Mon 24 Jun 2019 14:40 - 15:00 at 229AB - Synthesis Chair(s): Nuno P. Lopes

Many programs that interact with a database need to undergo schema refactoring several times during their life cycle. Since this process typically requires making significant changes to the program's implementation, schema refactoring is often non-trivial and error-prone. Motivated by this problem, we propose a new technique for automatically synthesizing a new version of a database program given its original version and the source and target schemas. Our method does not require manual user guidance and ensures that the synthesized program is equivalent to the original one. Furthermore, our method is quite efficient and can synthesize new versions of database programs (containing up to 263 functions) that are extracted from real-world web applications with an average synthesis time of 69.4 seconds.

Conference Day
Mon 24 Jun

Displayed time zone: Tijuana, Baja California change

14:00 - 15:30
SynthesisPLDI Research Papers at 229AB
Chair(s): Nuno P. LopesMicrosoft Research
14:00
20m
Talk
Resource-Guided Program Synthesis
PLDI Research Papers
Tristan KnothUniversity of California at San Diego, USA, Di WangCarnegie Mellon University, Nadia PolikarpovaUniversity of California, San Diego, Jan HoffmannCarnegie Mellon University
Media Attached
14:20
20m
Talk
Using Active Learning to Synthesize Models of Applications That Access Databases
PLDI Research Papers
Jiasi ShenMassachusetts Institute of Technology, Martin C. RinardMassachusetts Institute of Technology
DOI Media Attached
14:40
20m
Talk
Synthesizing Database Programs for Schema Refactoring
PLDI Research Papers
Yuepeng WangUniversity of Texas at Austin, James DongUniversity of Texas at Austin, USA, Rushi ShahUT Austin, Isil DilligUT Austin
Media Attached
15:00
20m
Talk
Synthesis and Machine Learning for Heterogeneous Extraction
PLDI Research Papers
Arun IyerMicrosoft Research, India, Manohar JonnalageddaInpher Inc., Switzerland, Suresh ParthasarathyMicrosoft Research, India, Arjun RadhakrishnaMicrosoft, Sriram RajamaniMicrosoft Research
Media Attached