Formal Language Recognition with the Java Type Checker

This paper is a theoretical study of a practical problem: the automatic generation of Java Fluent APIs from their specification. We explain why the problem\u27s core lies with the expressive power of Java generics. Our main result is that automatic generation is possible whenever the specification is an instance of the set of deterministic context-free languages, a set which contains most "practical" languages. Other contributions include a collection of techniques and idioms of the limited meta-programming possible with Java generics, and an empirical measurement demonstrating that the runtime of the "javac" compiler of Java may be exponential in the program\u27s length, even for programs composed of a handful of lines and which do not rely on overly complex use of generics

Economic Indicators as Public Interventions

This essay argues that the term public intellectual is too narrow for historical research about the public influence of economists and economic expertise. We propose, instead, the concept of public interventions to inform a more comprehensive approach that broadens the analytical frame by multiplying the relevant actors, modes, and targets of intervention yet could still include within it research on public intellectuals narrowly construed. As an empirical example, we suggest that the design and diffusion of economic indicators—specifically, the GDP and the myriad indicators compiled in recent years as part of proposals to replace it with a better representation of human welfare—could be analyzed as a specific mode by which economists intervene in and shape the public sphere

Reducing SAT to Max2SAT

In the literature we find reductions from 3SAT to Max2SAT. These reductions are based on the usage of a gadget, i.e., a combinatorial structure that allows translating constraints of one problem to constraints of another. Unfortunately, the generation of these gadgets lacks an intuitive or efficient method. In this paper, we provide an efficient and constructive method for Reducing SAT to Max2SAT and show empirical results of how MaxSAT solvers are more efficient than SAT solvers solving the translation of hard formulas for Resolution.Supported by projects PROOFS (PID2019-109137GB-C21) and EU-H2020-RIP LOGISTAR (No. 769142)

Community structure in industrial SAT instances

Modern SAT solvers have experienced a remarkable progress on solving industrial instances. It is believed that most of these successful techniques exploit the underlying structure of industrial instances. Recently, there have been some attempts to analyze the structure of industrial SAT instances in terms of complex networks, with the aim of explaining the success of SAT solving techniques, and possibly improving them. In this paper, we study the community structure, or modularity, of industrial SAT instances. In a graph with clear community structure, or high modularity, we can find a partition of its nodes into communities such that most edges connect variables of the same community. Representing SAT instances as graphs, we show that most application benchmarks are characterized by a high modularity. On the contrary, random SAT instances are closer to the classical Erdös-Rényi random graph model, where no structure can be observed. We also analyze how this structure evolves by the effects of the execution of a CDCL SAT solver, and observe that new clauses learned by the solver during the search contribute to destroy the original structure of the formula. Motivated by this observation, we finally present an application that exploits the community structure to detect relevant learned clauses, and we show that detecting these clauses results in an improvement on the performance of the SAT solver. Empirically, we observe that this improves the performance of several SAT solvers on industrial SAT formulas, especially on satisfiable instances.Peer ReviewedPostprint (published version

Towards clarifying the importance of interactions in Agent-Oriented Software Engineering

Interactions between subparts of a system have been recognized as the source of complexity in many fields ranging from physics, sociology, neurology, to software engineering. Agent-Oriented Software Engineering (AOSE) was born under the promise of conquering complexity and enabling the development of more complex software. However, current AOSE approaches do not provide enough engineering tools to deal with the complexity derived from interactions. More mature fields such as economy or component-based software systems have recognized that interactions present a predominant role in the determination of the desired outcome providing mature background that can be applied to AOSE. AOSE may improve its ability to deal with complex systems by improving the tools applied to manage agent’s interactions in the overall design of the system. In this paper, we justify this assessment and propose some principles to improve AOSE methodologies regarding complexit

The Potential Cost to New Zealand Dairy Farmers from the Introduction of Nitrate-Based Stocking Rate Restrictions

Introducing a stocking rate restriction is one possible course of action for regulators to improve water quality where it is affected by nitrate pollution. To determine the impact of a stocking rate restriction on a range of New Zealand dairy farms, a whole-farm model was optimised with and without a maximum stocking rate of 2.5 cows per hectare. Three farm systems, which differ by their level of feed-related capital, were examined for the changes to the optimal stocking rate and optimal level of animal milk production genetics when utility was maximised. The whole-farm model was optimised through the use of an evolutionary algorithm called differential evolution. The introduction of a stocking rate restriction would have a very large impact on the optimally organised high feed-related capital farm systems, reducing their certainty equivalent by almost half. However, there was no impact on the certainty equivalent of low feed-related capital systems.environmental regulation, dairy farms, whole-farm model, evolutionary algorithm, Environmental Economics and Policy, Livestock Production/Industries, Q12, Q52, C61,

Scale-Free Random SAT Instances

We focus on the random generation of SAT instances that have properties similar to real-world instances. It is known that many industrial instances, even with a great number of variables, can be solved by a clever solver in a reasonable amount of time. This is not possible, in general, with classical randomly generated instances. We provide a different generation model of SAT instances, called scale-free random SAT instances. This is based on the use of a non-uniform probability distribution P(i) ∼ i −β to select variable i, where β is a parameter of the model. This results in formulas where the number of occurrences k of variables follows a power-law distribution P(k) ∼ k −δ , where δ = 1 + 1/β. This property has been observed in most real-world SAT instances. For β = 0, our model extends classical random SAT instances. We prove the existence of a SAT– UNSAT phase transition phenomenon for scale-free random 2-SAT instances with β < 1/2 when the clause/variable ratio is m/n = 1−2β (1−β) 2 . We also prove that scale-free random k-SAT instances are unsatisfiable with a high probability when the number of clauses exceeds ω(n (1−β)k ). The proof of this result suggests that, when β > 1 − 1/k, the unsatisfiability of most formulas may be due to small cores of clauses. Finally, we show how this model will allow us to generate random instances similar to industrial instances, of interest for testing purposes.This research was supported by the project PROOFS, Grant PID2019-109137GB-C21 funded by MCIN/AEI/10.13039/501100011033

Coevolution of agents and networks: Opinion spreading and community disconnection

We study a stochastic model for the coevolution of a process of opinion formation in a population of agents and the network which underlies their interaction. Interaction links can break when agents fail to reach an opinion agreement. The structure of the network and the distribution of opinions over the population evolve towards a state where the population is divided into disconnected communities whose agents share the same opinion. The statistical properties of this final state vary considerably as the model parameters are changed. Community sizes and their internal connectivity are the quantities used to characterize such variations.Comment: To appear in Phys. Lett.