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Non-Cumulative Resource Analysis (Author’s version)

dc.conference.dateApril 11-18, 2015
dc.conference.placeLondres, Reino Unido
dc.conference.title21st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS'15)
dc.contributor.authorAlbert Albiol, Elvira María
dc.contributor.authorCorreas Fernández, Jesús
dc.contributor.authorRomán Díez, Guillermo
dc.date.accessioned2023-06-19T16:04:34Z
dc.date.available2023-06-19T16:04:34Z
dc.date.issued2015
dc.descriptionPublicado en Lecture Notes in Computer Science, vol. 9035
dc.description.abstractExisting cost analysis frameworks have been defined for cumulative resources which keep on increasing along the computation. Traditional cumulative resources are execution time, number of executed steps, amount of memory allocated, and energy consumption. Noncumulative resources are acquired and (possibly) released along the execution. Examples of non-cumulative cost are memory usage in the presence of garbage collection, number of connections established that are later closed, or resources requested to a virtual host which are released after using them. We present, to the best of our knowledge, the first generic static analysis framework to infer an upper bound on the peak cost for non-cumulative types of resources. Our analysis comprises several components: (1) a pre-analysis to infer when resources are being used simultaneously, (2) a program-point resource analysis which infers an upper bound on the cost at the points of interest (namely the points where resources are acquired) and (3) the elimination from the upper bounds obtained in (2) of those resources accumulated that are not used simultaneously. We report on a prototype implementation of our analysis that can be used on a simple imperative language.
dc.description.departmentDepto. de Sistemas Informáticos y Computación
dc.description.facultyFac. de Informática
dc.description.refereedFALSE
dc.description.sponsorshipUnión Europea. FP7
dc.description.sponsorshipComunidad de Madrid
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/36323
dc.identifier.doi10.1007/978-3-662-46681-0_6
dc.identifier.issn0302-9743
dc.identifier.officialurlhttp://link.springer.com/chapter/10.1007/978-3-662-46681-0_6#page-1
dc.identifier.urihttps://hdl.handle.net/20.500.14352/36142
dc.journal.titleLecture notes in computer science
dc.language.isoeng
dc.page.final100
dc.page.initial85
dc.publisherSpringer
dc.relation.projectIDENVISAGE (610582)
dc.relation.projectIDSICOMORO-CM (S2013/ICE-3006)
dc.relation.projectIDTIN2012-38137
dc.rights.accessRightsopen access
dc.subject.cdu004.4
dc.subject.ucmSoftware
dc.subject.unesco3304.16 Diseño Lógico
dc.titleNon-Cumulative Resource Analysis (Author’s version)
dc.typeconference paper
dc.volume.number9035
dcterms.references1. E. Albert, P. Arenas, A. Flores-Montoya, S. Genaim, M. Gómez-Zamalloa, E. Martin-Martin, G. Puebla, and G. Román-Díez. SACO: Static Analyzer for Concurrent Objects. In TACAS'14, vol. 8413 of LNCS, pp 562-567. 2014. 2. E. Albert, P. Arenas, S. Genaim, G. Puebla, and D. Zanardini. Cost Analysis of Java Bytecode. In SOP'07, vol. 4421 of LNCS, pp 157-172. Springer, 2007. 3. E. Albert, J. Correas, and G. Rom_an-Díez. Peak Cost Analysis of Distributed Systems. In SAS'14, vol. 8723 of LNCS, pp 18-33. Springer, 2014. 15 4. E. Albert, A. Flores-Montoya, and S. Genaim. Analysis of May-Happen-in-Parallel in Concurrent bjects. In FORTE'12, vol. 7273 of LNCS, pp 35-51. Springer, 2012. 5. E. Albert, S. Genaim, and M. G_omez-Zamalloa. Parametric Inference of Memory Requirements for Garbage Collected Languages. In ISMM'10, pp 121-130. 2010. 6. D. E. Alonso-Blas and S. Genaim. On the Limits of the Classical Approach to Cost Analysis. In SAS 2012, vol. 7460 of LNCS, pp 405-421. Springer, 2012. 7. V. Braberman, F. Fern_andez, D. Garbervetsky, and S. Yovine. Parametric Prediction of Heap Memory Requirements. In ISMM'08, pp 141-150. ACM, 2008. 8. V. A. Braberman, D. Garbervetsky, S. Hym, and S. Yovine. Summary-based inference of quantitative bounds of live heap objects. SCP, 92:56-84, 2014. 9. A. Flores-Montoya and R. Hähnle. Resource analysis of complex programs with cost equations. In APLAS'14, vol. 8858 of LNCS, pp 275-295. Springer, 2014. 10. S. Gulwani, K. K. Mehra, and T. M. Chilimbi. Speed: Precise and Eficient Static Estimation of Program Computational Complexity. In POPL'09, pp 127-139. ACM, 2009. 11. M. Hofmann and S. Jost. Static prediction of heap space usage for first-order functional programs. In POPL'13, pp 185-197. ACM, 2003. 12. E. B. Johnsen, R. Hähnle, J. Schäfer, R. Schlatte, and M. Ste_en. ABS: A Core Language for Abstract Behavioral Specification. In FMCO'10 (Revised Papers), vol. 6957 of LNCS, pp 142-164. Springer, 2012. 13. Moritz Sinn, Florian Zuleger, and Helmut Veith. A simple and scalable static analysis for bound analysis and amortized complexity analysis. In Proc. of CAV'14, volume 8559, pages 745-761. Springer, 2014. 14. P. W. Trinder, M. I. Cole, K. Hammond, H.W. Loidl, and G. Michaelson. Resource analyses for parallel and distributed coordination. CCPE, 25(3):309-348, 2013. 15. John Whaley and Monica S. Lam. Cloning-based context-sensitive pointer alias analysis using binary decision diagrams. In PLDI, pages 131{144. ACM, 2004.
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