Functionality-specific vulnerabilities, which mainly occur in Application Programming Interfaces (APIs) with specific functionalities, are crucial for software developers to detect and avoid. When detecting individual functionality-specific vulnerabilities, the existing two categories of approaches are ineffective because they consider only the API bodies and are unable to handle diverse implementations of functionality-equivalent APIs. To effectively detect functionality-specific vulnerabilities, we propose APISS, the first approach to utilize API doc strings and signatures instead of API bodies. APISS first retrieves functionality-equivalent APIs for APIs with existing vulnerabilities and then migrates Proof-of-Concepts (PoCs) of the existing vulnerabilities for newly detected vulnerable APIs. To retrieve functionality-equivalent APIs, we leverage a Large Language Model for API embedding to improve the accuracy and address the effectiveness and scalability issues suffered by the existing approaches. To migrate PoCs of the existing vulnerabilities for newly detected vulnerable APIs, we design a semi-automatic schema to substantially reduce manual costs. We conduct a comprehensive evaluation to empirically compare APISS with four state-of-the-art approaches of detecting vulnerabilities and two state-of-the-art approaches of retrieving functionality-equivalent APIs. The evaluation subjects include 180 widely used Java repositories using 10 existing vulnerabilities, along with their PoCs. The results show that APISS effectively retrieves functionality-equivalent APIs, achieving a Top-1 Accuracy of 0.81 while the best of the baselines under comparison achieves only 0.55. APISS is highly efficient: the manual costs are within 10 minutes per vulnerability and the end-to-end runtime overhead of testing one candidate API is less than 2 hours. APISS detects 179 new vulnerabilities and receives 60 new CVE IDs, bringing high value to security practice.
Abstract In this article, we review special features of Gwyddion—a modular, multiplatform, open-source software for scanning probe microscopy data processing, which is available at http://gwyddion.net/. We describe its architecture with emphasis on modularity and easy integration of the provided algorithms into other software. Special functionalities, such as data processing from non-rectangular areas, grain and particle analysis, and metrology support are discussed as well. It is shown that on the basis of open-source software development, a fully functional software package can be created that covers the needs of a large part of the scanning probe microscopy user community.
ERPLAB toolbox is a freely available, open-source toolbox for processing and analyzing event-related potential (ERP) data in the MATLAB environment. ERPLAB is closely integrated with EEGLAB, a popular open-source toolbox that provides many EEG preprocessing steps and an excellent user interface design. ERPLAB adds to EEGLAB's EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others. ERPLAB also provides robust tools for averaging EEG segments together to create averaged ERPs, for creating difference waves and other recombinations of ERP waveforms through algebraic expressions, for filtering and re-referencing the averaged ERPs, for plotting ERP waveforms and scalp maps, and for quantifying several types of amplitudes and latencies. ERPLAB's tools can be accessed either from an easy-to-learn graphical user interface or from MATLAB scripts, and a command history function makes it easy for users with no programming experience to write scripts. Consequently, ERPLAB provides both ease of use and virtually unlimited power and flexibility, making it appropriate for the analysis of both simple and complex ERP experiments. Several forms of documentation are available, including a detailed user's guide, a step-by-step tutorial, a scripting guide, and a set of video-based demonstrations.
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oTree is an open-source and online software for implementing interactive experiments in the laboratory, online, the field or combinations thereof. oTree does not require installation of software on subjects’ devices; it can run on any device that has a web browser, be that a desktop computer, a tablet or a smartphone. Deployment can be internet-based without a shared local network, or local-network-based even without internet access. For coding, Python is used, a popular, open-source programming language. www.oTree.org provides the source code, a library of standard game templates and demo games which can be played by anyone.
Open innovation is a powerful framework encompassing the generation, capture, and employment of intellectual property at the firm level. We identify three fundamental challenges for firms in applying the concept of open innovation: finding creative ways to exploit internal innovation, incorporating external innovation into internal development, and motivating outsiders to supply an ongoing stream of external innovations. This latter challenge involves a paradox, why would firms spend money on R&D efforts if the results of these efforts are available to rival firms? To explore these challenges, we examine the activity of firms in open-source software to support their innovation strategies. Firms involved in open-source software often make investments that will be shared with real and potential rivals. We identify four strategies firms employ – pooled R&D/product development, spinouts, selling complements and attracting donated complements – and discuss how they address the three key challenges of open innovation. We conclude with suggestions for how similar strategies may apply in other industries and offer some possible avenues for future research on open innovation.
Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies.
Microarrays have emerged as the premier tool for studying gene expression on a genomic scale. Advances in the precision of array printers and scanners as well as improved laboratory protocols (11) allow for assays of tremendous complexity and scope. Scientists seeking to harness the potential of this technique are often challenged by the large quantities of data produced. Well-designed, user-friendly software is the key to tracking, integrating, qualifying, and ultimately deriving scientific insight from the experimental results. In support of our ongoing work in microarray analysis of gene expression, we developed a suite of software that allow users in the laboratory to capture, manage, and analyze effectively data from DNA microarray experiments. The TM4 suite of tools consist of four major applications, Microarray Data Manager (MADAM), TIGR_Spotfinder, Microarray Data Analysis System (MIDAS), and Multiexperiment Viewer (MeV), as well as a Minimal Information About a Microarray Experiment (MIAME)-compliant MySQL database, all of which are freely available to the scientific research community at http://www.tigr.org/software. Although these software tools were developed for spotted two-color arrays, many of the components can be easily adapted to work with single-color formats such as filter arrays and GeneChips (Affymetrix, Santa Clara, CA, USA). Three of the TM4 applications, MADAM, MIDAS, and MeV, were developed in Java and have been tested on Microsoft Windows, Linux , Unix , and MacOS X platforms; TIGR Spotfinder was written in C/C++ and runs only on Windows systems. The TM4 software system represents a comprehensive, extensible, open-source, and freely available collection of tools that we believe will be of use to a wide range of laboratories conducting microarray experiments. We further hope that by providing source code along with the executable software, we can encourage others to develop new analysis methods and utilities that will further enhance the capabilities of this software system.
mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
Over the last few decades, researchers have developed a number of empirical and theoretical models for the correlation and prediction of the thermophysical properties of pure fluids and mixtures treated as pseudo-pure fluids. In this paper, a survey of all the state-of-the-art formulations of thermophysical properties is presented. The most-accurate thermodynamic properties are obtained from multiparameter Helmholtz-energy-explicit-type formulations. For the transport properties, a wider range of methods has been employed, including the extended corresponding states method. All of the thermophysical property correlations described here have been implemented into CoolProp, an open-source thermophysical property library. This library is written in C++, with wrappers available for the majority of programming languages and platforms of technical interest. As of publication, 110 pure and pseudo-pure fluids are included in the library, as well as properties of 40 incompressible fluids and humid air. The source code for the CoolProp library is included as an electronic annex.
In the present article, we introduce OpenSesame, a graphical experiment builder for the social sciences. OpenSesame is free, open-source, and cross-platform. It features a comprehensive and intuitive graphical user interface and supports Python scripting for complex tasks. Additional functionality, such as support for eyetrackers, input devices, and video playback, is available through plug-ins. OpenSesame can be used in combination with existing software for creating experiments.
BACKGROUND: Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface. RESULTS: With data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC. CONCLUSIONS: pROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.
Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similar in spirit to existing grid and HPC resource management and programming systems. These types of systems offer a new programming target for scalable application developers and have gained popularity over the past few years. However, most cloud computing systems in operation today are proprietary, rely upon infrastructure that is invisible to the research community, or are not explicitly designed to be instrumented and modified by systems researchers. In this work, we present Eucalyptus - an open-source software framework for cloud computing that implements what is commonly referred to as infrastructure as a service (IaaS); systems that give users the ability to run and control entire virtual machine instances deployed across a variety physical resources. We outline the basic principles of the Eucalyptus design, detail important operational aspects of the system, and discuss architectural trade-offs that we have made in order to allow EUCALYPTUS to be portable, modular and simple to use on infrastructure commonly found within academic settings. Finally, we provide evidence that EUCALYPTUS enables users familiar with existing grid and HPC systems to explore new cloud computing functionality while maintaining access to existing, familiar application development software and grid middleware.
We report on the implementation of a tool for the analysis of second-order elastic stiffness tensors, provided with both an open-source Python module and a standalone online application allowing the visualization of anisotropic mechanical properties. After describing the software features, how we compute the conventional elastic constants and how we represent them graphically, we explain our technical choices for the implementation. In particular, we focus on why a Python module is used to generate the HTML web page with embedded Javascript for dynamical plots.
Qiskit is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. https://qiskit.org
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We present ORB-SLAM2, a complete simultaneous localization and mapping (SLAM) system for monocular, stereo and RGB-D cameras, including map reuse, loop closing, and relocalization capabilities. The system works in real time on standard central processing units in a wide variety of environments from small hand-held indoors sequences, to drones flying in industrial environments and cars driving around a city. Our back-end, based on bundle adjustment with monocular and stereo observations, allows for accurate trajectory estimation with metric scale. Our system includes a lightweight localization mode that leverages visual odometry tracks for unmapped regions and matches with map points that allow for zero-drift localization. The evaluation on 29 popular public sequences shows that our method achieves state-of-the-art accuracy, being in most cases the most accurate SLAM solution. We publish the source code, not only for the benefit of the SLAM community, but with the aim of being an out-of-the-box SLAM solution for researchers in other fields.
The newly developed GSAS-II software is a general purpose package for data reduction, structure solution and structure refinement that can be used with both single-crystal and powder diffraction data from both neutron and X-ray sources, including laboratory and synchrotron sources, collected on both two- and one-dimensional detectors. It is intended that GSAS-II will eventually replace both the GSAS and the EXPGUI packages, as well as many other utilities. GSAS-II is open source and is written largely in object-oriented Python but offers speeds comparable to compiled code because of its reliance on the Python NumPy and SciPy packages for computation. It runs on all common computer platforms and offers highly integrated graphics, both for a user interface and for interpretation of parameters. The package can be applied to all stages of crystallographic analysis for constant-wavelength X-ray and neutron data. Plans for considerable additional development are discussed.
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This article presents ORB-SLAM3, the first system able to perform visual, visual-inertial and multimap SLAM with monocular, stereo and RGB-D cameras, using pin-hole and fisheye lens models. The first main novelty is a tightly integrated visual-inertial SLAM system that fully relies on maximuma posteriori(MAP) estimation, even during IMU initialization, resulting in real-time robust operation in small and large, indoor and outdoor environments, being two to ten times more accurate than previous approaches. The second main novelty is a multiple map system relying on a new place recognition method with improved recall that lets ORB-SLAM3 survive to long periods of poor visual information: when it gets lost, it starts a new map that will be seamlessly merged with previous maps when revisiting them. Compared with visual odometry systems that only use information from the last few seconds, ORB-SLAM3 is the first system able to reuse in all the algorithm stages all previous information from high parallax co-visible keyframes, even if they are widely separated in time or come from previous mapping sessions, boosting accuracy. Our experiments show that, in all sensor configurations, ORB-SLAM3 is as robust as the best systems available in the literature and significantly more accurate. Notably, our stereo-inertial SLAM achieves an average accuracy of 3.5 cm in the EuRoC drone and 9 mm under quick hand-held motions in the room of TUM-VI dataset, representative of AR/VR scenarios. For the benefit of the community we make public the source code.