NSAD 2019

The 8th International Workshop on Numerical and Symbolic Abstract Domains

October 8, 2019
Porto, Portugal

Objective

Abstract domains are a key notion in Abstract Interpretation theory and practice. They embed the semantic choices, data-structures and algorithmic aspects, and implementation decisions. The Abstract Interpretation framework provides constructive and systematic formal methods to design, compose, compare, study, prove, and apply abstract domains. Many abstract domains have been designed so far: numerical domains (intervals, congruences, polyhedra, polynomials, etc.), symbolic domains (shape domains, trees, etc.), but also domain operators (products, powersets, completions, etc.), and have been applied to several kinds of static analyses (safety, termination, probability, etc.). Abstract domains are a key notion in Abstract Interpretation theory and practice. They embed the semantic choices, data-structures and algorithmic aspects, and implementation decisions of The 8th International Workshop on Numerical and Symbolic Abstract Domains is intended to discuss on-going works and ideas in the field. This year's edition will be more open to work in progress, and contributions coming from other close communities such as constraint solving, compilation, worst-case execution time communities, will be welcome.

NSAD 2019 will be co-located with SAS 2019.

Scope

The technical program of TAPAS 2019 will consist of invited lectures together with presentations, based on submitted extended abstracts.

Submissions can cover any aspect of numerical and symbolic abstract domains, such that:

• cases studies or problem statements coming from close communities
• numeric abstract domains
• symbolic abstract domains
• extrapolations and accelerations
• compositions and operations on abstract domains
• data structures and algorithms for abstract domains
• novel applications of abstract domains implementations
• practical experiments and comparisons
• implementations

Like TAPAS, this workshop welcomes work in progress, overviews of more extensive work, programmatic or position papers and tool presentations.

Invited Speakers

Proceedings and post-proceedings

The workshop will have informal proceedings, posted on its web page.

Revised versions of selected papers will be published after the workshop by Springer in a volume of its Lecture Notes in Computer Science (LNCS), which will collect contributions to some workshops and symposia co-located with FM 2019. Condition for inclusion in the post-proceedings is that at least one of the co-authors has presented the paper at the workshop.

Submission instructions (for postproceedings)

Authors of *all* accepted papers of the NSAD workshop are invited to submit a short or long version of their submissions for publication in the FM postproceedings. This submission will receive a second round of review. You can submit your paper at any time after Oct 11th, until Nov 5th (firm, due to postproceedings short timing). NSAD 2019 author interface of EasyChair. Springer considers full papers to have 12-15 pages and short papers to have 6-8 pages, LNCS Style. (no paper shorter than 6 pages). We strongly encourage full papers submissions. Preference will be given to full papers. There is no hard upper page limit; authors should not try to squeeze papers with various tricks as the final editing by Springer may lengthen a paper unexpectedly.

• Farah Benmouhoub, Pierre-Loic Garoche and Matthieu Martel Improving the Numerical Accuracy of Parallel Programs by Data Mapping
• Vincenzo Arceri, Michele Pasqua and Isabella Mastroeni An abstract domain for objects in dynamic programming languages
• Ghiles Ziat, Alexandre Maréchal, Marie Pelleau, Antoine Miné and Charlotte TruchetCombination of Boxes and Polyhedra Abstractions for Constraint Solving
• Guillaume Cluzel and Cezara Drăgoi Towards an abstraction for data structures that implement cooperation mechanisms
• Maxime Jacquemin and Franck Vedrine A Dividing Method Minimizing the Linearization Term in Affine Arithmetic
• Solène Mirliaz and David PichardieFlow Insensitive Relational Static Analysis