Abstract
| Original language | English |
|---|---|
| Title of host publication | Functional and Logic Programming : 13th International Symposium, (FLOPS) 2016, Kochi, Japan, March 4-6, 2016 |
| Editors | Oleg Kiselyov, Andy King |
| Place of Publication | Cham |
| Publisher | Springer |
| Publication date | 2016 |
| Pages | 163-180 |
| ISBN (Print) | 978-3-319-29603-6 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | Thirteenth International Symposium on Functional and Logic Programming - Kochi, Japan Duration: 4 Mar 2016 → 6 Mar 2016 http://www.info.kochi-tech.ac.jp/FLOPS2016/ |
Conference
| Conference | Thirteenth International Symposium on Functional and Logic Programming |
|---|---|
| Country | Japan |
| City | Kochi |
| Period | 04/03/2016 → 06/03/2016 |
| Internet address |
| Series | Lecture Notes in Computer Science |
|---|---|
| Volume | 9613 |
| ISSN | 0302-9743 |
Bibliographical note
The uploaded version is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-29604-3_11Keywords
- static analysis
- resource analysis
Cite this
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A Transformational Approach to Parametric Accumulated-Cost Static Profiling. / Haemmerlé, Rémy; López García, Pedro; Liqat, Umer; Klemen, Maximiliano; Gallagher, John Patrick; Hermenegildo, Manuel.
Functional and Logic Programming : 13th International Symposium, (FLOPS) 2016, Kochi, Japan, March 4-6, 2016. ed. / Oleg Kiselyov; Andy King. Cham : Springer, 2016. p. 163-180 (Lecture Notes in Computer Science, Vol. 9613).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
TY - GEN
T1 - A Transformational Approach to Parametric Accumulated-Cost Static Profiling
AU - Haemmerlé, Rémy
AU - López García, Pedro
AU - Liqat, Umer
AU - Klemen, Maximiliano
AU - Gallagher, John Patrick
AU - Hermenegildo, Manuel
N1 - The uploaded version is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-319-29604-3_11
PY - 2016
Y1 - 2016
N2 - Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource usage functions, as it allows identifying the parts of a program that should be optimized, because of their greater impact on the total cost of program executions. We also report on our implementation of the proposed technique using the CiaoPP program analysis framework, and provide some experimental results.
AB - Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource usage functions, as it allows identifying the parts of a program that should be optimized, because of their greater impact on the total cost of program executions. We also report on our implementation of the proposed technique using the CiaoPP program analysis framework, and provide some experimental results.
KW - static analysis
KW - resource analysis
U2 - 10.1007/978-3-319-29604-3_11
DO - 10.1007/978-3-319-29604-3_11
M3 - Article in proceedings
SN - 978-3-319-29603-6
SP - 163
EP - 180
BT - Functional and Logic Programming
A2 - Kiselyov, Oleg
A2 - King, Andy
PB - Springer
CY - Cham
ER -