Translation validation was invented in the 90’s by Pnueli et al. as a technique to formally verify the correctness of code generators. Rather than certifying the code generator or exhaustively qualifying it, translation validators attempt to verify that program transformations preserve semantics. In this work, we adopt this approach to formally verify that the clock semantics and data dependence are preserved during the compilation of the Signal compiler. Translation validation is implemented for every compilation phase from the initial phase until the latest phase where the executable code is generated, by proving the transformation in each phase of the compiler preserves the semantics. We represent the clock semantics, the data dependence of a program and its transformed counterpart as first-order formulas which are called clock models and synchronous dependence graphs (SDGs), respectively. We then introduce clock refinement and dependence refinement relations which express the preservations of clock semantics and dependence, as a relation on clock models and SDGs, respectively. Our validator does not require any instrumentation or modification of the compiler, nor any rewriting of the source program.

The use of multi-core processors will become a trend in safety critical systems. For safe execution of multithreaded code, automatic code generation from formal specification is a desirable method. Signal, a synchronous language dedicated for the functional description of safety critical systems, provides soundness semantics for deterministic concurrency. Although sequential code generation of Signal has been implemented in Polychrony compiler, deterministic multi-threaded code generation strategy is still far from mature. Moreover, existing code generation methods use certain multi-thread library, which limits the cross platform executions. OpenMP is an application program interface (API) standard for parallel programming, supported by several mainstream compilers from different platforms. This paper presents a methodology translating Signal program to OpenMP-based multi-threaded C code. First, the intermediate representation of the core syntax of Signal using synchronous guarded actions is defined. Then, according to the compositional semantics of Signal equations, the Signal program is synthesized to dependency graph (DG). After parallel tasks are extracted from dependency graph, the Signal program can be finally translated into OpenMP-based C code which can be executed on multiple platforms.

Architecture analysis & design language (AADL) has been increasingly adopted in the design of embedded systems, and corresponding scheduling and formal verification have been well studied. However, little work takes code distribution and architecture exploration into account, particularly considering clock constraints, for distributed multi-processor systems. In this paper, we present an overview of our approach to handle these concerns, together with the associated toolchain, AADL-Polychrony-SynDEx. First, in order to avoid semantic ambiguities of AADL, the polychronous/multiclock semantics of AADL, based on a polychronous model of computation, is considered. Clock synthesis is then carried out in Polychrony, which bridges the gap between the polychronous semantics and the synchronous semantics of SynDEx. The same timing semantics is always preserved in order to ensure the correctness of the transformations between different formalisms. Code distribution and corresponding scheduling is carried out on the obtained SynDEx model in the last step, which enables the exploration of architectures originally specified in AADL. Our contribution provides a fast yet efficient architecture exploration approach for the design of distributed real-time and embedded systems. An avionic case study is used here to illustrate our approach.

This paper presents a new model of scenarios, dedicated to the specification and verification of system behaviours in the context of software product lines (SPL). We draw our inspiration from some techniques that are mostly used in the hardware community, and we show how they could be applied to the verification of software components. We point out the benefits of synchronous languages and models to bridge the gap between both worlds.

SIGNAL is a part of the synchronous languages family, which are broadly used in the design of safety-critical real-time systems such as avionics, space systems, and nuclear power plants. There exist several semantics for SIGNAL, such as denotational semantics based on traces (called trace semantics), denotational semantics based on tags (called tagged model semantics), operational semantics presented by structural style through an inductive definition of the set of possible transitions, operational semantics defined by synchronous transition systems (STS), etc. However, there is little research about the equivalence between these semantics.

In this work, we would like to prove the equivalence between the trace semantics and the tagged model semantics, to get a determined and precise semantics of the SIGNAL language. These two semantics have several different definitions respectively, we select appropriate ones and mechanize them in the Coq platform, the Coq expressions of the abstract syntax of SIGNAL and the two semantics domains, i.e., the trace model and the tagged model, are also given. The distance between these two semantics discourages a direct proof of equivalence. Instead, we transformthem to an intermediate model, which mixes the features of both the trace semantics and the tagged model semantics. Finally, we get a determined and precise semantics of SIGNAL.

Recently software crowdsourcing has become an emerging area of software engineering. Few papers have presented a systematic analysis on the practices of software crowdsourcing. This paper first presents an evaluation framework to evaluate software crowdsourcing projects with respect to software quality, costs, diversity of solutions, and competition nature in crowdsourcing. Specifically, competitions are evaluated by the min-max relationship from game theory among participants where one party tries to minimize an objective function while the other party tries to maximize the same objective function. The paper then defines a game theory model to analyze the primary factors in these minmax competition rules that affect the nature of participation as well as the software quality. Finally, using the proposed evaluation framework_this paper illustrates two crowdsourcing processes, Harvard-TopCoder and AppStori. The framework demonstrates the sharp contrasts between both crowdsourcing processes as participants will have drastic behaviors in engaging these two projects.

Web service choreography describes global models of service interactions among a set of participants. For an interaction to be executed, the participants must know the required channel(s) used in the interaction, otherwise the execution will get stuck. Since channels are composed dynamically, the initial channel set of each participant is often insufficient to meet the requirements. It is the responsibility of the participants to pass required channels owned (known) by one to others. Since service choreography may involve many participants and complex channel constraints, it is hard for designers to specify channel passing in a choreography exactly as required. We address the problem of checking whether a service choreography lacks channels or has redundant channels, and how to automatically generate channel passing based on interaction flows of the service choreography in the case of channel absence. Concretely, we propose a simple language Chorc, a channel interaction sub-language for modeling the channel passing aspect of service choreography. Based on the formal operational semantics of Chorc, the algorithms for static checking of service choreography and generating channel passing are also studied, and the complexity results of algorithms are discussed. Moreover, some illustrated service choreography examples are presented to show how to formalize and analyze service choreography with channel passing in Chorc.

In this paper we hybridize ant colony optimization (ACO) and river formation dynamics (RFD), two related swarm intelligence methods. In ACO, ants form paths (problem solutions) by following each other’s pheromone trails and reinforcing trails at best paths until eventually a single path is followed. On the other hand, RFD is based on copying how drops form rivers by eroding the ground and depositing sediments. In a rough sense, RFD can be seen as a gradient-oriented version of ACO. Several previous experiments have shown that the gradient orientation of RFD makes this method solve problems in a different way as ACO. In particular, RFD typically performs deepersearches, which in turn makes it find worse solutions than ACO in the first execution steps in general, though RFD solutions surpass ACO solutions after some more time passes. In this paper we try to get the best features of both worlds by hybridizing RFD and ACO. We use a kind of ant-drophybrid and consider both pheromone trails and altitudes in the environment. We apply the hybrid method, as well as ACO and RFD, to solve two NP-hard problems where ACO and RFD fit in a different manner: the traveling salesman problem (TSP) and the problem of the minimum distances tree in a variable-cost graph (MDV). We compare the results of each method and we analyze the advantages of using the hybrid approach in each case.

Graph-based dimensionality reduction (DR) methods have been applied successfully in many practical problems, such as face recognition, where graphs play a crucial role in modeling the data distribution or structure. However, the ideal graph is, in practice, difficult to discover. Usually, one needs to construct graph empirically according to various motivations, priors, or assumptions; this is independent of the subsequent DR mapping calculation. Different from the previous works, in this paper, we attempt to learn a graph closely linked with the DR process, and propose an algorithm called dimensionality reduction with adaptive graph (DRAG), whose idea is to, during seeking projection matrix, simultaneously learn a graph in the neighborhood of a prespecified one. Moreover, the pre-specified graph is treated as a noisy observation of the ideal one, and the square Frobenius divergence is used to measure their difference in the objective function. As a result, we achieve an elegant graph update formula which naturally fuses the original and transformed data information. In particular, the optimal graph is shown to be a weighted sum of the pre-defined graph in the original space and a new graph depending on transformed space. Empirical results on several face datasets demonstrate the effectiveness of the proposed algorithm.

The dynamicity of available resources and network conditions, such as channel capacity and traffic characteristics, have posed major challenges to scheduling in wireless networks. Reinforcement learning (RL) enables wireless nodes to observe their respective operating environment, learn, and make optimal or near-optimal scheduling decisions. Learning, which is the main intrinsic characteristic of RL, enables wireless nodes to adapt to most forms of dynamicity in the operating environment as time goes by. This paper presents an extensive review on the application of the traditional and enhanced RL approaches to various types of scheduling schemes, namely packet, sleep-wake and task schedulers, in wireless networks, as well as the advantages and performance enhancements brought about by RL. Additionally, it presents how various challenges associated with scheduling schemes have been approached using RL. Finally, we discuss various open issues related to RL-based scheduling schemes in wireless networks in order to explore new research directions in this area. Discussions in this paper are presented in a tutorial manner in order to establish a foundation for further research in this field.

This paper proposes an efficient retrieval approach for iris using local features. The features are extracted from segmented iris image using scale invariant feature transform (SIFT). The keypoint descriptors extracted from SIFT are clustered into m groups using k-means. The idea is to perform indexing of keypoints based on descriptor property. During database indexing phase, k-d tree k-dimensional tree is constructed for each cluster center taken from N iris images. Thus for m clusters, m such k-d trees are generated denoted as t_i, where 1≤i ≤m. During the retrieval phase, the keypoint descriptors from probe iris image are clustered into m groups and ith cluster center is used to traverse corresponding t_i for searching. k nearest neighbor approach is used, which finds p neighbors from each tree (t_i) that falls within certain radius r centered on the probe point in k-dimensional space. Finally, p neighbors from m trees are combined using union operation and top S matches (S ⊆ (m× p)) corresponding to query iris image are retrieved. The proposed approach has been tested on publicly available databases and outperforms the existing approaches in terms of speed and accuracy.

Developments in multimedia technologies have paved way for the storage of huge collections of video documents on computer systems. It is essential to design tools for content-based access to the documents, so as to allow an efficient exploitation of these collections. Content based analysis provides a flexible and powerfulway to access video data when compared with the other traditional video analysis techniques. The area of content based video indexing and retrieval (CBVIR), focusing on automating the indexing, retrieval and management of video, has attracted extensive research in the last decade. CBVIR is a lively area of research with enduring acknowledgments from several domains. Herein a vital assessment of contemporary researches associated with the content-based indexing and retrieval of visual information. In this paper, we present an extensive review of significant researches on CBVIR. Concise description of content based video analysis along with the techniques associated with the content based video indexing and retrieval is presented.