Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Manual software testing is laborious and prone to human error. Yet, among practitioners, it is the most popular method for quality assurance. Automating the test case generation promises better effectiveness, especially for exposing corner-case bugs. Symbo ...
Modern software is plagued by elusive corner-case bugs (e.g., security bugs). Because there are no scalable, automated ways of finding them, such bugs can remain hidden until software is deployed in production. This thesis proposes approaches to solve this ...
Fast query and transaction processing is the goal of 40 years of database research and the reason of existence for many new database system architectures. In data management, system performance means acceptable response time and throughput on critical-path ...
Query plans offer diverse tradeoffs between conflicting cost metrics such as execution time, energy consumption, or execution fees in a multi-objective scenario. It is convenient for users to choose the desired cost tradeoff in an interactive process, dyna ...
We present the design and implementation of a SQL query processor that outperforms existing database systems and is written in just about 500 lines of Scala code - a convincing case study that high-level functional programming can handily beat C for system ...
We present the design and implementation of a SQL query processor that outperforms existing database systems and is written in just about 500 lines of Scala code – a convincing case study that high-level functional programming can handily beat C for system ...
Hardware trends oblige software to overcome three major challenges against systems scalability: (1) taking advantage of the implicit/vertical parallelism within a core that is enabled through the aggressive micro-architectural features, (2) exploiting the ...
The common "one size does not fit all" paradigm isolates transactional and analytical workloads into separate, specialized database systems. Operational data is periodically replicated to a data warehouse for analytics. Competitiveness of enterprises today ...
Traditional on disk row major tables have been the dominant storage mechanism in relational databases for decades. Over the last decade, however, with explosive growth in data volume and demand for faster analytics, has come the recognition that a differen ...
Many analytics applications generate mixed workloads, i.e., workloads comprised of analytical tasks with different processing characteristics including data pre-processing, SQL, and iterative machine learning algorithms. Examples of such mixed workloads ca ...
