Miracle-dz/UniFAR-FTUs huggingface dataset:
Case studies and tools for contract specifications

Contracts are a popular tool for specifying the functional behavior of software. This paper characterizes the contracts that developers write, the contracts that developers could write, and how a developer reacts when shown the difference. This paper makes three research contributions based on an investigation of open-source projects' use of Code Contracts. First, we characterize Code Contract usage in practice. For example, approximately three-fourths of the Code Contracts are basic checks for the presence of data. We discuss similarities and differences in usage across the projects, and we identify annotation burden, tool support, and training as possible explanations based on developer interviews. Second, based on contracts automatically inferred for four of the projects, we find that developers underutilize contracts for expressing state updates, object state indicators, and conditional properties. Third, we performed user studies to learn how developers decide which contracts to enforce. The developers used contract suggestions to support their existing use cases with more expressive contracts. However, the suggestions did not lead them to experiment with other use cases for which contracts are better-suited. In support of the research contributions, the paper presents two engineering contributions: (1) Celeriac, a tool for generating traces of . NET programs compatible with the Daikon invariant detection tool, and (2) Contract Inserter, a Visual Studio add-in for discovering and inserting likely invariants as Code Contracts.
A Latent Variable Bayesian Approach to Spatial Clustering with Background Noise

We propose a finite mixture model for clustering of the spatial data patterns. The model is based on the spatial distances between the data locations in such a way that both the distances of the points to the cluster centers and the distances of a given point to its neighbors within a defined window are involved in the model. Nevertheless, we take into consideration the background noise as well in the model. We resort to Classification Expectation-Maximization (CEM) algorithm for both estimating the parameters and clustering the data points. We test the algorithm on some simulated data sets with dierent background noise levels and apply it to a real earthquake data recorded in Kashmir in 2005.
Star Formation and Selective Dust Extinction in Luminous Starburst Galaxies

We investigate the star formation and dust extinction properties of very luminous infrared galaxies whose spectra display a strong Hδ line in absorption and a moderate [O II] emission [e(a) spectrum]. This spectral combination has been suggested to be a useful method to identify dusty starburst galaxies at any redshift on the basis of optical data alone. We compare the average e(a) optical spectrum with synthetic spectra that include both the stellar and the nebular contribution, allowing dust extinction to affect differentially the stellar populations of different ages. We find that reproducing the e(a) spectrum requires the youngest stellar generations to be significantly more extinguished by dust than older stellar populations and implies a strong ongoing star formation activity at a level higher than in quiescent spirals. A model fitting the optical spectrum does not necessarily produce the observed FIR luminosity, and this can be explained by the existence of stellar populations which are practically obscured at optical wavelengths. Models in which dust and stars are uniformly mixed yield a reddening of the emerging emission lines which is too low compared to observations: additional foreground reddening is required.
Inductance evaluation of fractional slot permanent magnet synchronous motors with non-overlappingwinding by analytical approaches

Fractional slot permanent magnet synchronous machines with non-overlapping winding (FSPMSM) also known as tooth coil winding permanent synchronous machines (TCW PMSM) have gained intensive attention during the latest decade. Therefore, their design methods are constantly developed and improved. Numerical solution, i.e. finite element analysis (FEA), is still computationally heavy and time consuming, which makes it problematic to use this method in an optimization process. For this reason it is advantageous to use an analytical design method, for searching a design, which satisfies the needed characteristics of a PMSM, during the optimization process.
Using OWL to Construct and Parse Ontology for Learning Resources in Network Education Environment

With the development of information technology, e-Learning has become a sort of important studying style. Meanwhile, a great deal of learning resources have been created and released on the web. How to better label learning resources for sharing within different platforms and different systems is an important aspect. This paper proposes an ontology model based on OWL and illustrates it with an example of music course.
An Approach for Intrusion Detection Using Novel Gaussian Based Kernel Function

Software Security and Intrusion Detection need to be dealt at three levels Network, Host level and Application level. In this paper the major objective is to design and analyze the suitability of Gaussian similarity measure for intrusion detection. The objective is to use this as a distance measure to find the distance between any two data samples of training set such as DARPA Data Set, KDD Data Set. This major objective is to use this measure as a distance metric when applying k-means algorithm. The novelty of this approach is making use of the proposed distance function as part of k-means algorithm so as to obtain disjoint clusters. This is followed by a case study, which demonstrates the process of Intrusion Detection. The proposed similarity has fixed upper and lower bounds.
Statistical skull models from 3D X-ray images

We present 2 statistical models of the skull and mandible built upon an elastic registration method of 3D meshes. The aim of this work is to relate degrees of freedom of skull anatomy, as static relations are of main interest for anthropology and legal medicine. Statistical models can effectively provide reconstructions together with statistical precision. In our applications, patient-specific meshes of the skull and the mandible are high-density meshes, extracted from 3D CT scans. All our patient-specific meshes are registrated in a subject-shared reference system using our 3D-to-3D elastic matching algorithm. Registration is based upon the minimization of a distance between the high density mesh and a shared low density mesh, defined on the vertexes, in a multi resolution approach. A Principal Component analysis is performed on the normalised registrated data to build a statistical linear model of the skull and mandible shape variation. The accuracy of the reconstruction is under the millimetre in the shape space (after rigid registration). Reconstruction errors for Scan data of tests individuals are below registration noise. To take in count the articulated aspect of the skull in our model, Kernel Principal Component Analysis is applied, extracting a non-linear parameter associated with mandible position, therefore building a statistical articulated 3D model of the skull.
Telomerase Template Antagonist GRN163L Disrupts Telomere Maintenance, Tumor Growth, and Metastasis of Breast Cancer

Purpose: Maintenance of telomeres by telomerase is critical for the continuing proliferation of most advanced cancer cells. Telomerase activity has been detected in the vast majority of cancer cells but not most normal cells, making the enzyme an attractive target for anticancer therapy. The aim of this study was to address the breast cancer translational potential of the novel telomerase inhibitor, GRN163L. Experimental Design: In the present study, we investigated the effects of GRN163L treatment on a panel of breast cancer cells representing different tumor subtypes with varying genetic backgrounds, including ER+, ER−, HER2+, BRCA1 mutant breast tumor cells as well as doxorubicin-resistant cancer cells. To investigate the in vivo effects of GRN163L, we employed a breast cancer xenograft and metastasis model that simulates a clinical situation in which a patient arrives with a primary tumor that may be then treated or surgically removed. Results: GRN163L effectively inhibited telomerase activity in a dose-dependent fashion in all breast cancer cell lines resulting in progressive telomere shortening. A mismatch control oligonucleotide showed no effect on telomerase activity and GRN163L did not significantly affect telomere shortening in normal human mammary epithelial cells or in endothelial cells. Breast cancer cells that exhibited telomerase inhibition also exhibited significant reduction in colony formation and tumorigenicity. Furthermore, GRN163L suppressed tumor growth and lung metastases (P = 0.017) of MDA-MB-231 cells in vivo after 4 weeks of treatment. Conclusions: These results show in vivo effectiveness of GRN163L in breast cancer and support its promising clinical potential for breast cancer treatment.
Observations of the mesospheric semi-annual oscillation (MSAO) in water vapour by Odin/SMR

Mesospheric water vapour measurements taken by the SMR instrument aboard the Odin satellite between 2002 and 2006 have been analysed with focus on the mesospheric semi-annual circulation in the tropical and subtropical region. This analysis provides the first complete picture of mesospheric SAO in water vapour, covering altitudes above 80 km where previous studies were limited. Our analysis shows a clear semi- annual variation in the water vapour distribution in the entire altitude range between 65 km and 100 km in the equatorial area. Maxima occur near the equinoxes below 75 km and around the solstices above 80 km. The phase reversal occurs in the small layer in-between, consistent with the downward propagation of the mesospheric SAO in the zonal wind in this altitude range. The SAO amplitude exhibits a double peak structure in the equatorial region, with maxima at about 75 km and 81 km. The observed amplitudes show higher values than an earlier analysis based on UARS/HALOE data. The upper peak amplitude remains relatively constant with latitude. The lower peak amplitude decreases towards higher latitudes, but recovers in the Southern Hemisphere subtropics. On the other hand, the annual variation is much more prominent in the Northern Hemisphere subtropics. Furthermore, higher volume mixing ratios during summer and lower values during winter are observed in the Northern Hemisphere subtropics, as compared to the corresponding latitude range in the Southern Hemisphere.
Design and implementation of a network-link emulator

Network-link emulator is one of the key software utilities for network emulation. After a discussion of principles to emulating a specified network-link, this paper gives control models for bandwidth, transmission delay and packet loss rate emulation. After that, three implementing schemes for the emulator are presented and discussed, and the scheme based on Netfilter is chosen finally. Based on the scheme, the emulator is implemented, and its organization is presented. Finally, throughputs and accuracy of the emulator are tested and results are discussed.
An Improved K-Means Algorithm Based on Multiple Feature Points

K-means algorithm is one of the most popular clustering algorithms. However, it is sensitive to initialized partition and the circular dataset. To attack this problem, this paper introduced an improved k-means algorithm based on multiple feature points. The algorithm selects a number of feature points as cluster centroids unlike the traditional algorithm which only uses one centroid. In addition, the algorithm calculates the weighted distance to distribute the data point and to build the new feature points set. Theoretical analysis shows that the improved algorithm and the traditional algorithm are in the same order of magnitude. The experimental results on artificial data show that the improved algorithm is better than the traditional algorithm. Experiment on real data gives appropriate parameters.
Generation of nonclassical motional states of a trapped atom.

We report the creation of thermal, Fock, coherent, and squeezed states of motion of a harmonically bound {sup 9}Be{sup +} ion. The last three states are coherently prepared from an ion which has been initially laser cooled to the zero point of motion. The ion is trapped in the regime where the coupling between its motional and internal states, due to applied (classical) radiation, can be described by a Jaynes-Cummings-type interaction. With this coupling, the evolution of the internal atomic state provides a signature of the number state distribution of the motion. {copyright} {ital 1996 The American Physical Society. }
Comparative analysis of two operational amplifier topologies for a 40MS/s 12-bit pipelined ADC in 0.35μm CMOS

This paper describes a comparative analysis between two topologies of operational amplifiers to design a 40 MS/s 12-bit pipeline analog to digital converter (ADC). The analysis includes AC and transient simulation to select the proper topology. This ADC is implemented in a 0.35 mum AMS CMOS technology with 3.3 V single power supply. The capacitors and selected operational amplifiers were scaled for low power dissipation. All analog components of this pipeline ADC are fully differential, as there are dynamic comparators, analog multiplexers and operational amplifiers with gain boosting.
Recursive Fuzzy Granulation for Gene Subsets Extraction and Cancer Classification

A typical microarray gene expression dataset is usually both extremely sparse and imbalanced. To select multiple highly informative gene subsets for cancer classification and diagnosis, a new fuzzy granular support vector machine-recursive feature elimination algorithm (FGSVM-RFE) is designed in this paper. As a hybrid algorithm of statistical learning, fuzzy clustering, and granular computing, the FGSVM-RFE separately eliminates irrelevant, redundant, or noisy genes in different granules at different stages and selects highly informative genes with potentially different biological functions in balance. Empirical studies on three public datasets demonstrate that the FGSVM-RFE outperforms state-of-the-art approaches. Moreover, the FGSVM-RFE can extract multiple gene subsets on each of which a classifier can be modeled with 100% accuracy. Specifically, the independent testing accuracy for the prostate cancer dataset is significantly improved. The previous best result is 86% with 16 genes and our best result is 100% with only eight genes. The identified genes are annotated by Onto-Express to be biologically meaningful.
Using CSP for coordinating undo-based collaborative applications

Operational Transformation (OT) is a coordination approach used for supporting optimistic replication in distributed collaborative applications, where many users cooperatively manipulate replicated shared objects such as textual or multimedia documents. It allows users to concurrently update the shared data and exchange their updates in any order since the consistency of all replicas is ensured in all cases. In this context, it is desirable to undo some erroneous modifications for recovering the last correct state. This task is more tricky when out-of-order executions are considered. To avoid untimely and useless cancellations, a selective undo scheme based on OT approach is used to cancel the effect of any logged operation. Nevertheless, combining OT and undo approaches is a challenging problem since the process of doing and undoing should be reversible while preserving the data consistency. In this paper, we propose a theoretical study for this combination by formulating the undo problem as a Constraint Satisfaction Problem (CSP). For this purpose, we define a set of constraints to be fulfilled by the transformation function so that undoability is correctly managed. These constraints allow us to reduce the search space and output a reasonable number of transformation functions. The study of this output shows that commutativity somehow impacts on undoability. As the main result, to correctly manipulate undo for a shared object, we prove that the set of operations of size n • 4 must be totally commutative, while only a subset of commutative operations is necessary otherwise. As such, this work opens new perspectives for the design of safe OT-based collaborative applications using CSP methods.
Creating User Models from Web Logs

This paper describes the ground work we have done in our goal to create an adaptive educational website. We are interested in creating rich user models from a variety of sources. One important source of such user models can be based upon data from the time the user spends at a web page with an audio content. We report basic analyses of such logs from a course whose lectures are delivered as on-line audio associated with web pages.
Security Enhanced Authentication and Key Agreement Protocol for LTE/SAE Network

The 3rd Generation Partnership (3GPP) standard is developing System Architecture Evolution(SAE)/Long Term Evolution(LTE) architecture for the next generation mobile communication system. In the LTE/SAE architecture, EPS AKA(Evolved Packet System Authentication and Key Agreement) procedure is used to provide mutual authentication between the user and the network. However the EPS AKA has several vulnerabilities such as disclosure of user identity, man-in-middle attack, etc. Therefore, this paper analyzes the deficiencies of the EPS AKA, and proposes a Security Enhanced Authentication and Key agreement (SE-EPS AKA) based on Wireless Public Key Infrastructure (WPKI). Then, the new SE-EPS AKA has been proved with the formal verification method, and the proof result shows that the SE-EPS AKA can satisfy the security and efficiency propoerties in the LTE/SAE architecture.
Modelling the Adaptability of Biological Systems

There are approximately two million species of organisms in estimation today, each possessing different pref- erences or tolerance towards a multitude of factors; these factors include mainly competition between species and envi- ronmental conditions. From a computer modelling point of view, these biological systems could be difficult to implement. However, if a unified formula could be found to measure all of the factors against the preferences of each life form, its po- tentials for modelling open systems that require multiple external input variables could be significant. This article explores a formula and variations of it as applied first to measure static (immobile) systems - vegetation, which requires multiple variables for determining its fitness, and then to a pilot study exploring its use for dynamic (mobile) systems. Experiments suggest that using the formula and variations of it on vegetation communities yielded distribution patterns similar to those in natural landscapes. Experiments using the formula in the pilot study showed characteristics of emergent behaviours as each dynamic system seeks its own ecological niche. The findings provided evidence that the formula could be extended for modelling a wide variety of open biological systems. Abstract: There are millions of species of organisms in estimation today, each possessing different preferences or tolerance towards a multitude of factors; these factors include mainly competition between species and environmental conditions. From a computer modelling point of view, these biological systems could be difficult to implement. However, if a unified formula could be found to measure all of the factors against the preferences of each life form, its potentials for modelling open systems that require multiple external input variables could be significant. This article explores a formula and variations of it as applied first to measure sessile systems - vegetation, which requires multiple variables for determining its fitness, and then to a pilot study exploring its use for dynamic vagile systems. Experiments suggest that using the formula and variations of it on vegetation communities yielded distribution patterns similar to those in natural landscapes. Experiments using the formula in the pilot study showed characteristics of emergent behaviours as each dynamic system seeks its own ecological niche. The findings provided evidence that the formula could be extended for modelling a wide variety of open biological systems.
Static Analysis of File-Processing Programs using File Format Specifications

Programs that process data that reside in files are widely used in varied domains, such as banking, healthcare, and web-traffic analysis. Precise static analysis of these programs in the context of software verification and transformation tasks is a challenging problem. Our key insight is that static analysis of file-processing programs can be made more useful if knowledge of the input file formats of these programs is made available to the analysis. We propose a generic framework that is able to perform any given underlying abstract interpretation on the program, while restricting the attention of the analysis to program paths that are potentially feasible when the program's input conforms to the given file format specification. We describe an implementation of our approach, and present empirical results using real and realistic programs that show how our approach enables novel verification and transformation tasks, and also improves the precision of standard analysis problems.
Implementing Tabled Abduction in Logic Programs

Abduction has been on the back burner in logic programming, as abduction can be too difficult to implement, and costly to perform, in particular if abductive solutions are not tabled. If they become tabled, then abductive solutions can be reused, even from one abductive context to another. On the other hand, current Prolog systems, with their tabling mechanisms, are mature enough to facilitate the introduction of tabling abductive solutions (tabled abduction) into them. We recently proposed and published a conception of tabled abduction with its prototype, TABDUAL, implemented in XSB-Prolog. We detail here subsequent progress that has been made on the implementation aspect of TABDUAL, towards its more practical use.
Global ecological success of Thalassoma fishes in extreme coral reef habitats

Abstract Phenotypic adaptations can allow organisms to relax abiotic selection and facilitate their ecological success in challenging habitats, yet we have relatively little data for the prevalence of this phenomenon at macroecological scales. Using data on the relative abundance of coral reef wrasses and parrotfishes (f. Labridae) spread across three ocean basins and the Red Sea, we reveal the consistent global dominance of extreme wave‐swept habitats by fishes in the genus Thalassoma, with abundances up to 15 times higher than any other labrid. A key locomotor modification—a winged pectoral fin that facilitates efficient underwater flight in high‐flow environments—is likely to have underpinned this global success, as numerical dominance by Thalassoma was contingent upon the presence of high‐intensity wave energy. The ecological success of the most abundant species also varied with species richness and the presence of congeneric competitors. While several fish taxa have independently evolved winged pectoral fins, Thalassoma appears to have combined efficient high‐speed swimming (to relax abiotic selection) with trophic versatility (to maximize exploitation of rich resources) to exploit and dominate extreme coral reef habitats around the world.