspired by thisobservation, we make the first attempt to fuse API-KG and Task-KG by API entitylinking. This fusion creates nine categories of API semantic relations and twotypes of task semantic relations which are not present in the stand-aloneAPI-KG or Task-KG. According to the definitions of these new API and tasksemantic relations, our approach dives deeper than the surface-level APIlinking of API-KG and Task-KG, and infers nine categories of API semanticrelations from task descriptions and two types of task semantic relations withthe assistance of API-KG, which enrich the declaration or syntactic relationsin the current API-KG and Task-KG. Our fused and semantically-enriched API-TaskKG supports coherent API/Task-centric knowledge search by text or code queries.

1+1>2: Programming Know-What and Know-How Knowledge Fusion, Semantic Enrichment and Coherent Application