dief: Tools for Computing Diefficiency Metrics
In maribelacosta/dief: Metrics for Continuous Efficiency

Description Details Author(s) References Examples

An implementation of the metrics dief@t and dief@k to measure the diefficiency (or continuous efficiency) of incremental approaches, see Acosta, M., Vidal, M. E., & Sure-Vetter, Y. (2017) <doi:10.1007/978-3-319-68204-4_1>. The metrics dief@t and dief@k allow for measuring the diefficiency during an elapsed time period t or while k answers are produced, respectively. dief@t and dief@k rely on the computation of the area under the curve of answer traces, and thus capturing the answer rate concentration over a time interval.

Package:	dief
Type:	Package
Version:	1.2
Date:	2017-10-30
License:	MIT

Maribel Acosta

Maintainer: Maribel Acosta <maribel.acosta@kit.edu>

Maribel Acosta, Maria-Esther Vidal, and York Sure-Vetter. "Diefficiency metrics: Measuring the continuous efficiency of query processing approaches." In International Semantic Web Conference, pp. 3-19. Springer, Cham, 2017.

# This example uses the answer traces provided in the package.  
# These traces record the answers produced by three approaches "Selective", 
# "Not Adaptive", "Random"  when executing the test "Q9.sparql"
data(traces)
	
# Plot answer traces for test "Q9.sparql"
plotAnswerTrace(traces, "Q9.sparql")
	
# Compute dief@t with t the time where the slowest approach produced the last answer.
dieft(traces, "Q9.sparql")
	
# Compute dief@t after 7.5 time units (seconds) of execution. 
dieft(traces, "Q9.sparql", 7.5)