Title
Validating model-driven performance predictions on random software systems
Abstract
Software performance prediction methods are typically validated by taking an appropriate software system, performing both performance predictions and performance measurements for that system, and comparing the results. The validation includes manual actions, which makes it feasible only for a small number of systems. To significantly increase the number of systems on which software performance prediction methods can be validated, and thus improve the validation, we propose an approach where the systems are generated together with their models and the validation runs without manual intervention. The approach is described in detail and initial results demonstrating both its benefits and its issues are presented.
Year
DOI
Venue
2010
10.1007/978-3-642-13821-8_3
QoSA
Keywords
Field
DocType
appropriate software system,initial result,performance prediction,performance measurement,random software system,software performance prediction method,model-driven performance prediction,manual intervention,small number,manual action,software performance,software systems
Small number,Systems engineering,Computer science,Software system,Software performance testing,Reliability engineering
Conference
Volume
ISSN
ISBN
6093
0302-9743
3-642-13820-9
Citations 
PageRank 
References 
1
0.36
24
Authors
3
Name
Order
Citations
PageRank
Vlastimil Babka1295.28
Petr Tůma210813.38
Lubomír Bulej316520.20