Dynamic program analysis encompasses the development of techniques and tools for analyzing computer software by exploiting information gathered from a program at runtime. The impressive amounts of data collected by dynamic analysis tools require efficient indexing and compression schemes, as well as on-line algorithmic techniques for mining relevant information on-the-fly in order to identify frequent events, hidden software patterns, or undesirable behaviors corresponding to bugs, malware, or intrusions. The paper explores how recent results in algorithmic theory for data-intensive scenarios can be applied to the design and implementation of dynamic program analysis tools, focusing on two important techniques: sampling and streaming.
Software streams: Big data challenges in dynamic program analysis / Finocchi, Irene. - 7921:(2013), pp. 124-134. ((Intervento presentato al convegno 9th Conference on Computability in Europe tenutosi a Milan, Italy nel July 1 -5, 2013 [10.1007/978-3-642-39053-1_15].
Titolo: | Software streams: Big data challenges in dynamic program analysis | |
Autori: | ||
Data di pubblicazione: | 2013 | |
Citazione: | Software streams: Big data challenges in dynamic program analysis / Finocchi, Irene. - 7921:(2013), pp. 124-134. ((Intervento presentato al convegno 9th Conference on Computability in Europe tenutosi a Milan, Italy nel July 1 -5, 2013 [10.1007/978-3-642-39053-1_15]. | |
Handle: | http://hdl.handle.net/11385/192665 | |
ISBN: | 9783642390524 | |
Appare nelle tipologie: | 04.1 - Contributo in Atti di convegno (Paper in Proceedings) |