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Léon Constantin Fopa

dblp:124/3116 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Program analysis · 87% Software maintenance and evolution · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis
dynamic analysis		 0.212013
Efficiently rewriting large multimedia application execution traces with few event sequences · KDD 2013
Program analysis › dynamic analysis › trace analysis
execution trace analysis		 0.212013
Efficiently rewriting large multimedia application execution traces with few event sequences · KDD 2013
Software maintenance and evolution
program comprehension		 0.012013
Efficiently rewriting large multimedia application execution traces with few event sequences · KDD 2013

Methods — techniques the papers use, named apart from their topics

trace rewriting · 0.2sequence mining · 0.2
YearPublicationVenuePosition
2013 Efficiently rewriting large multimedia application execution traces with few event sequences
abstract
The analysis of multimedia application traces can reveal important information to enhance program execution comprehension. However typical size of traces can be in gigabytes, which hinders their effective exploitation by application developers. In this paper, we study the problem of finding a set of sequences of events that allows a reduced-size rewriting of the original trace. These sequences of events, that we call blocks, can simplify the exploration of large execution traces by allowing application developers to see an abstraction instead of low-level events.
Christiane Kamdem Kengne, Léon Constantin Fopa, Alexandre Termier, Noha Ibrahim, Marie-Christine Rousset, Takashi Washio, Miguel Santana
 KDD2