Missing values are common in real-world data and may seriously affect data analytics such
as simple statistics and hypothesis testing. Generally speaking, there are two types of …

Programming by Examples (PBE) involves synthesizing intended programs in an underlying
domain-specific language from example-based specifications. PBE systems are already …

Data collected from heterogeneous sources often have inconsistencies in data format and
thus require transformation before the data can be used. A major issue of existing …

Programming by examples (PBE) is a rapidly growing subfield of AI, that aims to synthesize
user-intended programs using input-output examples from the task. As users can provide …

Many symptoms of poor performance in big data analytics such as computational skews,
data skews, and memory skews are input dependent. However, due to the lack of inputs that …

We formalize and study``programming by rewards''(PBR), a new approach for specifying
and synthesizing subroutines for optimizing some quantitative metric such as performance …

The constantly increasing volume of data collected in every aspect of our daily lives has
necessitated the development of more powerful and efficient analysis tools. In particular …

Visualizing a model checker's run on a model can be useful when trying to gain a deeper
understanding of the verification of the particular model. However, it can be difficult to …