Generating certified code from formal proofs: a case study in homological algebra

We apply current theorem proving technology to certified code in the domain of abstract algebra. More concretely, based on a formal proof of the Basic Perturbation Lemma (a central result in homological algebra) in the prover Isabelle/HOL, we apply various code generation techniques, which lead to certified implementations of the associated algorithm in ML. In the formal proof, algebraic structures occurring in the Basic Perturbation Lemma are represented in a way, which is not directly amenable to code generation with the available tools. Interestingly, this representation is required in the proof, while for the algorithm simpler data structures are sufficient. Our approach is to establish a link between the non-executable setting of the proof and the executable representation in the algorithm, which is to be generated. This correspondence is established within the logical framework of Isabelle/HOL—that is, it is formally proved correct. The generated code is applied to and illustrated with a number of examples.     

SAR image processing using adaptive stack filter

Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is filtered by a Boolean function. The Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters on synthetic aperture radar (SAR) data is evaluated. With this aim, the equivalent number of looks for stack filtered data are calculated to assess the speckle noise reduction capability of this filter. Then a classification of simulated and real SAR images is carried out on data filtered with a stack filter trained with selected samples. The results of a maximum likelihood classification of these data are evaluated and compared with the results of classifying images previously filtered using the Lee and the Frost filters.     

Quantitative assessment of mobile web guidelines conformance

Conformance metrics for the mobile web can play a crucial role as far as engineering mobile websites are concerned, especially if they are automatically obtained. In this way, developers can have an idea in numeric terms of how suitable their developments are for mobile devices. However, there are a plethora of devices with their own particular features (screen size, formats support, etc.) that restrict a unified automatic assessment process. This paper proposes a tool-supported method for device-tailored assessment in terms of conformance with Mobile Web Best Practices 1.0, including the definition of five quantitative metrics for automatically measuring mobile web conformance: Navigability, Page layout, Page definition, User input and Overall score. The behaviour of these metrics was analysed for different devices and different web paradigms, both mobile web pages and their equivalent desktop pages. As expected, the results show that mobile web pages on more capable devices score higher. In addition, 20 users took part in an experiment aimed at discovering how conformance-based scores relate to usability dimensions. The results demonstrate that automatic scoring approaches strongly correlate with usability scores obtained by direct observation, such as task completion time and user satisfaction. This correlation is even stronger for the device-tailored assessment than the one that assumes a general profile for all devices. For instance, results show a strong negative correlation between Overall score and task completion time: ρ (9) = −0.81, (p < 0.05) for the generalist approach and ρ (9) = −0.88 for the device-tailored one, entailing that mobile web guidelines and the metrics based on their conformance capture usability aspects. This result challenges the widely accepted belief that conformance to guidelines does not imply more usable web pages, at least for web accessibility conformance.     

An unified approach for DTC design using interactive tools

This paper presents an interactive tool for dead-time compensator design. The tool is based on an unified dead-time compensator and considers models commonly used in industrial process control. The main contribution of this work is that the proposed tool and controller are simple to analyze and tune as they are based on an unique modified structure of the Smith predictor valid for every type of dead-time process (including integrating and unstable systems). Simple frequency analysis and block diagram transformations are used together with simulations to illustrate the main problems associated to the control of dead-time processes. Several examples of typical processes are presented to illustrate the fundamental concepts associated to the control of these systems. The interactive tool is not only useful for designing and analyzing but also for training and educational purposes.     

Multi‐criteria IoT resource discovery: a comparative analysis

The growth of real‐world objects with embedded and globally networked sensors allows to consolidate the Internet of things paradigm and increase the number of applications in the domains of ubiquitous and context‐aware computing. The merging between cloud computing and Internet of things named cloud of things will be the key to handle thousands of sensors and their data. One of the main challenges in the cloud of things is context‐aware sensor search and selection. Typically, sensors require to be searched using two or more conflicting context properties. Most of the existing work uses some kind of multi‐criteria decision analysis to perform the sensor search and selection, but does not show any concern for the quality of the selection presented by these methods. In this paper, we analyse the behaviour of the SAW, TOPSIS and VIKOR multi‐objective decision methods and their quality of selection comparing them with the Pareto‐optimality solutions. The gathered results allow to analyse and compare these algorithms regarding their behaviour, the number of optimal solutions and redundancy. Copyright © 2016 John Wiley & Sons, Ltd.     

Cryptanalysis of the RNTS system

Internet of Things is a paradigm that enables communication between different devices connected to a local network or to Internet. Identification and communication between sensors used in Internet of Things and devices like smart-phones or tablets are established using radio frequency identification technology. However, this technology still has several security and privacy issues because of its severe computational constraints. In 2011, Jeong and Anh proposed the combined use of an authentication radio frequency identification protocol together with a ticket issuing system for bank services (in J. Supercomput. 55:307, 2011). In this paper we show that their message generation is weak, because it abuses the XOR operation and the use of a counter, which leaks too much secret protocol information. Our analysis shows important security faults that ruin most of the security properties claimed in the original paper. More precisely, information privacy (via a disclosure and leakage attack) and location privacy (traceability attack) are both compromised. Moreover, an attacker can disrupt the proper working of the system by exploiting the fact that message integrity is not properly checked.     

Discovering filter keywords for company name disambiguation in twitter

A major problem in monitoring the online reputation of companies, brands, and other entities is that entity names are often ambiguous (apple may refer to the company, the fruit, the singer, etc.). The problem is particularly hard in microblogging services such as Twitter, where texts are very short and there is little context to disambiguate. In this paper we address the filtering task of determining, out of a set of tweets that contain a company name, which ones do refer to the company. Our approach relies on the identification of filter keywords: those whose presence in a tweet reliably confirm (positive keywords) or discard (negative keywords) that the tweet refers to the company.We describe an algorithm to extract filter keywords that does not use any previously annotated data about the target company. The algorithm allows to classify 58% of the tweets with 75% accuracy; and those can be used to feed a machine learning algorithm to obtain a complete classification of all tweets with an overall accuracy of 73%. In comparison, a 10-fold validation of the same machine learning algorithm provides an accuracy of 85%, i.e., our unsupervised algorithm has a 14% loss with respect to its supervised counterpart.Our study also shows that (i) filter keywords for Twitter does not directly derive from the public information about the company in the Web: a manual selection of keywords from relevant web sources only covers 15% of the tweets with 86% accuracy; (ii) filter keywords can indeed be a productive way of classifying tweets: the five best possible keywords cover, in average, 28% of the tweets for a company in our test collection.     

Durability Prediction for GFRP Reinforcing Bars Using Short-Term Data of Accelerated Aging Tests

This paper presents a procedure based on the Arrhenius relation to predict the long-term behavior of glass fiber-reinforced polymer (GFRP) bars in concrete structures, based on short-term data from accelerated aging tests. GFRP reinforcing bars were exposed to simulated concrete pore solutions at 20, 40, and 60°C. The tensile strengths of the bars determined before and after exposure were considered a measure of the durability performance of the specimens. Based on the short-term data, a detailed procedure is developed and verified to predict the long-term durability performance of GFRP bars. A modified Arrhenius analysis is included in the procedure to evaluate the validity of accelerated aging tests before the prediction is made. The accelerated test and prediction procedure used in this study can be a reliable method to evaluate the durability performance of FRP composites exposed to solutions or in contact with concrete.