Paolo Nesi

Temporal logics for real-time system specification

The specification of reactive and real-time systems must be supported by formal, mathematically-founded methods in order to be satisfactory and reliable. Temporal logics have been used to this end for several years. Temporal logics allow the specification of system behavior in terms of logical formulas, including temporal constraints, events, and the relationships between the two. In the last ten years, temporal logics have reached a high degree of expressiveness. Most of the temporal logics proposed in the last few years can be used for specifying reactive systems, although not all are suitable for specifying real-time systems. In this paper we present a series of criteria for assessing the capabilities of temporal logics for the specification, validation, and verification of real-time systems. Among the criteria are the logics expressiveness, the logics order, presence of a metric for time, the type of temporal operators, the fundamental time entity, and the structure of time. We examine a selection of temporal logics proposed in the literature. To make the comparison clearer, a set of typical specifications is identified and used with most of the temporal logics considered, thus presenting the reader with a number of real examples.

Estimation and prediction metrics for adaptive maintenance effort of object-oriented systems

Many software systems built in recent years have been developed using object-oriented technology and, in some cases, they already need adaptive maintenance in order to satisfy market and customer needs. In most cases, the estimation and prediction of maintenance effort is performed with difficulty due to the lack of metrics and suitable models. In this paper, a model and metrics for estimation/prediction of adaptive maintenance effort are presented and compared with some other solutions taken from the literature. The model proposed can be used as a general approach for adopting well-known metrics (typically used for the estimation of development effort) for the estimation/prediction of adaptive maintenance effort. The model and metrics proposed have been validated against real data by using multilinear regression analysis. The validation has shown that several well-known metrics can be profitably employed for the estimation/prediction of maintenance effort.

Variational approach to optical flow estimation managing discontinuities

Abstract Projection of the 3D velocity of real objects on the image plane is often called the ‘velocity field’. The estimation of this field is one of the most important research topics in computer vision. In the literature, there are numerous solutions which adopt a sort of continuity equation called optical flow constrain (OFC). The solution of this constraint equation is usually called the ‘optical flow’ field, and can be considered equal to the velocity field under particular assumptions. The structure of the OFC equation makes the optical flow estimation an ill-posed problem, like many other inverse problems in early vision. For this reason, many reglarization techniques were used in the past for estimating optical flow. The major drawback of these solutions is the presence of propagation effects which produce the loss of the information associated to the discontinuities. On the other hand, the dicontinuities are very important for estimating precise optical flow fields, and detecting the shape of moving objects. In this paper, we propose a new solution based on variational techniques for optical flow estimation and regularization, which takes into account the discontinuities, and strongly reduces the related problems. The proposed method is called ‘discontinuity-dependent variational solution ’.

Effort estimation and prediction of object-oriented systems

Abstract Due to the growing diffusion of the object-oriented paradigm (OOP) and the need of maintaining under control the process of software development, industries are looking for metrics capable of producing satisfactory effort estimations and predictions. These metrics have to produce results with a known confidence since the early phases of software life-cycle in order to establish a process of prediction and correction of costs. To this end, specific metrics are needed in order to maintain under control object-oriented system development. In this paper, new complexity and size metrics for effort evaluation and prediction are presented and compared with respect to the most important metrics proposed for the same purpose in the literature. The validation of the most important of these metrics is also reported.

Comparing fault-proneness estimation models

Over the last, years, software quality has become one of the most important requirements in the development of systems. Fault-proneness estimation could play a key role in quality control of software products. In this area, much effort has been spent in defining metrics and identifying models for system assessment. Using this metrics to assess which parts of the system are more fault-proneness is of primary importance. This paper reports a research study begun with the analysis of more than 100 metrics and aimed at producing suitable models for fault-proneness estimation and prediction of software modules/files. The objective has been to find a compromise between the fault-proneness estimation rate and the size of the estimation model in terms of number of metrics used in the model itself. To this end, two different methodologies have been used, compared, and some synergies exploited. The methodologies were the logistic regression and the discriminant analyses. The corresponding models produced for fault-proneness estimation and prediction have been based on metrics addressing different aspects of computer programming. The comparison has produced satisfactory results in terms of fault-proneness prediction. The produced models have been cross validated by using data sets derived from source codes provided by two application scenarios.

A study on fault-proneness detection of object-oriented systems

Fault-proneness detection in object-oriented systems is an interesting area for software companies and researchers. Several hundred metrics have been defined with the aim of measuring the different aspects of object-oriented systems. Only a few of them have been validated for fault detection, and several interesting works with this view have been considered. This paper reports a research study starting from the analysis of more than 200 different object-oriented metrics extracted from the literature with the aim of identifying suitable models for the detection of the fault-proneness of classes. Such a large number of metrics allows the extraction of a subset of them in order to obtain models that can be adopted for fault-proneness detection. To this end, the whole set of metrics has been classified on the basis of the measured aspect in order to reduce them to a manageable number; then, statistical techniques were employed to produce a hybrid model comprised of 12 metrics. The work has focused on identifying models that can detect as many faulty classes as possible and, at the same time, that are based on a manageably small set of metrics. A compromise between these aspects and the classification correctness of faulty and non-faulty classes was the main challenge of the research. As a result, two models for fault-proneness class detection have been obtained and validated.

Optical flow computation using extended constraints

Several approaches for optical flow estimation use partial differential equations to model changes in image brightness throughout time. A commonly used equation is the so-called optical flow constraint (OFC), which assumes that the image brightness is stationary with respect to time. More recently, a different constraint referred to as the extended optical flow constraint (EOFC) has been introduced, which also contains the divergence of the flow field of image brightness. There is no agreement in the literature about which of these constraints provides the best estimation of the velocity field. Two new solutions for optical flow computation are proposed, which are based on an approximation of the constraint equations. The two techniques have been used with both EOFC and OFC constraint equations. Results achieved by using these solutions have been compared with several well-known computational methods for optical flow estimation in different motion conditions. Estimation errors have also been measured and compared for different types of motion.

A three-dimensional iconic environment for image database querying

Retrieval by contents of images from pictorial databases can be effectively performed through visual icon-based systems. In these systems, the representation of pictures with 2D strings, which are derived from symbolic projections, provides an efficient and natural way to construct iconic indexes for pictures and is also an ideal representation for the visual query. With this approach, retrieval is reduced to matching two symbolic strings. However, using 2D-string representations, spatial relationships between the objects represented in the image might not be exactly specified. Ambiguities arise for the retrieval of images of 3D scenes. In order to allow the unambiguous description of object spatial relationships, in this paper, following the symbolic projections approach, images are referred to by considering spatial relationships in the 3D imaged scene. A representation language is introduced that expresses positional and directional relationships between objects in three dimensions, still preserving object spatial extensions after projections. Iconic retrieval from pictorial databases with 3D interfaces is discussed and motivated. A system for querying by example with 3D icons, which supports this language, is also presented. >

A robust algorithm for optical flow estimation

Abstract Most of the existing methods for optical flow estimation are based on a constraint equation which is defined for each image pixel. This class of algorithms is usually called gradient-based. Due to the structure of the constraint equation, the problem is ill-posed, thus some solutions based on regularization have been proposed in the past. On the contrary, if other constraint equations can be found for the pixel under consideration or in its immediate neighborhood, the problem is not ill-posed and a solution can be found by solving determined or over-determined systems of equations, Following this reasoning, several algorithms for evaluating the optical flow have been proposed in the literature. Most of these over-determined systems of equations are solved by using least-squares techniques, In this paper, a new approach is presented in order to eliminate, or strongly reduce, the drawbacks of least-squares and regularization-based techniques. This is based on a modified version of the Combinatorial Hough Transform. A comparison is made between the results obtained with the new approach and those produced by the classical least-squares and regularization-based techniques.

Km4City ontology building vs data harvesting and cleaning for smart-city services

Presently, a very large number of public and private data sets are available from local governments. In most cases, they are not semantically interoperable and a huge human effort would be needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity, to allow the data reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big data volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to a smart-city ontology, called KM4City (Knowledge Model for City), and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users via specific applications of public administration and enterprises. The paper presents the process adopted to produce the ontology and the big data architecture for the knowledge base feeding on the basis of open and private data, and the mechanisms adopted for the data verification, reconciliation and validation. Some examples about the possible usage of the coherent big data knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection.