Search

Aim: Analyses of biogeographical patterns and macroecology of islands require large datasets reporting the occurrence of species. The Mediterranean region is a biodiversity hotspot, which hosts a large number of reptile species and has been the focus of many studies. Nevertheless, comprehensive inventories describing the features and biodiversity of these environments are lacking. We gathered a dataset summarizing data on reptile distribution on islands of the Mediterranean basin and Macaronesia, also including detailed information on the geographical features. Location: Islands from the Mediterranean Basin, the Atlantic Ocean within the Mediterranean biogeographical region, and Macaronesia (Canary and Savage Islands, Azores, Madeira and Cape Verde). Time period: Present. Taxon: Reptiles (squamates and turtles). Methods: Initially, we developed a geographical database describing islands of the study region, then gathered information on reptile occurrences from 757 bibliographical sources, including atlases, published papers and the grey literature. Through a critical review of these sources, we also obtained information on the status of populations (native, island endemic or non-native) and on the reliability of occurrence data. Results: We obtained basic geographical information from 1875 islands covering the whole study region and with a very broad range of geographical features. We gathered >4150 records of reptile occurrence on islands, referring to 198 taxonomic units (species or species complexes); information on population status was available for 84.9% of records. Data are provided as comma-delimited text files. Main conclusions: The database provides a key resource for biogeographical analyses and can also serve as a backbone for conservation studies. The availability of a large database on island features can also be useful for biogeographers working on other taxonomic groups. Nevertheless, more data are required for some geographical areas, in order to

We present a generic scheme for the declarative debugging of programs that are written in rewriting-based languages that are equipped with narrowing. Our aim is to provide an integrated development environment in which it is possible to debug a program and then correct it automatically. Our methodology is based on the combination (in a single framework) of a semantics-based diagnoser that identifies those parts of the code that contain errors and an inductive learner that tries to repair them, once the bugs have been located in the program. We develop our methodology in several steps. First, we associate with our programs a semantics that is based on a (continuous) immediate consequence operator, TR, which models the answers computed by narrowing and is parametric w.r.t. the evaluation strategy, which can be eager or lazy. Then, we show that, given the intended specification of a program R, it is possible to check the correctness of R by a single step of TR. In order to develop an effective debugging method, we approximate the computed answers semantics of R and derive a finitely terminating bottom-up abstract diagnosis method, which can be used statically. Finally, a bug-correction program synthesis methodology attempts to correct the erroneous components of the wrong code. We propose a hybrid, top-down (unfolding-based) as well as bottom-up (induction-based), correction approach that is driven by a set of evidence examples which are automatically produced as an outcome by the diagnoser. The resulting program is proven to be correct and complete w.r.t. the considered example sets. Our debugging framework does not require the user to provide error symptoms in advance or to answer difficult questions concerning program correctness. An implementation of our debugging system has been undertaken which demonstrates the workability of our approach. © 2010 Elsevier B.V. All rights reserved.

We propose a new methodology for synthesizing correct functional logic programs. We aim to create an integrated development environment in which it is possible to debug a program and correct it automatically. We start from a declarative diagnoser that we have developed previously which allows us to identify wrong program rules w.r.t. an intended specification. Then a bug-correction, program synthesis methodology tries to correct the erroneous components of the wrong code. We propose a hybrid, top-down (unfolding-based) as well as bottom-up (induction-based), approach for the automatic correction of functional logic programs which is driven by a set of evidence examples which are automatically produced as an outcome by the diagnoser. The resulting program is proven to be correct and complete w.r.t. the considered example sets. Finally, we also provide a prototypical implementation which we use for an experimental evaluation of our system. © Springer-Verlag Berlin Heidelberg 2003.

We present a generic scheme for the declarative debugging of programs that are written in rewriting-based languages that are equipped with narrowing. Our aim is to provide an integrated development environment in which it is possible to debug a program and then correct it automatically. Our methodology is based on the combination (in a single framework) of a semantics-based diagnoser that identifies those parts of the code that contain errors and an inductive learner that tries to repair them, once the bugs have been located in the program. We develop our methodology in several steps. First, we associate with our programs a semantics that is based on a (continuous) immediate consequence operator, TR, which models the answers computed by narrowing and is parametric w.r.t. the evaluation strategy, which can be eager or lazy. Then, we show that, given the intended specification of a program R, it is possible to check the correctness of R by a single step of TR. In order to develop an effective debugging method, we approximate the computed answers semantics of R and derive a finitely terminating bottom-up abstract diagnosis method, which can be used statically. Finally, a bug-correction program synthesis methodology attempts to correct the erroneous components of the wrong code. We propose a hybrid, top-down (unfolding-based) as well as bottom-up (induction-based), correction approach that is driven by a set of evidence examples which are automatically produced as an outcome by the diagnoser. The resulting program is proven to be correct and complete w.r.t. the considered example sets. Our debugging framework does not require the user to provide error symptoms in advance or to answer difficult questions concerning program correctness. An implementation of our debugging system has been undertaken which demonstrates the workability of our approach. © 2010 Elsevier B.V. All rights reserved.

We present a general framework for the declarative debugging of functional logic programs, which is valid both for eager as well as lazy programs. We associate to our programs a semantics based on a (continuous) immediate consequence operator which models computed answers. Then we show that, given the intended specification of a program P, it is possible to check the correctness of P by a single step of the immediate consequence operator. We also present a more effective methodology which is based on abstract interpretation. By approximating the intended specification of the success set we derive a finitely terminating debugging method, which can be used statically. Our framework is parametric w.r.t. to the chosen approximation of the success set. We present one specific example of approximation. We provide an implementation of our debugging system which shows experimentally on a wide set of benchmarks that we are able to find some common errors in the user programs. © 2001 Published by Elsevier Science B. V.

We present a generic scheme for the declarative debugging of functional logic programs which is valid for eager as well as lazy programs. In particular we show that the framework extends naturally some previous work and applies to the most modern lazy strategies, such as needed narrowing. First we associate to our programs a semantics based on a (continuous) immediate consequence operator, TR, which models computed answers. We show that, given the intended specification of a program R, it is possible to check the correctness of R by a single step of TR. We consider then a more effective methodology which is based on abstract interpretation: by approximating the intended specification of the success set we derive a finitely terminating diagnosis method, which can be used statically and is parametric w.r.t. to the chosen approximation. In order to correct the bugs, we sketch a preliminary deductive approach which uses example-guided unfolding. We specialize the incorrect rules w.r.t. sets of positive and negative examples which are gathered (bottom-up) during the diagnosis process, so that all refutations of negative examples and no refutation of positive examples are excluded. Our debugging framework does not require the user to either provide error symptoms in advance or answer difficult questions concerning program correctness. We extend an implementation of our system to the case of needed narrowing and illustrate it through some examples which demonstrate the practicality of our approach. © 2002 Published by Elsevier Science B.V.

[EN] Keeping XML data in a consistent state w.r.t. both structure and content is a burdensome task. To maintain the consistency of ever-larger, complex XML repositories, suitable mechanisms that are able to x every possible inconsistency are needed. In this article, we present a methodology for semi-automatically repairing faulty XML repositories that can be integrated on top of an existing rewriting-based veri cation engine. As a formal basis for representing consistency criteria, we use a rule-based description formalism that is realized in the language Maude. Then, starting from a categorization of the kinds of errors that can be found during the veri cation process, we formulate a stepwise transformation procedure that achieves correctness and completeness of the XML repository w.r.t. its Maude formal speci cation while strictly observing the structure of the XML documents. With the aim of increasing the level of automation of our repair methodology, we also de ne two correction strategies and two completion strategies that reduce either the amount of information to be changed or the number of repair actions to be executed in order to deliver an XML repository that is both correct and complete. Finally, we describe a prototype implementation of the repairing tool, which we use for an experimental evaluation of our method with good results. ©2013 Elsevier Inc.All rights reserved.

Concurrent constraint programming (ccp), like most of the concurrent paradigms, has a mechanism of global choice which makes computations dependent on the scheduling of processes. This is one of the main reasons why the formal semantics of ccp is more complicated than the one of its deterministic and local-choice sublanguages. In this paper we study various subsets of ccp obtained by adding some restriction on the notion of choice, or by requiring confluency, i.e. independency from the scheduling strategy. We show that it is possible to define simple denotational semantics for these subsets, for various notions of observables. Finally, as an application of our results we develop a framework for the compositional analysis of full ccp. The basic idea is to approximate an arbitrary ccp program by a program in the restricted language, and then analyze the latter, by applying the standard techniques of abstract interpretation to its denotational semantics.