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Sequence database search engines are bioinformatics algorithms that identify peptides from tandem mass spectra using a reference protein sequence database. Two decades of development, notably driven by advances in mass spectrometry, have provided scientists with more than 30 published search engines, each with its own properties. In this review, we present the common paradigm behind the different implementations, and its limitations for modern mass spectrometry datasets. We also detail how the search engines attempt to alleviate these limitations, and provide an overview of the different software frameworks available to the researcher. Finally, we highlight alternative approaches for the identification of proteomic mass spectrometry datasets, either as a replacement for, or as a complement to, sequence database search engines. acceptedVersion

There are many settings where individual person data (IPD) are not available, due to privacy or technical reasons, and one must work with IPD proxies, such as summary statistics, to approximate original IPD inferences, that is, the results of statistical analyses that would ideally have been performed on individual-level data. For instance, in a distributed computing setting, as implemented in the DataSHIELD software framework, different centers can only share IPD proxies to obtain pooled IPD inferences. Such privacy requirements limit the scope of statistical investigation. For example, it can be challenging to perform between-center random-effect regression models. To increase modeling freedom we propose a method that only uses simple nondisclosive summaries of the original IPD as input, such as empirical marginal moments and correlation matrices, and generates artificial data compatible with those summary features. Specifically, data are generated from a Gaussian copula with marginal and joint components specified by the above summaries. The goal is to reproduce original IPD features in the artificial data, such that original IPD inferences are recovered from the artificial data. In an application example, and through simulations, we show that we can recover estimates of a multivariable IPD random-effect logistic regression, from artificial data generated via the Gaussian copula using the above IPD summaries, suggesting the proposed approach provides a generally applicable strategy for distributed computing settings with data protection constraints.

Although known to be very powerful, the widespread application of model‐based techniques is still significantly hampered in the area of bio‐processes. Reasons for this situation can be found along the whole chain to set up and implement such approaches. In a time‐consuming step, models are typically hand‐crafted. Whether alternatives of better models exist to actually fulfill the final goals is undocumented, most often even unknown. In a next step, model‐based process control methods are hand‐coded in an error‐prone procedure. For many of these methods given in the literature, only simulation studies are shown, leaving the interested reader with the unanswered question whether the implementation of a specific method in a real process is viable. As the potentially time‐consuming implementation of such a method presents a risk for a rapid process development, promising candidates may be overlooked. To remediate this unsatisfactory situation, a combination of theoretical methods and information technology is proposed here. By an exemplarily realized software tool, it is shown how such an environment helps to promote model‐based optimization, supervision, and control of bio‐processes and allows for an inexpensive test of new ideas as well in real‐life experiments. The contribution concentrates on an overview of a possible software architecture with respect to necessary methods and a meaningful information strategy, highlighting some of the more crucial building blocks. Experimental results exploiting parts of the proposed methods are given for a yeast strain synthesizing a product of industrial interest.

Service-oriented architecture is becoming a major software framework for complex application and it can be dynamically and flexibly composed by integrating existing component web services provided by different providers with standard protocols. The rapid introduction of new web services into a dynamic business environment can adversely affect the service quality and user satisfaction. Therefore, how to leverage, aggregate and make use of individual component's quality of service (QoS) information to derive the optimal QoS of the composite service which meets the needs of users is still an ongoing hot research problem. This study aims at reviewing the advance of the current state-of-the-art in technologies and inspiring the possible new ideas for web service selection and composition, especially with nature-inspired computing approaches. Firstly, the background knowledge of web services is presented. Secondly, various nature-inspired web selection and composition approaches are systematically reviewed and analysed for QoS-aware web services. Finally, challenges, remarks and discussions about QoS-aware web service composition are presented.

In this work we present PAROC, an integrated framework software platform for the development of explicit model predictive controllers, and we apply it to the intravenous anaesthesia process. First, we overview the main features of PAROC, including high-fidelity modelling, state-of-the-art multiparametric optimization techniques, explicit/multiparametric model predictive control strategies, and a closed loop validation step. We then apply PAROC to the anaesthesia process, in particular for the development of explicit/multiparametric model predictive controllers for the induction and maintenance phases of intravenous anaesthesia validated on a set of 12 patients.

Effectiveness in lab workflows—despite progresses made in automation and lab informatics—is often hindered by insufficient integration of devices and data. The iLAB software framework, a middleware connecting and integrating devices and data, provides a plugin architecture that can be adapted to individual lab environments. Integration of devices is preferably based on standardized data and communication protocols. In addition to device integration, process data and result data from different sources (e.g. readers) are converted to a standard format and administered by a powerful database for further processing. In this paper, the use of iLAB in a bioprocess development application is described. Process parameters and measured values of two high‐throughput bioreactor systems (96‐well plates and 10 mL reactor vessels) are collected in the iLAB database. Data from screening experiments and offline data are visualized, analyzed, and compared. A filter algorithm allows searching for matching parameters in experiments as well as the comparison of correlated datasets, independently from the used bioreactor system. The database model enables the consolidation of data, the transition from data to information, and a solid base for management decisions on enterprise level.

The use of two-stage stochastic optimization for the support of the solution of process design problems in the early phase of process development where the different potential elements of the production process can only be described with significant uncertainty is discussed. The first stage variables are the design decisions which are fixed after the process has been built, while the second stage variables are the operational parameters which can be adapted to the realization of the uncertainties. The application of the approach to the design of a hydroformylation process in a thermomorphic solvent system is demonstrated. The proposed designs which are computed using the software framework FSOpt are analyzed and compared using different graphic representations which provide insight into what the most important design decisions are. Finally, the experience with the proposed formulation and solution techniques and point out where further advances are needed is reviewed. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3404–3419, 2016

Cuby is a computational chemistry framework written in the Ruby programming language. It provides unified access to a wide range of computational methods by interfacing external software and it implements various protocols that operate on their results. Using structured input files, elementary calculations can be combined into complex workflows. For users, Cuby provides a unified and userfriendly way to automate their work, seamlessly integrating calculations carried out in different computational chemistry programs. For example, the QM/MM module allows combining methods across the interfaced programs and the builtin molecular dynamics engine makes it possible to run a simulation on the resulting potential. For programmers, it provides high-level, object-oriented environment that allows rapid development and testing of new methods and computational protocols. The Cuby framework is available for download at http://cuby4.molecular.cz. © 2016 Wiley Periodicals, Inc.

Knowledge transfer is a key function in software development. Software tool development is an important skills in the software engineering. However, generic teaching courses are hard to evaluate the integrated development skills from undergraduate students. This paper proposed a continuous collaboration model (CCM) and a view-based semi-automatic tool, OpenNeeds, develop and run as an Eclipse plug-in to proceed the functional requirements' analysis. These selected methods and tools include programming languages, markup language, information exchange standards, modeling language, model-view-controller (MVC) software framework, virtual machine handling, interface development environment, version control platform, knowledge management, software documentation, and software unit tests. The MVC tool can simply manipulate several requirement-related graphical components, such as mind view and use case view. The lateral thinking approach is adapted in grid view to assist in analyzing other potential requirements from the original ones. Subsequently, the source codes of this tool are opened and can be distributed via the Eclipse Public License from the OpenFoundry and Github repositories. There are three professors who come from two distinct colleges to share their learning experiences. Meanwhile, 26 and 27 college students attend this team in the first and second year, respectively. Professors can truly understand the fortes of the individual attendee through the attending performance and promote his/her merits in the future tasks. Further, their industrial practices and related outcomes might disclose that the proposed CCM is feasible and trustable in college environment, especially for the software development activities in the software engineering field. © 2015 Wiley Periodicals, Inc. Comput Appl Eng Educ 9999:1–13, 2015; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21679

In recent years, a plethora of approaches have been proposed to deal with the increasingly challenging task of multi-output regression. This study provides a survey on state-of-the-art multi-output regression methods, that are categorized as problem transformation and algorithm adaptation methods. In addition, we present the mostly used performance evaluation measures, publicly available data sets for multi-output regression real-world problems, as well as open-source software frameworks. WIREs Data Mining Knowl Discov 2015, 5:216-233. doi: 10.1002/widm.1157

Summary Three persistent common problems in satellite ground control software are obsolescence, lack of desired features and flexibilities, and endless software bug fixing. The obsolescence problem occurs when computer and ground equipment hardware become obsolete, usually after only one-third into the satellite mission lifetime. The software needs to be updated to accommodate changes on the hardware side, requiring significant work of satellite operators to test, verify, and validate these software updates. Trying to help solve these problems, we have proposed an object-process methodology model and guidelines for developing satellite ground control software. The system makes use of a database-driven application and concepts of object-process orientation and modularity. In the new proposed framework, instead of coding each software function separately, the common base functions will be coded, and combining them in various ways will provide the different required functions. The formation and combination of these base functions will be governed by the main code, definitions, and database parameters. These design principles will make sure that the new software framework would provide satellite operators with the flexibility to create new features and enable software developer to find bugs quicker and fix them more effectively. Copyright © 2015 John Wiley & Sons, Ltd.

The use of Graphics Processing Units GPUs for high-performance computing has gained growing momentum in recent years. Unfortunately, GPU-programming platforms like Compute Unified Device Architecture CUDA are complex, user unfriendly, and increase the complexity of developing high-performance parallel applications. In addition, runtime systems that execute those applications often fail to fully utilize the parallelism of modern CPU-GPU systems. Typically, parallel kernels run entirely on the most powerful device available, leaving other devices idle. These observations sparked research in two directions: 1 high-level approaches to software development for GPUs, which strike a balance between performance and ease of programming; and 2 task partitioning to fully utilize the available devices. In this paper, we propose a framework, called PSkel, that provides a single high-level abstraction for stencil programming on heterogeneous CPU-GPU systems, while allowing the programmer to partition and assign data and computation to both CPU and GPU. Our current implementation uses parallel skeletons to transparently leverage Intel Threading Building Blocks Intel Corporation, Santa Clara, CA, USA and NVIDIA CUDA Nvidia Corporation, Santa Clara, CA, USA. In our experiments, we observed that parallel applications with task partitioning can improve average performance by up to 76% and 28% compared with CPU-only and GPU-only parallel applications, respectively. Copyright © 2015John Wiley & Sons, Ltd.

In the framework of service-oriented architecture (SOA), the initial stage of application development is a complex task due to the upfront costs, software redesign, and specialized skills. The focus of this study is on the formalization of a virtual model-view-controller (Virtual-MVC) design pattern to simplify the development of service-oriented applications for medium and small-sized enterprises. The Virtual-MVC pattern facilitates the implementation of service-oriented applications by abstracting the complex integration logic and service interface design from the developer's tasks. The main changes introduced by the Virtual-MVC pattern are the total decoupling of the View from the Model, whose links are reorganized within an enhanced Controller based on the enterprise service bus. The Controller is reinforced with dependency injection for service virtualization. In this paper, the description of a Virtual-MVC-based programming framework is formalized, and a standard functional classification of MVC-related patterns is proposed for comparison. The Virtual-MVC pattern is implemented into a software development framework, along with its corresponding programming strategy. The evaluation is performed through a study in a software engineering course at the University of Aizu, where services were designed following the Virtual-MVC programming approach. The results indicate a reduction of development complexity, while enforcing service design principles. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

To address the challenge of virtual process engineering (VPE), a systematic co-design of the physical model, numerical software, and computer hardware was conducted, eventually leading to the so-called EMMS Paradigm, which can greatly accelerate simulation speed while reducing its cost. Following this paradigm, a multiscale software framework was developed, coupling continuum and coarse-grained discrete simulations and a multiscale hardware architecture with different parallelization schemes, which have drawn the dream of VPE a substantial step closer: High-resolution interactive simulation of pilot-scale reactors or direct numerical simulation of microreactors, both at quasi-real time speed for the multiphase hydrodynamics, are now possible on the upgraded Mole-8.5 supercomputing system. The spectrum of multiscale methods available or to be developed for different purposes in VPE, and the corresponding software and hardware co-designing from more fundamental levels, are discussed also.

We describe the design of an object-oriented library of software components that are suitable for constructing simulations of systems of interacting particles. The emphasis of the discussion is on the general design of the components and how they interact, and less on details of the programming interface or its implementation. Example code is provided as an aid to understanding object-oriented programming structures and to demonstrate how the framework is applied.

With the development of applications and high-throughput sensor technologies in medical fields, scientists and scientific professionals are facing a big challenge—how to manage and analyze the big electrophysiological datasets created by these sensor technologies. The challenge exhibits several aspects: one is the size of the data (which is usually more than terabytes); the second is the format used to store the data (the data created are generally stored using different formats); the third is that most of these unstructured, semi-structured, or structured datasets are still distributed over many researchers' own local computers in their laboratories, which are not open access, to become isolated data islands. Thus, how to overcome the challenge and share/mine the scientific data has become an important research topic. The aim of this paper is to systematically review recent published research on the developed web-based electrophysiological data platforms from the perspective of cloud computing and programming frameworks. Based on this review, we suggest that a conceptual scientific workflow-based programming framework associated with an elastic cloud computing environment running big data tools (such as Hadoop and Spark) is a good choice for facilitating effective data mining and collaboration among scientists. WIREs Data Mining Knowl Discov 2017, 7:e1206. doi: 10.1002/widm.1206 For further resources related to this article, please visit the WIREs website.

Dynamic consolidation of virtual machines VMs is an efficient approach for improving the utilization of physical resources and reducing energy consumption in cloud data centers. Despite the large volume of research published on this topic, there are very few open-source software systems implementing dynamic VM consolidation. In this paper, we propose an architecture and open-source implementation of OpenStack Neat, a framework for dynamic VM consolidation in OpenStack clouds. OpenStack Neat can be configured to use custom VM consolidation algorithms and transparently integrates with existing OpenStack deployments without the necessity of modifying their configuration. In addition, to foster and encourage further research efforts in the area of dynamic VM consolidation, we propose a benchmark suite for evaluating and comparing dynamic VM consolidation algorithms. The proposed benchmark suite comprises OpenStack Neat as the base software framework, a set of real-world workload traces, performance metrics and evaluation methodology. As an application of the proposed benchmark suite, we conduct an experimental evaluation of OpenStack Neat and several dynamic VM consolidation algorithms on a five-node testbed, which shows significant benefits of dynamic VM consolidation resulting in up to 33% energy savings. Copyright © 2014 John Wiley & Sons, Ltd.

Chemical process modelling and simulation are widely used in process industries to progress in the understanding and in the improvement of many processes. Due to the complexity and variety of these processes, several pieces of software are often needed to model a given process, hence requiring interoperability between software. CAPE-OPEN is an industry standard for interoperability between process simulation software. Compared to proprietary interfaces of software applications, CAPE-OPEN allows for less overhead on programming and maintenance, fast access to market and a common basis for collaboration in joint projects.

We describe a new approach to the design of visible difference metrics that is based on calculating the information available at different points in the visual pathway and determining whether an ideal linear classifier can use this information to reliably predict the difference between two stimuli. This approach, referred to as the computational observer model, establishes a near upper bound on performance by assessing whether the information necessary to make discrimination is present in the visual system. We describe the implementation of a software framework that embodies the computational observer and illustrate how this framework can be used to address specific questions about display design.

Global software development in software development industry is a new aspect for many software project managers. In this scenario, the allocation of work packages among project participants is not a simple task. This allocation was traditionally determined by availability and competence but this new trend introduces complexity in an already complex process. Given the need to define new models to guide managers in these operations, this paper presents a framework to allocate work packages among project participants. Apart from the introduction of the framework itself, the results of its implementation are presented. These results show a notable output of the implementation in terms of accuracy of task execution to planning, effect introduction and overall satisfaction. Copyright © 2013 John Wiley & Sons, Ltd.

The support for software reuse has been a major goal in the design of programming languages. This goal, however, has proven difficult to reach, being only partially enabled by current software tools. In particular, reuse is not fully supported by object-oriented programming OOP. Aspect-oriented programming AOP has introduced new operators that extend OOP, enabling a superior support for reusability. However, AOP operators exhibit limitations in supporting software reuse and more powerful constructs are still required. We consider the ability to define software in an independent manner as the key construct to enable systematic software reuse. To bridge the gap between independence and practical software tools, we have developed the concept of Independent and Pluggable Software Unit PU, a construct that supports the definition of software topologies. In this paper, we compare PUs with AOP in their support for reusable software. To enable comparison, we employ some well described problems addressed by Software Design Patterns SDPs. We provide PU and AOP versions of several SDPs, including, Observer, Composite, Command, Chain of Responsibility, and Proxy. In particular, we show that, whereas PUs provide a unified representation of design patterns, AOP representations do not achieve this unification. We also show that AOP solutions do not promote independent and reusable software.Copyright © 2013 John Wiley & Sons, Ltd.

Aircraft dynamics and control (ADC) is a core course requirement for an undergraduate program in aeronautical engineering. This article presents an undertaking that reconfigures the instruction of fundamental concepts in ADC by replacing traditional problem-solving approach with a method that relies on a simulation framework comprising of Matlab, USAF DATCOM, and flight simulation software. The typical challenges experienced by students including their inability to visualize complicated, multi-modal aircraft were overcome by the new method thus enhancing the student's learning experience. The implemented approach improved students' motivational belief and its calibration, their use of active learning strategies and actual performance. © 2013 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:63–71, 2015; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21579

Uintah is a software framework that provides an environment for solving fluid-structure interaction problems on structured adaptive grids for large-scale science and engineering problems involving the solution of partial differential equations. Uintah uses a combination of fluid flow solvers and particle-based methods for solids, together with adaptive meshing and a novel asynchronous task-based approach with fully automated load balancing. When applying Uintah to fluid-structure interaction problems, the combination of adaptive meshing and the movement of structures through space present a formidable challenge in terms of achieving scalability on large-scale parallel computers. The Uintah approach to the growth of the number of core counts per socket together with the prospect of less memory per core is to adopt a model that uses MPI to communicate between nodes and a shared memory model on-node so as to achieve scalability on large-scale systems. For this approach to be successful, it is necessary to design data structures that large numbers of cores can simultaneously access without contention. This scalability challenge is addressed here for Uintah, by the development of new hybrid runtime and scheduling algorithms combined with novel lock-free data structures, making it possible for Uintah to achieve excellent scalability for a challenging fluid-structure problem with mesh refinement on as many as 260K cores. Copyright © 2013 John Wiley & Sons, Ltd.

We present a new software framework for Markov chain Monte Carlo sampling for simulation, prediction, and inference of protein structure. The software package contains implementations of recent advances in Monte Carlo methodology, such as efficient local updates and sampling from probabilistic models of local protein structure. These models form a probabilistic alternative to the widely used fragment and rotamer libraries. Combined with an easily extendible software architecture, this makes PHAISTOS well suited for Bayesian inference of protein structure from sequence and/or experimental data. Currently, two force-fields are available within the framework: PROFASI and OPLS-AA/L, the latter including the generalized Born surface area solvent model. A flexible command-line and configuration-file interface allows users quickly to set up simulations with the desired configuration. PHAISTOS is released under the GNU General Public License v3.0. Source code and documentation are freely available from http://phaistos.sourceforge.net. The software is implemented in C++ and has been tested on Linux and OSX platforms. © 2013 Wiley Periodicals, Inc.

Open source software systems that serve as key components of critical infrastructures in the society are still ever-expanding now. Many open source software systems are developed in all parts of the world, that is, Firefox, Apache HTTP server, Linux, Android, and so on. Especially, a large-scale open source solution composed of several open source software is now attracting attention as a next-generation software development paradigm because of the cost reduction, quick delivery, and work saving. In this paper, we propose a new approach to software reliability assessment based on stochastic differential equations and a hierarchical Bayesian model in order to consider the interesting aspect of the collision status in the binding phase of open source software. Also, we analyze actual software fault-count data to show numerical examples of software reliability assessment considering the component collision for several open source software. Moreover, we show that the proposed reliability analysis can assist improvement of quality for the large-scale open source solution. Copyright © 2013 John Wiley & Sons, Ltd.

Complex coupled multiphysics simulations are playing increasingly important roles in scientific and engineering applications such as fusion, combustion, and climate modeling. At the same time, extreme scales, increased levels of concurrency, and the advent of multicores are making programming of high-end parallel computing systems on which these simulations run challenging. Although partitioned global address space PGAS languages attempt to address the problem by providing a shared memory abstraction for parallel processes within a single program, the PGAS model does not easily support data coupling across multiple heterogeneous programs, which is necessary for coupled multiphysics simulations. This paper explores how multiphysics-coupled simulations can be supported by the PGAS programming model. Specifically, in this paper, we present the design and implementation of the XpressSpace programming system, which extends existing PGAS data sharing and data access models with a semantically specialized shared data space abstraction to enable data coupling across multiple independent PGAS executables. XpressSpace supports a global-view style programming interface that is consistent with the PGAS memory model, and provides an efficient runtime system that can dynamically capture the data decomposition of global-view data-structures such as arrays, and enable fast exchange of these distributed data-structures between coupled applications. In this paper, we also evaluate the performance and scalability of a prototype implementation of XpressSpace by using different coupling patterns extracted from real world multiphysics simulation scenarios, on the Jaguar Cray XT5 system at Oak Ridge National Laboratory. Copyright © 2013 John Wiley & Sons, Ltd.

Multi-touch driven user interfaces are becoming increasingly prevalent because of their intuitiveness and because of the reduction in the associated hardware costs. In recognition of this trend, multi-touch software frameworks MSFs have begun to emerge. These frameworks abstract the low level issues of multi-touch software development and deployment. MSFs therefore enable software developers who are unfamiliar with the complexities of multi-touch software development to implement and deploy multi-touch applications more easily. However, some multi-touch applications have real-time system requirements, and at present, no MSFs provide support for the development and deployment of such real-time multi-touch applications. The implication of this is that software developers are unable to take advantage of MSFs and, therefore, are forced to handle the complexities of multi-touch and real-time systems development and deployment for themselves in an ad hoc manner. The primary consequence of this is that the multi-touch and/or real-time aspects of the application may not function correctly. In this paper, guidelines are presented for applying real-time system concepts to support the development and deployment of real-time multi-touch applications using MSFs. This serves to increase the probability that the application will meet its timing requirements while also reducing the complexity of the development and deployment process associated with multi-touch applications. Copyright © 2013 John Wiley & Sons, Ltd.

SUMMARY In several scientific and business domains, very large data repositories are generated. To find interesting and useful information in those repositories, efficient data mining techniques and knowledge discovery processes must be used. The exploitation of data mining techniques in science helps scientists in hypothesis formation and gives them a support on their scientific practices, whereas in industrial processes, data mining can exploit existing data sources as a real value for companies that can take advantage from the knowledge that can be extracted from their large data sources. Data mining tasks are often composed by multiple stages that may be linked to each other to form various execution flows. Moreover, data mining tasks are often distributed because they involve data and tools located over geographically distributed environments. Therefore, it is fundamental to exploit effective paradigms, such as services and workflows, to model data mining tasks that are both multi-staged and distributed. This paper discusses data mining services and workflows for analyzing scientific data in high-performance distributed environments such as Grids and Clouds. We discuss how it is possible to define basic and complex services for supporting distributed data mining tasks in Grids. We also present a workflow formalism and a service-oriented programming framework, named DIS3GNO, for designing and running distributed knowledge discovery processes in the Knowledge Grid system. DIS3GNO supports all the phases of a knowledge discovery process, including composition, execution, and results visualization. After introducing DIS3GNO, some relevant use cases implemented by it and a performance evaluation of the system are discussed.Copyright © 2012 John Wiley & Sons, Ltd.

This article presents a new open-source software tool, SciMAT, which performs science mapping analysis within a longitudinal framework. It provides different modules that help the analyst to carry out all the steps of the science mapping workflow. In addition, SciMAT presents three key features that are remarkable in respect to other science mapping software tools: (a) a powerful preprocessing module to clean the raw bibliographical data, (b) the use of bibliometric measures to study the impact of each studied element, and (c) a wizard to configure the analysis. © 2012 Wiley Periodicals, Inc.

Decision Support Systems have been developed to aid the decision maker by providing ranked alternatives to consider. The ranking criteria may be resource-based, schedule-based or performance-based. When considering decisions that affect the overall architecture of a software system and the integration of its subsystems/components, the software systems engineer may have some unique challenges when legacy software is part of the system. For the software systems engineer, reengineering legacy systems or integrating legacy systems with new development and/or off-the-shelf software are areas where effective software system analysis is critical. When analyzing a software system, a range of system artifacts may be used. These artifacts include a description of the system in natural language, program design language descriptions, flow charts, object diagrams, as well as the system code. All of these artifact types can contain equivalent information at their specific level of abstraction. However, deriving information that is needed from each of these types of artifacts for reengineering or integrating a legacy system may present varying levels of difficulty. For example, analyzing a poorly structured system with little or no design documentation is a particularly challenging problem. Software modelling using an abstract architecture representation as a common description vehicle can “level the playing field” by creating representations of disparate systems at the same level of abstraction. This is of importance to reengineering efforts; it shows promise for supporting and facilitating integration efforts between legacy and other systems. It also allows the definition and development of a framework for a decision support system to aid the software system engineer. This paper is a follow on to previous work by the authors and presents a proposed decision support system framework that makes the use of the technical analyses and techniques presented.

This paper describes an approach towards protocol verification, which is based on the Unifying Theories of Programming framework and the associated refinement calculus: we encode protocol runs as predicates, in the form of homogeneous relations between probability distributions on the state space at the beginning and at the end of the protocol. The attacker model is a variation of the classical Dolev-Yao model, where cryptographic primitives can be broken probabilistically. We obtain a lattice of traces, where safe runs with respect to the attacker not achieving a given goal of the protocol are at the bottom and possible attacks are above in the order of increasing probability of success for the attacker. Copyright © 2012 John Wiley & Sons, Ltd.

Pervasive computing applications involve both software concerns, like any software system, and integration concerns, for the constituent networked devices of the pervasive computing environment. This situation is problematic for testing because it requires acquiring, testing and interfacing a variety of software and hardware entities. This process can rapidly become costly and time-consuming when the target environment involves many entities. This paper introduces DiaSim, a simulator for pervasive computing applications. To cope with widely heterogeneous entities, DiaSim is parameterized with respect to a description of a target pervasive computing environment. This description is used to generate both a programming framework to develop the simulation logic and an emulation layer to execute applications. Furthermore, a simulation renderer is coupled to DiaSim to allow a simulated pervasive system to be visually monitored and debugged. DiaSim has been implemented and used to simulate various pervasive computing systems in different application areas, demonstrating the generality of our parameterized approach.

Application update at run-time remains a challenging issue in software engineering. There are many techniques with different evaluation metrics, resulting in different behaviours in the application being updated. In this paper, we provide an extensive review of research work on dynamic software updating. A framework for the evaluation of dynamic updating features is developed, and the articles are categorized and discussed based on the provided framework. Areas of online software maintenance requiring further research are also identified and highlighted. This information is deemed to not only assist practitioners in selecting appropriate dynamic updating techniques for their systems, but also to facilitate the ongoing and continuous research in the field of dynamic software updating. Copyright © 2012 John Wiley & Sons, Ltd.

Modern graphics cards provide computational capabilities that exceed current CPUs. As one of the computational intensive problems, numerical weather prediction has the opportunity to benefit from the massive number of threads and large memory throughput in the graphics architecture. In this paper, we present the key steps to integrate the Compute Unified Device Architecture (CUDA) programming framework for one key component in numerical weather prediction, the data assimilation algorithm, which incorporates the observational data into the model to produce the best initial condition in the next prediction. The data assimilation algorithm we studied in this paper exhibits good localization and favors parallelism. To maximize the throughput of the graphics card, over a million CUDA threads, global memory coalescing, and fast graphics shared memory are utilized. We also demonstrate the differences in the advancement of GPU architectures from the GTX 200 series to Fermi. The experiments are carried out separately on a GTX 260 (GTX 200 series) and a GTX 460 (Fermi) graphics card. Results show an improvement of 72.1× speedup running on the GTX 260 and 92.7×speedup on the GTX 460. The results provide attractive evidence for applying CUDA GPUs to high demanding scientific computation realms. Copyright © 2011 John Wiley & Sons, Ltd.

It is generally accepted that systems composed of multiple aerial robots with autonomous cooperation capabilities can assist responders in many search and rescue (SAR) scenarios. In most of the previous research work, the aerial robots are mainly considered as platforms for environmental sensing and have not been used to assist victims. In this paper, outdoor field experiments of transportation and accurate deployment of loads with single/multiple autonomous aerial vehicles are presented. This is a novel feature that opens the possibility to use aerial robots to assist victims during rescue phase operations. Accuracy in the deployment location is a critical issue in SAR scenarios in which injured people may have very limited mobility. The presented system is composed of up to three small-size helicopters and features cooperative sensing, using several different sensor types. The system supports several forms of cooperative actuation as well, ranging from the cooperative deployment of small sensors/objects to the coupled transportation of slung loads. The complete system is described, outlining the hardware and software framework used, as well as the approaches for modeling and control used. Additionally, the results of several flight field experiments are presented, including a description of the worldwide first successful autonomous load transportation experiment, using three coupled small-size helicopters (conducted in December 2007). During these experiments strong, steady winds and wind gusts were present. Various solutions and lessons learned from the design and operation of the system are also provided. © 2011 Wiley Periodicals, Inc.

This paper presents AIBench (SING group, Ourense, Spain), a JAVA desktop application framework mainly focused on scientific software development, with the goal of improving the productivity of research groups. Following the MVC design pattern, the programmer is able to develop applications using only three types of concepts: operations, data-typesand views. The framework provides the rest of the functionality present in typical scientific applications, including user parameter requests, logging facilities, multithreading execution, experiment repeatability and graphic user interface generation, among others. The proposed framework is implemented following a plugin-based architecture, which also allows assembling new applications by the reuse of modules from past development projects. Copyright © 2011 John Wiley & Sons, Ltd.

This paper describes a few mild design constraints that permit rapid adaptation of the modelling code for linear wave propagation to imaging/inversion or design optimization applications, retaining parallelism and other performance enhancements of the underlying simulator. It also describes an abstract software framework preserving the modularity of both optimization and modelling software in building inversion applications and illustrates this possibility via an example framework implemented in C++. Wave inverse problems tend to be afflicted by a variety of features, including extreme ill‐conditioning and nonlinearity, which degrade the performance of optimization formulations. Extended modelling variants of least‐squares inversion, motivated by migration velocity analysis, may relieve some of these difficulties. The framework described also accommodates these extensions to standard inversion.

An interactive software to simulate and to study the steady state and transient operation of distributed generation systems with a large number of elements is presented. This software can be an effective tool to give students better understanding of the behavior of power systems under various operating conditions, and can motivate them to learn more about power systems. It may also be useful for advanced users such as PhD students and researchers as they can implement their own algorithms and models, without the necessity of buying expensive licenses for commercial software. In addition, the software may well be used for teaching introductory courses into the analysis of network with high penetration of distributed generators. A detailed software description, comparison with similar available software, potential educational applications and future enhancements of this simulation tool are presented and discussed.

During the 19805 much attention, both pro and con, was directed toward optimized production technology (OPT). Criticism was directed at the proprietary nature of the scheduling algorithms within the software. Despite these criticisms, many large companies installed OPT. Little has been written on how the software is constructed and operates. This article introduces the software, provides a discussion of how it interfaces with management, and how various algorithms are imbedded in the software function. Last, a survey of companies that had implemented the software revealed that the major users are in the automotive industry.

This paper shows that object-oriented generic application frameworks can be used to improve the design and implementation of interactive engineering software. Enhanced development time, consistency, transparency, flexibility, and quality are achieved by separating programs into generic and domain-specific components. Advantages of object-oriented programming over conventional procedure-oriented approaches are highlighted for the development of basic interactive software (event-driven architectures, user-interface standards, etc.). A language-independent model is used to provide the implementation details for a generic application framework called “GenApp.” Programs can be constructed on top of this framework by creating specialized object classes that selectively mix inherited generic behavior with application-specific tasks. Customized user-interface, object management, and support for existing procedures are some of the features offered by GenApp to simplify the development of engineering software. A finite-element analysis program is shown as an example product of this generic application framework.

Software design is much more important for individual-based models (IBMs) than it is for conventional models,for three reasons. First,the results of an IBM are the emergent properties of a system of interacting agents that exist only in the software; unlike analytical model results,an IBMs outcomes can be reproduced only by exactly reproduc- ing its software implementation. Second,outcomes of an IBM are expected to be complex and novel,making software er- rors difficult to identify. Third,an IBM needs 'systems soft- ware' that manages populations of multiple kinds of agents, often has nonlinear and multi-threaded process control and simulates a wide range of physical and biological processes. General software guidelines for complex models are especially important for IBMs. (1) Have code critically reviewed by several people. (2) Follow prudent release management prac- tices,keeping careful control over the software as changes are implemented. (3) Develop multiple representations of the model and its software; diagrams and written descriptions of code aid design and understanding. (4) Use appropriate and widespread software tools which provide numerous major ben- efits; coding 'from scratch' is rarely appropriate. (5) Test the software continually,following a planned,multi-level,exper- imental strategy. (6) Provide tools for thorough,pervasive validation and verification. (7) Pay attention to how pseudo- random numbers are generated and used. Additional guide- lines for IBMs include: (a) design the model's organization before starting to write code,(b) provide the ability to ob- serve all parts of the model from the beginning,(c) make an extensive effort to understand how the model executes how

The purpose of this exploratory study is to investigate organizational-level mechanisms in the Prevention Delivery System (PDS) and their influence on implementing comprehensive programming frameworks (e.g., Communities that Care-CtC) as the innovation. The PDS is part of the Interactive Systems Framework for Dissemination and Implementation (ISF) and describes key characteristics of innovation implementation and dissemination. The study addresses two research questions: (1) What types of organizational characteristics are related to successful use of each of the programming processes (i.e., planning, implementation, evaluation, and sustainability) that are part of comprehensive programming frameworks?; and (2) What are the similarities and differences in the organizational patterns correlated with use of each of the programming processes? Surveys, interview data, and other documents designed to assess organizational characteristics and extent of use of a comprehensive programming framework over time, were collected from 8 Community boards and 23 provider agencies. These organizations were responsible for planning and delivering substance abuse prevention services as part of a statewide initiative in Ohio. Data were analyzed using Spearman rho (and rank-biserial) correlations, with an emphasis on effect sizes. Results indicated that leadership, shared vision, process advocates, and technical assistance were common correlates of use across programming processes. However, the role played by these organizational variables differed for each programming process, pointing to complex interactions of the organizational infrastructure with other variables (i.e., characteristics of the innovation itself and external macro-level factors). This exploratory study provides preliminary data on the organizational-level mechanisms of the PDS and the complexity of their relationships with the other Systems in the Interactive Systems Framework.

Hybrids of meta-heuristics have been shown to be more effective and adaptable than their parents in solving combinatorial optimization problems. However, hybridized schemes are also more tedious to implement due to their increased complexity. We address this problem by proposing the meta-heuristics development framework (MDF). In addition to being a framework that promotes software reuse to reduce developmental effort, the key strength of MDF lies in its ability to model meta-heuristics using a “request, sense and response” schema, which decomposes algorithms into a set of well-defined modules that can be flexibly assembled through a centralized controller. Under this scheme, hybrid schemes become an event-based search that can adaptively trigger a desired parent's behavior in response to search events. MDF can hence be used to design and implement a wide spectrum of hybrids with varying degrees of collaboration, thereby offering algorithm designers quick turnaround in designing and testing their meta-heuristics. Such technicality is illustrated in the paper through the construction of hybrid schemes using ant colony optimization and tabu search.