Search

This paper presents DistRDF2ML, the generic, scalable, and distributed framework for creating in-memory data preprocessing pipelines for Spark-based machine learning on RDF knowledge graphs. This framework introduces software modules that transform large-scale RDF data into ML-ready fixed-length numeric feature vectors. The developed modules are optimized to the multimodal nature of knowledge graphs. DistRDF2ML provides aligned software design and usage principles as common data science stacks that offer an easy-to-use package for creating machine learning pipelines. The modules used in the pipeline, the hyper-parameters and the results are exported as a semantic structure that can be used to enrich the original knowledge graph. The semantic representation of metadata and machine learning results offers the advantage of increasing the machine learning pipelines’ reusability, explainability, and reproducibility. The entire framework of DistRDF2ML is open source, integrated into the holistic SANSA stack, documented in scala-docs, and covered by unit tests. DistRDF2ML demonstrates its scalable design across different processing power configurations and (hyper-)parameter setups within various experiments. The framework brings the three worlds of knowledge graph engineers, distributed computation developers, and data scientists closer together and offers all of them the creation of explainable ML pipelines using a few lines of code.

International audience; CRISPR-based genome editing systems have been successfully and effectively used in many organisms. However, only a few studies have reported the comparison between CRISPR/Cas9 and CRISPR/Cpf1 systems in the whole-genome applications. Although many web-based toolkits are available, there is still a shortage of comprehensive, user-friendly, and plant-specific CRISPR databases and desktop software. In this study, we identified and analyzed the similarities and differences between CRISPR/Cas9 and CRISPR/Cpf1 systems by considering the abundance of proto-spacer adjacent motif (PAM) sites, effects of GC content, optimal proto-spacer length, potential universality within the plant kingdom, PAM-rich region (PARR) inhibiting ratio, and effects of G-quadruplex (G-Q) structures. Using this information, we built a comprehensive CRISPR database (including 138 plant genome data sources, www.grapeworld.cn/pc/index.html), which provides search tools for the identification of CRISPR editing sites in both CRISPR/Cas9 and CRISPR/Cpf1 systems. We also developed a desktop software on the basis of Perl/TK tool, which facilitates and improves the detection and analysis of CRISPR editing sites at the whole-genome level on Linux and/or Windows platform. Therefore, this study provides helpful data and software for easy selection and application of CRISPR-based genome editing systems in plants.

Software design patterns are well-known solutions for solving commonly occurring problems in software design. Detecting design patterns used in the code can help to understand the structure and behavior of the software, evaluate the quality of the software, and trace important design decisions. To develop and maintain a software system, we need sufficient knowledge of design decisions and software implementation processes. However, the acquisition of knowledge related to design patterns used in complex software systems is a challenging, time-consuming, and costly task. Therefore, using a suitable method to detect the design patterns used in the code reduces software development and maintenance costs. In this paper, we proposed a new method based on conceptual signatures to improve the accuracy of design pattern detection. So we used the conceptual signatures based on the purpose of patterns to detect the patterns’ instances that conform to the standard structure of patterns, and cover more instances of patterns’ variants and implementation versions of the patterns and improve the accuracy of pattern detection. The proposed method is a specific process in two main phases. In the first phase, the conceptual signature and detection formula for each pattern is determined manually. Then in the second phase, each pattern in the code is detected in a semi-automatic process using the conceptual signature and pattern detection formula. To implement the proposed method, we focused on GoF design patterns and their variants. We evaluated the accuracy of our proposed method on five open-source projects, namely, Junit v3.7, JHotDraw v5.1, QuickUML 2001, JRefactory v2.6.24, and MapperXML v1.9.7. Also, we performed our experiments on a set of source codes containing the instances of GoF design patterns’ variants for a comprehensive and fair evaluation. The evaluation results indicate that the proposed method has improved the accuracy of design pattern detection in the code.

Building information modelling (BIM) represents a workflow whose application on a construction project will enable all involved players to compile as well as work with information on every aspect of a building in a common model/database. Through BIM, the entire building can be virtually designed and built on a computer. BIM touches every part of a building’s life cycle starting from the design phase well into the construction phase and beyond that into asset management. This research examines the experiences of early adopters of BIM and use that insight to introduce BIM, specially focusing on the structural analysis and design stage of a building. The study demonstrates how all structural design activities can be integrated with each other and how cross-discipline collaboration with the architect can be achieved through the adoption of BIM without leaving ones customary structural design platform. As a demonstration, a sample building is modelled using Revit along with conventional structural software packages ETABS and SAFE. Plugins and applications were developed for these software packages to facilitate interoperability amongst them so that they all act together as a single platform. Modelling, analysis, design and clash detections were facilitated by applying BIM. Major benefits of employing BIM in a structural design project are illustrated through this research.

Software systems quality is strongly influenced by the presence of design problems and wrong constructs introduced during software evolution. Design smells are recognized to be indicators of such problems since their presence can indicate violations of the fundamental software design principles. This explains the interest of software researchers and developers in new approaches performing design smell early detection. In this paper, the adoption of a just-in-time design smell prediction approach is proposed. The approach uses a variant of Temporal Convolutional Networks (TCN) to predict the presence of design smells before they are introduced in the model. In comparison to other studies, in the proposed approach we focus on commit-level fine-grained product metrics and process metrics (i.e., ownership and seniority) to make deep neural networks training suitable. The validation is performed on a large dataset composed of six open source systems. The results show good prediction performance for some design smells and for all the considered design smells categories. The experiment performed shows that, with respect to baseline prediction models (i.e., LSTM,CNN and RF), the proposed TCN variant trained on the identified metrics, gives better results.

Aiming at the problems of low user satisfaction and long response time in traditional online English education platforms, this paper designs a web-based online English education platform and carries out relevant application tests. With the support of the web, the hardware and software of the platform are designed. The hardware of the platform is composed of student module, teacher module, administrator module, and database module. On this basis, the K-means clustering method is used to cluster the learner data in the web, to determine their English level, and the collaborative filtering algorithm is combined to recommend relevant course materials for learners so as to complete the platform software design. The application test results show that the platform has the advantages of superior function and security, high user satisfaction, and short response time and has certain practical application value.

Android is a mobile device on the operating system for mobile phones based on Linux, android provides an open platform for developers to create applications. Android-based application developers make applications so that they can be useful for the community ranging from game genre applications, education, entertainment and simulation applications that are very likely to be created and run on this android operating system. Simulation is the process of designing a matemastis or logical model of a real system, conducting experiments on models using computers to describe, explain and predict system behavior. For a simulation application company can be used as a medium of product promotion, while for smartphone users can help to channel the existing imagination into a real picture. The application of simulation applications many functions, one example of its application to two-wheeled motor vehicles. By utilizing android application and the growth of vehicle users that lead to the hobby of modification, it can be utilized by creating an android-based coloring simulation application to help modifiers and modification lovers in order to channel their imagination and make it easier to design colors as desired. Without having to bother using design software that requires special skills

This research aimsto produce a village web-based information system design in Manulondo Village. This application contains the design of a village information system including village profiles, population information, and village potential information. This research uses the method waterfall. The research stages include data collection, analysis, design, coding, implementation testing. The trial using BlackBox Testing. That is by testing the user interface system to find out whether the user interface contained in this application can function properly as expected. That results of the software design in the form of a web-based Manulondo Village information system, consist of, serach for population information an village potential information.

Code smell is a software quality problem caused by software design flaws. Refactoring code smells can improve software maintainability. While prior works mostly focused on Java code smells, only a few prior researches detect and refactor code smells of Python. Therefore, we intend to outline a route (i.e. sequential refactoring operation) for refactoring Python code smells, including LC, LM, LMC, LPL, LSC, LBCL, LLF, MNC, CCC and LTCE. The route could instruct developers to save effort by refactoring the smell strongly correlated with other smells in advance. As a result, more smells could be resolved by a single refactoring. First, we reveal the co-occurrence and the inter-causation between smells. Then, we evaluate the smells’ correlation. Results highlight seven groups of smells with high co-occurrence. Meanwhile, 10 groups of smells correlate with each other in a significant level of Spearman’s correlation coefficient at 0.01. Finally, we generate the refactoring route based on the association rules, we exploit an empirical verification with 10 developers involved. The results of Kendall’s Tau show that the proposed refactoring route has a high inter-agreement with the developer’s perception. In conclusion, we propose four refactoring routes to provide guidance for practitioners, i.e. {LPL [Formula: see text] LLF}, {LPL [Formula: see text] LBCL}, {LPL [Formula: see text] LMC} and {LPL [Formula: see text] LM [Formula: see text] LC [Formula: see text] CCC [Formula: see text] MNC}.

Software is rapidly evolving and operates in a changing environment; therefore, in addition to software design and testing, it is essential to observe and understand the software execution behavior by modeling data recorded during the execution of the software to improve its reliability. The nested call relationship between methods during the execution of software is common, but most process-mining methods are unable to discover them, only generating flat models with low fitness. Meanwhile, it is easy to generate “spaghetti-like” models with low comprehensibility when dealing with complex software execution data. This paper proposes a component-based hierarchical software behavior model discovery method that can discover hierarchical nested call structures during software runtime, improving the fitness of the model; meanwhile, the proposed method partitions the discovery model into several parts by component information to improve the comprehensibility of the model, which can also reflect the interaction behavior within and between components. The proposed approach was implemented in a process mining toolkit. Using real-life software event logs and public datasets, we demonstrated that compared with other advanced process mining techniques, our approach can visualize actual software execution behavior in a more accurate and easy-to-understand way while balancing time performance.

Today’s industry has gradually realized the importance of lifting efficiency and saving costs during the life-cycle of an application. In particular, we see that most of the cloud-based applications and services often consist of hundreds of micro-services; however, the traditional monolithic pattern is no longer suitable for today’s development life-cycle. This is due to the difficulties of maintenance, scale, load balance, and many other factors associated with it. Consequently, people switch their focus on containerization—a lightweight virtualization technology. The saving grace is that it can use machine resources more efficiently than the virtual machine (VM). In VM, a guest OS is required to simulate on the host machine, whereas containerization enables applications to share a common OS. Furthermore, containerization facilitates users to create, delete, or deploy containers effortlessly. In order to manipulate and manage the multiple containers, the leading Cloud providers introduced the container orchestration platforms, such as Kubernetes, Docker Swarm, Nomad, and many others. In this paper, a rigorous study on Kubernetes from an administrator’s perspective is conducted. In a later stage, serverless computing paradigm was redefined and integrated with Kubernetes to accelerate the development of software applications. Theoretical knowledge and experimental evaluation show that this novel approach can be accommodated by the developers to design software architecture and development more efficiently and effectively by minimizing the cost charged by public cloud providers (such as AWS, GCP, Azure). However, serverless functions are attached with several issues, such as security threats, cold start problem, inadequacy of function debugging, and many other. Consequently, the challenge is to find ways to address these issues. However, there are difficulties and hardships in addressing all the issues altogether. Respectively, in this paper, we simply narrow down our analysis toward the security aspects of serverless. In particular, we quantitatively measure the success probability of attack in serverless (using Attack Tree and Attack–Defense Tree) with the possible attack scenarios and the related countermeasures. Thereafter, we show how the quantification can reflect toward the end-to-end security enhancement. In fine, this study concludes with research challenges such as the burdensome and error-prone steps of setting the platform, and investigating the existing security vulnerabilities of serverless computing, and possible future directions.

Digital media have become increasingly important in recent years and can offer new possibilities for mathematics education in elementary schools. From our point of view, geometry and geometric objects seem to be suitable for the use of computer-aided design software in mathematics classes. Based on the example of Tinkercad, the use of CAD software — a new and challenging context in elementary schools — is discussed within the approach of domains of subjective experience and the Toulmin model. An empirical study examined the influence of Tinkercad on fourth-graders’ development of a model of a geometric solid and related reasoning processes in mathematics classes.

This article describes two types of paradigms – object-oriented and functional paradigms. Paradigm stands for a style and an approach to perform any kind of coding activities. Relevance of usage for each of them as well as their differences and benefits were analyzed. Regardless of ever-changing tendencies in popularity of both paradigms it is impossible to acknowledge any of them to deprecate another one. Although object-oriented programming as well as functional programming are essential in their approaches they have the same goal – to make comprehensive programs without possible mistakes. OOP follows imperative programming model which is based on a set of primitives the given language provides. Functional paradigm is intertwined with declarative style which imply what is to be done, but not how to do it. We may come to conclusion that the consensus is that object oriented paradigm and functional paradigm can be effective in a peculiar situation. Therefore, developers are to choose and pick the programming paradigm for a given task to make a process as simple and productive as it can be. Object-oriented programming languages are a good choice when you have a fixed set of operations on things and you add new things for your code to evolve. You can achieve it by adding new classes that implement existing methods while existing classes remain the same. Functional languages may be a better choice if you have a fixed set of things and you add new operations on existing things for your code to evolve. You can achieve it by adding new functions which are to be computed with existing data types while existing functions remain the same. Object-oriented programming as well as functional programming has its place in modern approaches to software development. Meanwhile the functional programming is being reconsidered and used much more often due to Big Data Technologies while object-oriented programming remains popular to perform representation of real-life objects in the code.

There are many methods of detecting unknown malware, each of which has its advantages, disadvantages and features of use. However, at present there is no methodology that would fully solve all the problems of detecting malware with acceptable efficiency. In the field of modern computer security, most solutions are implemented as a set of several technologies. In this regard, the study of modern methods of detecting malware is an important area. The purpose of this work is to analyze and systematize the main methods of detecting malicious software and study the features of their use. The research of signature and heuristic methods of malware detection is performed in the work. A separate analysis is devoted to the application of machine learning methods (static, dynamic, visual representation of elements and their combinations) for the classification of malicious programs. Various machine learning techniques have been studied: the machine method of reference vector, random forest, decision trees, naive bayes, k-nearest neighbor and gradient amplification to classify and detect malware samples and their respective classes, their filtering. The usefulness of graphical byte visualization for detecting software design templates using Dotplot technique for further automation of virus detection is shown. The comparative characteristic of modern, mainly, heuristic methods of detection of malware is executed and systematized on values of accuracy of search. As there is currently no effective method of detecting unknown malware, so to effectively search and destroy malware you need to combine all modern methods, techniques and tools, taking into account all the features of their use. The results can be used to develop software to effectively detect and destroy malware using artificial neural networks and their training.

Design patterns are generic solutions to common programming problems. Design patterns represent a typical example of design reuse. However, implementing design patterns can lead to several problems, such as programming overhead and traceability. Existing research introduced several approaches to alleviate the implementation issues of design patterns. Nevertheless, existing approaches pose different implementation restrictions and require programmers to be aware of how design patterns should be implemented. Such approaches make the source code more prone to faults and defects. In addition, existing design pattern implementation approaches limit programmers to apply specific scenarios of design patterns (e.g. class-level), while other approaches require scattering implementation code snippets throughout the program. Such restrictions negatively impact understanding, tracing, or reusing design patterns. In this paper, we propose a novel approach to support the implementation of software design patterns as an extensible Java compiler. Our approach allows developers to use concise, easy-to-use language constructs to apply design patterns in their code. In addition, our approach allows the application of design patterns in different scenarios. We illustrate our approach using three commonly used design patterns, namely Singleton, Observer and Decorator. We show, through illustrative examples, how our design pattern constructs can significantly simplify implementing design patterns in a flexible, reusable and traceable manner. Moreover, our design pattern constructs allow class-level and instance-level implementations of design patterns.

Based on reverse engineering, product innovation design and 3D-printing technology, a technical route for the rapid design and development of helmet products has been constructed, and optimize the product production process, reduce the product development cycle, improve production efficiency, and complete the personalized design of helmets to improve the comfort of personnel wearing. The point cloud data of the physical model were collected by the 3D scanner, and imported to the reverse processing software (Geomagic Studio) for data processing, surface reconstruction and surface fitting. In this way, the section curve of the repaired head surface was extracted. Then, the extracted information was sent to the forward design software (SolidWorks) through the parameter exchange command for the forward design of the helmet, and the 3D model was subsequently printed. Effectively solve the traditional design method for complex surface modelling design and manufacturing, forward software measurement deviation, modelling design process is complex and tedious, time-consuming and labor-intensive, cannot well meet the product design, processing and manufacturing process is relatively cumbersome, long production cycle and other design defects, speed up enterprise product development, shorten the cycle and reduce costs. Furthermore, the adoption of 3D printing technology to output the designed 3D digital model effectively shortens the product development cycle.

Power distribution systems are vulnerable to natural disasters and malicious attacks. An efficient and accurate online risk assessment tool is very necessary to provide timely warning information for emergency dispatch of resilient distribution systems. However, conventional analytical risk assessment methods are subject to known network information, while emerging datadriven methods rarely incorporate resilient resources into the risk assessment procedures, limiting their accuracies when applied to extreme events. To solve the problems, this paper proposes an improved online data-driven risk assessment method adaptive for resilient distribution systems. Twenty-five basic operational indexes from practical experience are chosen to indirectly reflect the system risk, and the complicated relationship between the indexes and risk is characterized by entropy weights and gray correlation degrees. The proposed method is validated on a modified 33-node system, and the results show that it has better accuracy compared with similar approaches in online risk assessment during extreme events. The whole scheme can be helpful for the software design and hardware layout of future resilient distribution systems.

Due to massive thread-level parallelism, GPUs have become an attractive platform for accelerating large-scale data parallel computations, such as graph processing. However, achieving high performance for graph processing with GPUs is non-trivial. Processing graphs on GPUs introduces several problems, such as load imbalance, low utilization of hardware unit, and memory divergence. Although previous work has proposed several software strategies to optimize graph processing on GPUs, there are several issues beyond the capability of software techniques to address. In this article, we present GraphPEG, a graph processing engine for efficient graph processing on GPUs. Inspired by the observation that many graph algorithms have a common pattern on graph traversal, GraphPEG improves the performance of graph processing by coupling automatic edge gathering with fine-grain work distribution. GraphPEG can also adapt to various input graph datasets and simplify the software design of graph processing with hardware-assisted graph traversal. Simulation results show that, in comparison with two representative highly efficient GPU graph processing software framework Gunrock and SEP-Graph, GraphPEG improves graph processing throughput by 2.8× and 2.5× on average, and up to 7.3× and 7.0× for six graph algorithm benchmarks on six graph datasets, with marginal hardware cost.

Spatial ability is considered a major factor of intelligence and is increasingly important in times of digitization. This article explores the fostering of spatial ability through computer-aided design software. Different notions of spatial ability will be discussed, and, finally, a concept consisting of five aspects will be described. In addition, literature reviews on the connection between the use of computers and the fostering of spatial ability, as well as on the use of 3D printing technology in mathematics education, are given. Building on this, a case study is presented which examines the work of two middle-school students using computer-aided design software within a workshop at the University of Siegen. From the data material, basic possible actions within such software are derived. These are, based on theory, connected with the five aspects of the specific concept of spatial ability used. The results show various perspectives for the fostering of spatial ability with computer-aided design software.

The reported use of 3D printing in hand and wrist rehabilitation has been mostly limited to feasibility studies and case series so far. Some of the reasons are the lack of purpose-built scanning applications, complicated digital design software, and lengthy and error-prone printing processes. We propose a multidisciplinary workflow for in-hospital mass production of patient-specific 3D-printed devices for hand and wrist rehabilitation.

This tutorial is designed for those who want an introduction to building a digital library using an open source software program. The tutorial will focus on the Greenstone digital library software. In particular, participants will work with the Greenstone Librarian Interface, a flexible graphical user interface designed for developing and managing digital library collections. Attendees do not require programming expertise, however they should be familiar with HTML and the Web, and be aware of representation standards such as Unicode, Dublin Core and XML. The Greenstone software has a pedigree of more than two decades, with over 1 million downloads from SourceForge. The premier version of the software has, for many years, been Greenstone~2. This tutorial will introduce users to Greenstone 3---a redesign and reimplementation of the original software to take better advantage of newer standards and web technologies that have been developed since the original implementation of Greenstone. Written in Java, the software is more modular in design to increase the flexibility and extensibility of the software design. Emphasis in the tutorial is placed on where Greenstone~3 goes beyond what Greenstone~2 can do. Through the hands-on practical exercises participants will, for example, build collections where geo-tagged metadata embedded in photos is automatically extracted and used to provide a map-based view in the digital library of the collection.

The study of the transport of particles in different environments plays an essential role in understanding interactions with humans and other living organisms. Importantly, obtained data can be directly used for multiple applications in fields such as fundamental biology, toxicology or medicine. Particle movement in biorelevant media can be readily monitored using microscopy and converted into time-resolved trajectories using freely available tracking software. However, translation into tangible and meaningful parameters is time-consuming and not always intuitive. Thus, we developed a new software – MPTHub – as an open-access, stand-alone, user-friendly tool for the rapid and reliable analysis of particle trajectories extracted from video microscopy. The software was programmed using Python and allowed to import and analyze trajectory data, and export relevant data such as individual and ensemble time-averaged mean square displacements and effective diffusivity, and anomalous transport exponent. Data processing was reliable, fast (total processing time of less than 10 sec) and required minimal memory resources (up to a maximum of around 150 MB in RAM). Demonstration of software applicability was conducted by studying the transport of different polystyrene nanoparticles (100-200 nm) in mucus surrogates. Overall, MPTHub represents a freely available software tool that can be used even by unexperienced users for studying the transport of particles in biorelevant media.

Objective: This study intends to design software algorithms, which is called Co-Drug Interaction (CODI), that able to analyse drug interactions in prescription and recommendations for further correction by replacing active substances based on the E-book Drug Interaction Facts and provide drug information features. Methods: The research used data collection and conversed into programming languages. Java language programme choosed to build the entire application as its considerable free of charge and recognizable interface to use. The reference book is also used to help in prescribing and evaluating the reliability and efficiency of the software. Result: The evaluations were performed by analyzing 30 groups of medicine based on 2 diseases, which are hypertension and diabetes mellitus. Conclusion: The algorithm design and evaluation are in accordance with the planned output.

To expand the use of Computer Aided Design (CAD) technology in the competency pattern contruction course in drawing various sleeve patterns, this study aims to develop belended learning based optitex media. With Research & Development (R&D) method, Borg and Gall combined with Dick & Carey instructional system development model, this study develops optitex media as a viable and effective medium to use as a learning resource for learning tutorials to draw various patterns of sleeves based on Optitex PDS 11. Procedure development of instructional media there are 5 stages as follows: (1) The preliminary study, (2) Design software, (3) Gather materials, (4) Creating and producing instructional media, (5) Conduct field reviews in order to evaluate and revise products. Obtaining the average result of the presentation of the learning material expert gave a response of 88.75%, then the design expert gave a response of 84.17%, that the material was suitable for use because it contained material and delivery criteria that met the standards of delivering messages to students and meanwhile learning media experts gave a response of 86.25% worthy of use because it has been designed in such a way and meets the standards of learning media. In the small group presentation results with an average value of 86.42%. In the results of group presentations with an average value of 91.09% and in the results of large group / field trial presentations with an average presentation of 92.76%. The results showed that the optitex media to draw various patterns of sleeves was effectively used based on blended learning.

As quantum internet technologies develop, the need for simulation software and education for quantum internet rises. QuNetSim aims to fill this need. QuNetSim is a Python software framework that can be used to simulate quantum networks up to the network layer. The goal of QuNetSim is to make it easier to investigate and test quantum networking protocols over various quantum network configurations and parameters. The framework incorporates many known quantum network protocols so that users can quickly build simulations and beginners can easily learn to implement their own quantum networking protocols., 11 pages, 6 figures. To appear in IEEE Transactions on Quantum Engineering

The manuscript developed an optimal frequency band transmission system structure of QPSK. The software programming experiment of this complete QPSK optimal band transmission system is designed and realized based on Matlab. The experimental parameters used in the design are consistent with the requirements of the actual system parameters. The key code of the software design is given in each module of the system. The whole system is simulated. The simulation results show that the QPSK optimal band transmission system can achieve the best reception performance and realize its function.

Interface and interaction design take up most of the times in software creation. Human Computer Interaction (HCI) is mainly the best way to interact with a computer. During software development, class diagram is the only required step and process to design an information system according to UML notation. In addition, creating class diagram is a mandatory activity during the software creation process. The aim of this paper is to automatically generate the HCI mockup from class diagram to make easy and extremely fast software design. For example, the SEF (Schema d’Enchainement de Fenetre), is an interface model allowing to create a new interface mockup. It offers more widgets to design the HCI. And MACAO (Methode d’Analyse et de Conception d’Applications Orientees-objets) is one of the methods which helps computer scientist to easily create software. The model transformation is based on Model Driven Engineering (MDE). We use UML notation to design the class diagrams. We also adopt MDA architecture to create the model-based transformation process. Transformation rules are created using Atlas Transformation Language (ATL) to automatically generate a specific interface from the class diagram.

In software testing, one of the most important issues is to validate the consistency of program and design. Usually, this kind of design information is expressed by software related documents, such as software requirements, software design, etc. Therefore, how to effectively extract the design information based on these documents is very important. In this paper, we first introduce the method of the analyzing class diagram model and method call diagram model from UML model of design document; secondly, we classify and summarize the inconsistency problems that may exist in the two types of models; thirdly, we design static and dynamic consistency algorithms for these models. Finally, we implement the CCoSaD (consistency checking of software and Design) tool and validate the effectiveness based on experiments.

With the development of society and the improvement of living standards, people pay more and more attention to their own living environment and life safety, and more people are gradually paying attention to the impact of the quality of the living environment on their health and work efficiency, and to meet this demand of people, it is necessary to effectively monitor and control the living environment. Based on this, this article applies cloud computing and Internet of things technologies that have developed rapidly in recent years, and proposes to design a residential environment intelligent monitoring system based on cloud computing and Internet of things, and use Internet of things and sensor technologies to achieve target connection and communication. It then uses distributed computing, a cloud computing technology, to implement integrated, standardized management of this system for truly intelligent monitoring. In this article, we first gathered a large amount of information through literature search methods, systematically introduced cloud computing and Internet of Things technologies, and introduced two applications in environmental intelligent monitoring. Next, we propose a design experiment of a residential environment intelligent monitoring system based on cloud computing and the Internet of Things, and propose an overall concept of system design, system hardware and software design requirements, and device selection and comfort evaluation. And living environment data integration is introduced in detail. We then tested the performance of the system in a specific application of the system in a real residential environment, using data parameters collected at different points in time as experimental data. Finally, it is concluded that the fuzzy close fusion algorithm used in the experiment can obtain data parameter values that are in good agreement with the real values, and the error range is controlled within 0–0.01; the indoor environment comfort is judged by 1 as the standard. $PMV>1$ indicates that the comfort level is excellent, and in the test experiment, each parameter value at 5 time points is all > 1, indicating that the indoor environment comfort level detected by the system is excellent.

The project management process has been used in the area of Software Engineering to support project managers to keep projects under control. One of the essential processes in Software Engineering is to conduct an accurate and reliable estimation of the required effort to complete the project. This article’s objectives are: i) to identify the variables that influence the estimation based on the correlation, and ii) to apply the Extreme Learning Machine - ELM model for effort estimation and compare it with the literature models. Thus, it was investigated which technique has better effort prediction accuracy. The models were compared with each other based on predictive precision in the criterion of absolute mean residue (MAR) and statistical tests. The main findings in this study were: i) important variables for effort estimation and; ii) the results indicated that the ELM model presents the best results compared to the models in the literature for estimating software design effort. In this way, the use of Machine Learning techniques in the effort estimation process can increase the chances of success in the accuracy of the time estimates and the project’s costs.

Three design principles are prominent in software development-encapsulation, data hiding, and separation of concerns. These principles are used as subjective quality criteria for both procedural and object-oriented applications. The purpose of research is to quantify encapsulation, data hiding, and separation of concerns is quantified using cyclomatic-based metrics. As a result of this research, the derived design metrics, coefficient of encapsulation, coefficient of data hiding, and coefficient of separation of concerns, are defined and applied to production software indicating whether the software has low or high encapsulation, data hiding, and separation of concerns.

Software system and conceptual design are highly abstract and functionally based. In recent years, the software system has been developing rapidly whereas the growth of hardware system is slow. However, it is difficult to transfer the knowledge from software to hardware for conceptual design due to the discipline gaps between software and hardware. Axiomatic design theory bridges software and hardware design conceptually; but lacks in further methodologies for transforming the software system structure to the axiomatic design matrix. This paper focuses on developing a methodology to conceptually design firmware which will help bridge the gap between software and hardware conceptual design. A conversion method between the axiomatic design matrix and the widely used UML sequence diagram was developed. This helps the designers identify Functional Requirements (FRs), Design Parameters (DPs) and their dependencies (i.e., Functional Couplings). In this methodology Functional Messages (FMs) are introduced, defined as the messages of UML sequence diagram and they are used for transition to axiomatic design matrix. DPs of design matrix are defined as the objects in the UML sequence diagram, and FRs of design matrix are generated by merging FMs depending on their flow of information in the sequence diagram. A case study was performed on software system of FDM 3D Printer to validate the proposed method. The UML Sequence diagram of the software system of FDM 3D Printer was successfully transformed into the design matrix. Then Design Coupling Sequence approach was applied to find the proper executable sequence to improve the software design concept of the 3D printer and innovation opportunities were suggested. By using this method, the Software system architecture of FDM 3D Printer was improved conceptually by decoupling the highly coupled DPs, which makes the system more efficient by reducing the build time of a 3D printed part.

Today, the problem of ensuring the effectiveness of the system of testing weapons and military equipment remains relevant. According to the existing national legislation and the accepted standards, separate specialized institutions are involved in the testing of samples of armaments and military equipment. One of the methods of improving the efficiency of test centers and institutions is the automation of all processes that accompany the testing of samples of weapons, military equipment and special equipment. The article highlights the approaches to the design and practical implementation of the information system to support the testing of weapons and military equipment. Its possible functional composition is considered. It is assumed that the information system should automate all processes in the test facility that are somehow related to the tests.Based on the analysis of existing guidance documents and scientific and technical information sources, the composition of the main functional components of the information system of test support is proposed. The necessity of introducing a management component into the information system for the implementation of a targeted approach to the management of a testing facility is substantiated. Reclassification of tasks of information databases on stages of carrying out tests is done. Based on the generalized scheme of testing the conceptual model of information system of support of tests is offered.The approximate composition of individual software modules and the content of databases are given.The expediency of using a spiral model of software design for the development of a comprehensive full-featured information system for test support is substantiated. It is expected that the automation of planning, conducting and other processes that accompany the tests can significantly affect the overall efficiency of the organization and conduct of tests, ensure the proper quality of the results and help reduce time losses for testing.

The ability of the software to easily understand it is very important, to evaluate the performance of a system or process a certain mechanism is needed. So that the achievement level of software development is obtained, the assessment of code quality and design in the metrics have different contributions to the quality properties of software design. The assessment of software characteristics is described in a model based on the Chidamber Kemerer (CK) Entropy Metrics design property indicator. Measure specific properties of the software by mapping them into numbers according to objective and well-defined measurement rules. To be able to help perform the software quality calculation process based on CK metrics on the eclipse equinox data by using the Mamdani fuzzy inference system, pointing the classification into low which can be interpreted as having good quality. And the value affirmation of the deffuzzyfication method in this case is done by using the COA (center of area) method, to determine the crisp x value, obtained from the membership function formed from the composition process of all outputs.

In this chapter, the authors delve into the domain of the object‐oriented (OO) approach to software design and object‐oriented programming (OOP), which helps with software system modeling. They delve into the OOP properties of C++, starting with OOP concepts and then examining code examples. OOP is based on the four principles: encapsulation, inheritance, polymorphism, and abstraction. The authors provide a closer look at the internal structure of a class. The construction portion of the class contains the special member functions: default constructor, parametric constructor, copy constructor, assignment operator, and destructor. A class's data and member functions can be assigned to the private or public groups. If not explicitly assigned, then by default, members of a class are private. The authors explain how to make another class, this time to represent complex numbers: two valued entities with their own arithmetic rules, which are used e.g. in electronics and physics.

Accessible chromatin is a highly informative structural feature for identifying regulatory elements, which provides a large amount of information about transcriptional activity and gene regulatory mechanisms. Human ATAC-seq datasets are accumulating rapidly, prompting an urgent need to comprehensively collect and effectively process these data. We developed a comprehensive human chromatin accessibility database (ATACdb, http://www.licpathway.net/ATACdb), with the aim of providing a large amount of publicly available resources on human chromatin accessibility data, and to annotate and illustrate potential roles in a tissue/cell type-specific manner. The current version of ATACdb documented a total of 52 078 883 regions from over 1400 ATAC-seq samples. These samples have been manually curated from over 2200 chromatin accessibility samples from NCBI GEO/SRA. To make these datasets more accessible to the research community, ATACdb provides a quality assurance process including four quality control (QC) metrics. ATACdb provides detailed (epi)genetic annotations in chromatin accessibility regions, including super-enhancers, typical enhancers, transcription factors (TFs), common single-nucleotide polymorphisms (SNPs), risk SNPs, eQTLs, LD SNPs, methylations, chromatin interactions and TADs. Especially, ATACdb provides accurate inference of TF footprints within chromatin accessibility regions. ATACdb is a powerful platform that provides the most comprehensive accessible chromatin data, QC, TF footprint and various other annotations.

Context.—Tumor reporting constitutes a significant daily task of pathologists. An efficient tumor-reporting methodology is thus vitally important. The Web dynamic form (WbDF) method offers a multitude of advantages over the prevailing transcription-mediated reporting method based on static-text checklists. However, its adaptation has been severely hampered for 2 decades by its costly needs to maintain a complex back-end system and to change the system for frequent updates of reporting content.Objective.—To overcome these 2 obstacles with a serverless Web platform that enables users to create, customize, use, and download WbDFs as synoptic templates for structured tumor reporting.Design.—Deploy ReactJS as a Web platform. Create form components in JavaScript Object Notation files. Use JavaScript Object Notation files to make WbDFs on the Web platform. Use the WbDFs to generate final pathology reports.Results.—Ordinary users (pathologists) can create/customize reporting templates as WbDFs on the Web platform. The WbDF can be used to make a pathology report and stored/shared like ordinary document files. There is no back-end system to change, nor a requirement for computer programming skills.Conclusions.—This strategy eliminates the need for a complex back-end system and the associated cost when updating tumor-reporting standards, making it possible to adopt the WbDF method without the technological drawbacks associated with content updates. It also opens a new field of how the tumor-reporting system should be organized, updated, and implemented.

Computer physics communications 270, 108138 (2022). doi:10.1016/j.cpc.2021.108138, CMInject simulates nanoparticle injection experiments of particles with diameters in the micrometer to nanometer-regime, e.g., for single-particle-imaging experiments. Particle-particle interactions and particle-induced changes in the surrounding fields are disregarded, due to low nanoparticle concentration in these experiments. CMInject's focus lies on the correct modeling of different forces on such particles, such as fluid-dynamics or light-induced interactions, to allow for simulations that further the scientific development of nanoparticle injection pipelines. To provide a usable basis for this framework and allow for a variety of experiments to be simulated, we implemented first specific force models: fluid drag forces, Brownian motion, and photophoretic forces. For verification, we benchmarked a drag-force-based simulation against a nanoparticle focusing experiment. We envision its use and further development by experimentalists, theorists, and software developers., Published by North Holland Publ. Co., Amsterdam

Context: Design smell detection has proven to be a significant activity that has an aim of not only enhancing the software quality but also increasing its life cycle. Objective: This work investigates whether machine learning approaches can effectively be leveraged for software design smell detection. Additionally, this paper provides a comparatively study, focused on using balanced datasets, where it checks if avoiding dataset balancing can be of any influence on the accuracy and behavior during design smell detection. Method: A set of experiments have been conducted-using 28 Machine Learning classifiers aimed at detecting God classes. This experiment was conducted using a dataset formed from 12,587 classes of 24 software systems, in which 1,958 classes were manually validated. Results: Ultimately, most classifiers obtained high performances,-with Cat Boost showing a higher performance. Also, it is evident from the experiments conducted that data balancing does not have any significant influence on the accuracy of detection. This reinforces the application of machine learning in real scenarios where the data is usually imbalanced by the inherent nature of design smells. Conclusions: Machine learning approaches can effectively be used as a leverage for God class detection. While in this paper we have employed SMOTE technique for data balancing, it is worth noting that there exist other methods of data balancing and with other design smells. Furthermore, it is also important to note that application of those other methods may improve the results, in our experiments SMOTE did not improve God class detection. The results are not fully generalizable because only one design smell is studied with projects developed in a single programming language, and only one balancing technique is used to compare with the imbalanced case. But these results are promising for the application in real design smells detection scenarios as mentioned above and the focus on other measures, such as Kappa, ROC, and MCC, have been used in the assessment of the classifier behavior. © 2021 The Authors open access

Database schema design has a significant importance in software design. There are lots of tools and methods available for schema design in RDBMS but limited attention is given in NoSQL for schema design as it is emerging in database technology. NoSQL requires a different approach in designing efficient schema, such as in the document database which information should be stored as embedded document, or which information should be stored as referenced document. There are certain thumb rules for schema design in NoSQL databases. In reengineering projects, especially in Old RDBMS to new NoSQL system, developing good and efficient database schema is a very difficult task. In this paper, we have proposed a schema design advisor model which uses the existing software’s SQL queries load as an input along with an algorithm for schema design recommendation. Also, we have proposed a cost model for various schemas created by recommendation model. The proposed model is implemented through a prototype for the MongoDB document database in Java. The prototype produces all possible combinations of schemas and calculates cost of each schema. Automated schema design process produces all possible combinations of NoSQL schemas, which is difficult with manual schema design approach.

Background/Objectives: The main purpose is to find the significance of Object-Oriented metrics on software design; metrics are related to minimizing class unused attributes and methods to maintain quality and complexity.Methods/Statistical analysis: Experimental analysis is utilized for validating findings. Mathematical properties are used for validation and evaluation outcomes. The purpose of experimental validation is to understand whether a measurement quantifies what it should quantify. MS-Excel is utilized as a metric computation and graph generation for fifteen project designs. Statistical analysis through SPSS tool of different inheritance categories as single, multiple, multilevel, hierarchical, and hybrid are utilized for metric results.Findings: SSAAM is suggested to give measurement results for counting public and protected attributes of all super and subclasses in the class inheritance hierarchy. SSMAM explores numeric value for computing public and protected methods of all super and sub classes in the class inheritance hierarchy. Higher results are computed of SSAAM and SSMAM, it shows more inheritance hierarchy utilized in the design. It assist in a controlled use of public/protected members in software design to minimize complications. Software design complications can be enhanced due to more use of protected and public members as well as decreased use of the concept of encapsulation. Keywords: Metrics; quality; protected and public specifiers

Refactoring improves he software design while preserving overall functionality and behavior, and is an important technique in managing the growing complexity of software systems. This disclosure introduces an interactive way to refactor software systems using innovization and interactive dynamic multi-objective optimization. The interactive approach supports the adaption of refactoring solutions based on developer feedback while also taking into account other code changes that the developer may have performed in parallel with the refactoring activity.

ContextSoftware design in e-commerce can be improved with user data through controlled experiments (i.e. A/B tests) to better meet user needs. Machine learning-based algorithmic optimization techniques extends the approach to large number of variables to personalize software to different user needs. So far the optimization techniques has only been applied to optimize software of low complexity, such as colors and wordings of text.ObjectiveIn this paper, we introduce the COMBO toolkit with capability to model optimization variables and their relationship constraints specified through an embedded domain-specific language. The toolkit generates personalized software configurations for users as they arrive in the system, and the configurations improve over time in in relation to some given metric. COMBO has several implementations of machine learning algorithms and constraint solvers to optimize the model with user data by software developers without deep optimization knowledge.MethodThe toolkit was validated in a proof-of-concept by implementing two features that are relevant to Apptus, an e-commerce company that develops algorithms for web shops. The algorithmic performance was evaluated in simulations with realistic historic user data.ResultsThe validation shows that the toolkit approach can model and improve relatively complex features with many types of variables and constraints, without causing noticeable delays for users.ConclusionsWe show that modeling software hierarchies in a formal model facilitates algorithmic optimization of more complex software. In this way, using COMBO, developers can make data-driven and personalized software products.

Virtual reality (VR) has re-emerged as a low-cost, highly accessible consumer product, and training on simulators is rapidly becoming standard in many industrial sectors. However, the available systems are either focusing on gaming context, featuring limited capabilities or they support only content creation of virtual environments without any rapid prototyping and modification. In this project, we propose a code-free, visual scripting platform to replicate gamified training scenarios through rapid prototyping and VR software design patterns. We implemented and compared two authoring tools: a) visual scripting and b) VR editor for the rapid reconstruction of VR training scenarios. Our visual scripting module is capable of generating training applications utilizing a node-based scripting system, whereas the VR editor gives user/developer the ability to customize and populate new VR training scenarios directly from the virtual environment. We also introduce action prototypes, a new software design pattern suitable to replicate behavioral tasks for VR experiences. In addition, we present the training scenegraph architecture as the main model to represent training scenarios on a modular, dynamic and highly adaptive acyclic graph based on a structured educational curriculum. Finally, a user-based evaluation of the proposed solution indicated that users—regardless of their programming expertise—can effectively use the tools to create and modify training scenarios in VR.

During the object-oriented software design phase, the designers have to describe the dynamic aspect of the system under development through the most common interaction diagram variant in UML 2.0, i.e. sequence diagrams. Some novice designers, including undergraduate and postgraduate students, suffer from making inappropriate models due to insufficiently detailed guidance required to develop such sequence diagrams. This paper classifies some potential mistakes which are likely performed by such novice designers, and discusses the corresponding corrections. We summarized such mistakes based on our long experiences in teaching software modeling classes as well as software analysis and design classes. There were classified twenty-one potential mistakes with respect to the syntactical and semantical correctness of the developed models. It is concluded that novice designers have to be aware and take into account the identified mistakes in such a way they can produce correct sequence diagrams.

Code smells are generally not considered as bugs; instead, they point out certain shortcomings in the software design or code. Identification of code smell is a necessary step for improving the sof...

Context.— Smart glasses are a wearable technology that enable hands-free data acquisition and entry. Objective.— To develop a surgical pathology grossing application on a smart glass platform. Design.— An existing logistics software for the Google Glass Enterprise smart glass platform was used to create surgical pathology grossing protocols. The 2 grossing protocols were developed to simulate grossing a complex (heart) and a simple (kidney) specimen. For both protocols, users were visually prompted by the smart glass device to perform each task, record measurements, or document the field of view. In addition to measuring the total time of the protocol performance, each substep within the protocol was automatically recorded. Subsequently, a report was generated that contained the dictation, images, voice recordings, and the timing of each step. The application was tested by 3 users using the 2 grossing protocols. The users were tracked across 3 grossing procedures for each protocol. Results.— For the complex specimen grossing the average time across repeated procedures was not significantly different between users (P > .99). However, when grossing times of the complex specimen were compared for repeated performances of the same user, a significant reduction in grossing times was observed with each repetition (P = .002). For the simple specimen, the average grossing time across multiple attempts was different among users (P = .03); however, no improvement in grossing time was observed with repeated performance (P = .499). Conclusions.— Augmented reality based grossing applications can provide automated data collection to track the changes in grossing performance over time.

Nowadays software control large majority of systems that humankind use. Systems that software is used widely, such as transportation, military, medicine and avionics must be safe during operation. Fail in these critical systems may cause catastrophic results (i.e. loss of human life, loss or severe damage to environment or equipment etc.). In order to avoid failure on safety critical systems or at least mitigate risks detailed testing is required. Many safety critical systems are developed with sequential phases and tested with test last approach. But test last approach is not sufficient when requirements are unclear or changed. To overcome weaknesses of test last approach we propose test driven approach for safety critical software development, regulated by IEC 61508 standard. A systematic analysis of IEC 61508 software requirements against proposed approach showed that the approach directly supports some objectives and partially supports some of them. Supported objectives are safety requirement identification, simple and testable software design, verification and validation. In general introduced approach suits regulated software development well and this paper outlines these details.

The construction of models of system behavior is of great importance throughout science and engineering. In bioengineering and bionanotechnology, these often take the form of dynamic models that specify the evolution of different species over time. To ensure that scientific observations and conclusions are consistent and that systems can be reliably engineered on the basis of model predictions, it is important that models of biomolecular systems can be constructed in a reliable, principled, and efficient manner. This review focuses on efforts to address this need by using domain-specific programming languages as the basis for custom design tools for researchers working on computational nucleic acid devices, where a domain-specific language is simply a programming language tailored to a particular application domain. The underlying thesis of our review is that there is a continuum of practical implementation strategies for computational nucleic acid systems, which can all benefit from appropriate domain-specific languages and software design tools. We emphasize the need for specialized yet flexible tools that can be realized using domain-specific languages that compile to more general-purpose representations.