Abstract
In this paper we consider linear arithmetic constraints over infinite trees whose nodes are labelled with nonnegative real numbers. These constraints arose in the context of resource inference for object-oriented programs but should be of independent interest. It is as yet open whether satisfiability of these constraint systems is at all decidable. For a restricted fragment motivated from the application to resource inference we are however able to provide a heuristic decision procedure based on regular trees. We also observe that the related problem of optimising linear objectives over these infinite trees falls into the area of convex optimisation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Blumensath, A., Grädel, E.: Automatic structures. In: LICS, pp. 51–62 (2000)
Dantchev, S., Valencia, F.D.: On infinite csp’s (2007)
Hofmann, M.O., Jost, S.: Type-Based Amortised Heap-Space Analysis. In: Sestoft, P. (ed.) ESOP 2006. LNCS, vol. 3924, pp. 22–37. Springer, Heidelberg (2006)
Hofmann, M., Rodriguez, D.: Efficient Type-Checking for Amortised Heap-Space Analysis. In: Grädel, E., Kahle, R. (eds.) CSL 2009. LNCS, vol. 5771, pp. 317–331. Springer, Heidelberg (2009)
Silva, A., Rutten, J.J.M.M.: A coinductive calculus of binary trees. Inf. Comput. 208(5), 578–593 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hofmann, M., Rodriguez, D. (2012). Linear Constraints over Infinite Trees. In: Bjørner, N., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2012. Lecture Notes in Computer Science, vol 7180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28717-6_27
Download citation
DOI: https://doi.org/10.1007/978-3-642-28717-6_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28716-9
Online ISBN: 978-3-642-28717-6
eBook Packages: Computer ScienceComputer Science (R0)