Paper Info
Title
Compositional performance prediction exemplified using generic object finalization analysis
Abstract
Static analysis methods for performance prediction of component-based software must be compositional in order to be scalable. In this paper, we explain the problem and our solution approach by analyzing the time to finalize or destroy generic objects, in the presence of data abstraction. Unlike initialization of objects to pre-specified values, finalization has to contend with objects with arbitrary values. In the process, we explain necessary trade-offs between precision and complexity and the need to strengthen specifications of operations and internal assertions, such as loop invariants for performance analysis.
Year
DOI
Venue
2009
10.1145/1566445.1566464
ACM Southeast Regional Conference 2005
Keywords
Field
DocType
internal assertion,performance analysis,arbitrary value,component-based software,data abstraction,performance prediction,static analysis method,loop invariants,compositional performance prediction,generic object,generic object finalization analysis,necessary trade-offs,static analysis
Data mining,Abstraction,Computer science,Static analysis,Theoretical computer science,Loop invariant,Software,Finalization,Initialization,Performance prediction,Scalability
Conference
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
Nighat Yasmin101.01
Murali Sitaraman227040.99