A communication infrastructure to support knowledge level agents on the web

Agent Communication Languages (ACLs) have been developed to provide a way for agents to communicate with each other supporting cooperation in Multi-Agent Systems. In the past few years many ACLs have been proposed for Multi-Agent Systems, such as KQML and FIPA-ACL. The goal of these languages is to support high-level, human like communication among agents, exploiting Knowledge Level features rather than symbol level ones. Adopting these ACLs, and mainly the FIPA-ACL specifications, many agent platforms and prototypes have been developed. Despite these efforts, an important issue in the research on ACLs is still open and concerns how these languages should deal (at the Knowledge Level) with possible failures of agents. Indeed, the notion of Knowledge Level cannot be straightforwardly extended to a distributed framework such as MASs, because problems concerning communication and concurrency may arise when several Knowledge Level agents interact (for example deadlock or starvation). The main contribution of this Thesis is the design and the implementation of NOWHERE, a platform to support Knowledge Level Agents on the Web. NOWHERE exploits an advanced Agent Communication Language, FT-ACL, which provides high-level fault-tolerant communication primitives and satisfies a set of well defined Knowledge Level programming requirements. NOWHERE is well integrated with current technologies, for example providing full integration for Web services. Supporting different middleware used to send messages, it can be adapted to various scenarios. In this Thesis we present the design and the implementation of the architecture, together with a discussion of the most interesting details and a comparison with other emerging agent platforms. We also present several case studies where we discuss the benefits of programming agents using the NOWHERE architecture, comparing the results with other solutions. Finally, the complete source code of the basic examples can be found in appendix.

Food safety and zoonotic enteric pathogens: sources, risk factors and transmission routes of human salmonellosis and campylobacteriosis

Salmonella and Campylobacter are common causes of human gastroenteritis. Their epidemiology is complex and a multi-tiered approach to control is needed, taking into account the different reservoirs, pathways and risk factors. In this thesis, trends in human gastroenteritis and food-borne outbreak notifications in Italy were explored. Moreover, the improved sensitivity of two recently-implemented regional surveillance systems in Lombardy and Piedmont was evidenced, providing a basis for improving notification at the national level. Trends in human Salmonella serovars were explored: serovars Enteritidis and Infantis decreased, Typhimurium remained stable and 4,[5],12:i:-, Derby and Napoli increased, suggesting that sources of infection have changed over time. Attribution analysis identified pigs as the main source of human salmonellosis in Italy, accounting for 43–60% of infections, followed by Gallus gallus (18–34%). Attributions to pigs and Gallus gallus showed increasing and decreasing trends, respectively. Potential bias and sampling issues related to the use of non-local/non-recent multilocus sequence typing (MLST) data in Campylobacter jejuni/coli source attribution using the Asymmetric Island (AI) model were investigated. As MLST data become increasingly dissimilar with increasing geographical/temporal distance, attributions to sources not sampled close to human cases can be underestimated. A combined case-control and source attribution analysis was developed to investigate risk factors for human Campylobacter jejuni/coli infection of chicken, ruminant, environmental, pet and exotic origin in The Netherlands. Most infections (~87%) were attributed to chicken and cattle. Individuals infected from different reservoirs had different associated risk factors: chicken consumption increased the risk for chicken-attributed infections; animal contact, barbecuing, tripe consumption, and never/seldom chicken consumption increased that for ruminant-attributed infections; game consumption and attending swimming pools increased that for environment-attributed infections; and dog ownership increased that for environment- and pet-attributed infections. Person-to-person contacts around holiday periods were risk factors for infections with exotic strains, putatively introduced by returning travellers.

Toward optimal display of physiologic status in critical care: I. Recreating bedside displays from archived physiologic data

BACKGROUND: Physiologic data display is essential to decision making in critical care. Current displays echo first-generation hemodynamic monitors dating to the 1970s and have not kept pace with new insights into physiology or the needs of clinicians who must make progressively more complex decisions about their patients. The effectiveness of any redesign must be tested before deployment. Tools that compare current displays with novel presentations of processed physiologic data are required. Regenerating conventional physiologic displays from archived physiologic data is an essential first step. OBJECTIVES: The purposes of the study were to (1) describe the SSSI (single sensor single indicator) paradigm that is currently used for physiologic signal displays, (2) identify and discuss possible extensions and enhancements of the SSSI paradigm, and (3) develop a general approach and a software prototype to construct such "extended SSSI displays" from raw data. RESULTS: We present Multi Wave Animator (MWA) framework-a set of open source MATLAB (MathWorks, Inc., Natick, MA, USA) scripts aimed to create dynamic visualizations (eg, video files in AVI format) of patient vital signs recorded from bedside (intensive care unit or operating room) monitors. Multi Wave Animator creates animations in which vital signs are displayed to mimic their appearance on current bedside monitors. The source code of MWA is freely available online together with a detailed tutorial and sample data sets.

Replaying past changes in multi-developer projects

What was I working on before the weekend? and What were the members of my team working on during the last week? are common questions that are frequently asked by a developer. They can be answered if one keeps track of who changes what in the source code. In this work, we present Replay, a tool that allows one to replay past changes as they happened at a fine-grained level, where a developer can watch what she has done or understand what her colleagues have done in past development sessions. With this tool, developers are able to not only understand what sequence of changes brought the system to a certain state (e.g., the introduction of a defect), but also deduce reasons for why her colleagues performed those changes. One of the applications of such a tool is also discovering the changes that broke the code of a developer.

Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients

To derive tests for randomness, nonlinear-independence, and stationarity, we combine surrogates with a nonlinear prediction error, a nonlinear interdependence measure, and linear variability measures, respectively. We apply these tests to intracranial electroencephalographic recordings (EEG) from patients suffering from pharmacoresistant focal-onset epilepsy. These recordings had been performed prior to and independent from our study as part of the epilepsy diagnostics. The clinical purpose of these recordings was to delineate the brain areas to be surgically removed in each individual patient in order to achieve seizure control. This allowed us to define two distinct sets of signals: One set of signals recorded from brain areas where the first ictal EEG signal changes were detected as judged by expert visual inspection ("focal signals") and one set of signals recorded from brain areas that were not involved at seizure onset ("nonfocal signals"). We find more rejections for both the randomness and the nonlinear-independence test for focal versus nonfocal signals. In contrast more rejections of the stationarity test are found for nonfocal signals. Furthermore, while for nonfocal signals the rejection of the stationarity test increases the rejection probability of the randomness and nonlinear-independence test substantially, we find a much weaker influence for the focal signals. In consequence, the contrast between the focal and nonfocal signals obtained from the randomness and nonlinear-independence test is further enhanced when we exclude signals for which the stationarity test is rejected. To study the dependence between the randomness and nonlinear-independence test we include only focal signals for which the stationarity test is not rejected. We show that the rejection of these two tests correlates across signals. The rejection of either test is, however, neither necessary nor sufficient for the rejection of the other test. Thus, our results suggest that EEG signals from epileptogenic brain areas are less random, more nonlinear-dependent, and more stationary compared to signals recorded from nonepileptogenic brain areas. We provide the data, source code, and detailed results in the public domain.

QUANTIFYING UNCERTAINTY IN GENOTYPE CALLS

Genome-wide association studies (GWAS) are used to discover genes underlying complex, heritable disorders for which less powerful study designs have failed in the past. The number of GWAS has skyrocketed recently with findings reported in top journals and the mainstream media. Mircorarrays are the genotype calling technology of choice in GWAS as they permit exploration of more than a million single nucleotide polymorphisms (SNPs)simultaneously. The starting point for the statistical analyses used by GWAS, to determine association between loci and disease, are genotype calls (AA, AB, or BB). However, the raw data, microarray probe intensities, are heavily processed before arriving at these calls. Various sophisticated statistical procedures have been proposed for transforming raw data into genotype calls. We find that variability in microarray output quality across different SNPs, different arrays, and different sample batches has substantial inuence on the accuracy of genotype calls made by existing algorithms. Failure to account for these sources of variability, GWAS run the risk of adversely affecting the quality of reported findings. In this paper we present solutions based on a multi-level mixed model. Software implementation of the method described in this paper is available as free and open source code in the crlmm R/BioConductor.

Enriching Reverse Engineering with Annotations

Much of the knowledge about software systems is implicit, and therefore difficult to recover by purely automated techniques. Architectural layers and the externally visible features of software systems are two examples of information that can be difficult to detect from source code alone, and that would benefit from additional human knowledge. Typical approaches to reasoning about data involve encoding an explicit meta-model and expressing analyses at that level. Due to its informal nature, however, human knowledge can be difficult to characterize up-front and integrate into such a meta-model. We propose a generic, annotation-based approach to capture such knowledge during the reverse engineering process. Annotation types can be iteratively defined, refined and transformed, without requiring a fixed meta-model to be defined in advance. We show how our approach supports reverse engineering by implementing it in a tool called Metanool and by applying it to (i) analyzing architectural layering, (ii) tracking reengineering tasks, (iii) detecting design flaws, and (iv) analyzing features.

Exploiting Runtime Information in the IDE

Developers rely on the mechanisms provided by their IDE to browse and navigate a large software system. These mechanisms are usually based purely on a system's static source code. The static perspective, however, is not enough to understand an object-oriented program's behavior, in particular if implemented in a dynamic language. We propose to enhance IDEs with a program's runtime information (eg. message sends and type information) to support program comprehension through precise navigation and informative browsing. To precisely specify the type and amount of runtime data to gather about a system under development, dynamically and on demand, we adopt a technique known as partial behavioral reflection. We implemented navigation and browsing enhancements to an IDE that exploit this runtime information in a prototype called Hermion. We present preliminary validation of our experimental enhanced IDE by asking developers to assess its usefulness to understand an unfamiliar software system.

Assigning Bug Reports using a Vocabulary-Based Expertise Model of Developers

For popular software systems, the number of daily submitted bug reports is high. Triaging these incoming reports is a time consuming task. Part of the bug triage is the assignment of a report to a developer with the appropriate expertise. In this paper, we present an approach to automatically suggest developers who have the appropriate expertise for handling a bug report. We model developer expertise using the vocabulary found in their source code contributions and compare this vocabulary to the vocabulary of bug reports. We evaluate our approach by comparing the suggested experts to the persons who eventually worked on the bug. Using eight years of Eclipse development as a case study, we achieve 33.6\% top-1 precision and 71.0\% top-10 recall.

Flow-Centric, Back-In-Time Debugging

Conventional debugging tools present developers with means to explore the run-time context in which an error has occurred. In many cases this is enough to help the developer discover the faulty source code and correct it. However, rather often errors occur due to code that has executed in the past, leaving certain objects in an inconsistent state. The actual run-time error only occurs when these inconsistent objects are used later in the program. So-called back-in-time debuggers help developers step back through earlier states of the program and explore execution contexts not available to conventional debuggers. Nevertheless, even back-in-time debuggers do not help answer the question, ``Where did this object come from?'' The Object-Flow Virtual Machine, which we have proposed in previous work, tracks the flow of objects to answer precisely such questions, but this VM does not provide dedicated debugging support to explore faulty programs. In this paper we present a novel debugger, called Compass, to navigate between conventional run-time stack-oriented control flow views and object flows. Compass enables a developer to effectively navigate from an object contributing to an error back-in-time through all the code that has touched the object. We present the design and implementation of Compass, and we demonstrate how flow-centric, back-in-time debugging can be used to effectively locate the source of hard-to-find bugs.

Extracting models from IDEs

Systems must co-evolve with their context. Reverse engineering tools are a great help in this process of required adaption. In order for these tools to be flexible, they work with models, abstract representations of the source code. The extraction of such information from source code can be done using a parser. However, it is fairly tedious to build new parsers. And this is made worse by the fact that it has to be done over and over again for every language we want to analyze. In this paper we propose a novel approach which minimizes the knowledge required of a certain language for the extraction of models implemented in that language by reflecting on the implementation of preparsed ASTs provided by an IDE. In a second phase we use a technique referred to as Model Mapping by Example to map platform dependent models onto domain specific model.

ModelDB in Computational Neuroscience Education - A research tool as interactive educational media

ModelDB's mission is to link computational models and publications, supporting the field of computational neuroscience (CNS) by making model source code readily available. It is continually expanding, and currently contains source code for more than 300 models that cover more than 41 topics. Investigators, educators, and students can use it to obtain working models that reproduce published results and can be modified to test for new domains of applicability. Users can browse ModelDB to survey the field of computational neuroscience, or pursue more focused explorations of specific topics. Here we describe tutorials and initial experiences with ModelDB as an interactive educational tool.

Software als Schutzgegenstand des Europäischen Urheberrechts

After 20 years of silence, two recent references from the Czech Republic (Bezpečnostní softwarová asociace, Case C-393/09) and from the English High Court (SAS Institute, Case C-406/10) touch upon several questions that are fundamental for the extent of copyright protection for software under the Computer Program Directive 91/25 (now 2009/24) and the Information Society Directive 2001/29. In Case C-393/09, the European Court of Justice held that “the object of the protection conferred by that directive is the expression in any form of a computer program which permits reproduction in different computer languages, such as the source code and the object code.” As “any form of expression of a computer program must be protected from the moment when its reproduction would engender the reproduction of the computer program itself, thus enabling the computer to perform its task,” a graphical user interface (GUI) is not protected under the Computer Program Directive, as it does “not enable the reproduction of that computer program, but merely constitutes one element of that program by means of which users make use of the features of that program.” While the definition of computer program and the exclusion of GUIs mirror earlier jurisprudence in the Member States and therefore do not come as a surprise, the main significance of Case C-393/09 lies in its interpretation of the Information Society Directive. In confirming that a GUI “can, as a work, be protected by copyright if it is its author’s own intellectual creation,” the ECJ continues the Europeanization of the definition of “work” which began in Infopaq (Case C-5/08). Moreover, the Court elaborated this concept further by excluding expressions from copyright protection which are dictated by their technical function. Even more importantly, the ECJ held that a television broadcasting of a GUI does not constitute a communication to the public, as the individuals cannot have access to the “essential element characterising the interface,” i.e., the interaction with the user. The exclusion of elements dictated by technical functions from copyright protection and the interpretation of the right of communication to the public with reference to the “essential element characterising” the work may be seen as welcome limitations of copyright protection in the interest of a free public domain which were not yet apparent in Infopaq. While Case C-393/09 has given a first definition of the computer program, the pending reference in Case C-406/10 is likely to clarify the scope of protection against nonliteral copying, namely in how far the protection extends beyond the text of the source code to the design of a computer program and where the limits of protection lie as regards the functionality of a program and mere “principles and ideas.” In light of the travaux préparatoires, it is submitted that the ECJ is also likely to grant protection for the design of a computer program, while excluding both the functionality and underlying principles and ideas from protection under the European copyright directives.

Cognitive response control in writer's cramp

Disturbances of the motor and sensory system as well as an alteration of the preparation of movements have been reported to play a role in the pathogenesis of dystonias. However, it is unclear whether higher aspects of cortical – like cognitive – functions are also involved. Recently, the NoGo-anteriorization (NGA) elicited with a visual continuous performance test (CPT) during recording of a 21-channel electroencephalogram has been proposed as an electrophysiological standard-index for cognitive response control. The NGA consists of a more anterior location of the positive area of the brain electrical field associated with the inhibition (NoGo-condition) compared with that of the execution (Go-condition) of a prepared motor response in the CPT. This response control paradigm was applied in 16 patients with writer’s cramp (WC) and 14 age matched healthy controls. Topographical analysis of the associated event-related potentials revealed a significant (P < 0.05) NGA effect for both patients and controls. Moreover, patients with WC showed a significantly higher global field power value (P < 0.05) in the Go-condition and a significantly higher difference-amplitude (P < 0.05) in the NoGo-condition. A source location analysis with the low resolution electromagnetic tomography (LORETA) method demonstrated a hypoactivity for the Go-condition in the parietal cortex of the right hemisphere and a hyperactivity in the NoGo-condition in the left parietal cortex in patients with WC compared with healthy controls. These results indicate an altered response control in patients with WC in widespread cortical brain areas and therefore support the hypothesis that the pathogenesis of WC is not restricted to a pure sensory-motor dysfunction.

Overthrowing the Tyranny of Alphabetical Ordering in Documentation Systems

Software developers are often unsure of the exact name of the API method they need to use to invoke the desired behavior. Most state-of-the-art documentation browsers present API artefacts in alphabetical order. Albeit easy to implement, alphabetical order does not help much: if the developer knew the name of the required method, he could have just searched for it in the first place. In a context where multiple projects use the same API, and their source code is available, we can improve the API presentation by organizing the elements in the order in which they are more likely to be used by the developer. Usage frequency data for methods is gathered by analyzing other projects from the same ecosystem and this data is used then to improve tools. We present a preliminary study on the potential of this approach to improve the API presentation by reducing the time it takes to find the method that implements a given feature. We also briefly present our experience with two proof-of-concept tools implemented for Smalltalk and Java.