Section: Research Program

Advanced Algorithms for Data Querying and Transformation

The efficient evaluation of queries over large databases remains a challenging task, to which certain optimization approaches based on static analysis of queries, data properties (such as integrity constraints), and indexing capabilities (such as materialized views) can still provide practically-relevant solutions. In this area, mainly for relational stores, we focus on query reformulation under constraints and views, as a uniform solution to problems such as view-based rewriting under constraints, semantic query optimization, and physical access path selection in query optimization.

With the increasing amount of available data, as well as the increasing complexity of data processing and transformations queries, for instance in applications such as relational data analysis or integration of Web data (e.g., XML or RDF), comes the need to better manage complex data transformations. In particular, it has become essential to analyze and debug data transformations. In this context, Oak has focused on verifying the semantic correctness of a declarative program that specifies a data transformation query, e.g., an SQL . In particular, we study one important sub-problem of data transformation analysis, namely the one of Why-Not questions. Such questions can explain to developers of complex data transformations or manipulations why their data transformation did not produce some specific results, although they expected them to do so.