Entire Software Research Articles

Анализ угроз информационной безопасности и защита данных в системах «умный дом»

The idea of smart homes has been around for several decades and has been described by different authors many times since then. However, there are almost always three aspects in the definitions of the last 20 years. First, home devices must be connected, not only to each other, but also to the Internet. Second, an intelligent way to manage the system is needed, such as a central gateway or smart smartphone apps. Finally, there must be some degree of home automation in the system. A hardware and software complex that meets these requirements can be called a “smart home” system. The system of ensuring the security of the "smart home" is now of great practical importance, which should include measures to protect the IT infrastructure, ensuring the personal safety of residents, ensuring their health, the sanitary condition of the premises, as well as the safety of material assets. It follows from this that the problem of the lack of a thorough study of information security threats and the elaboration of protection of the entire software and hardware complex of the "smart home" system is quite urgent. When solving this problem, an analysis of the main types and characteristics of smart home systems was carried out, and their key vulnerabilities were identified. Also, a study of vulnerabilities in the hardware of smart home systems was carried out; A qualitative assessment of the information security risks of a "smart home" has been carried out and protective measures have been developed to reduce them; A prototype of a fragment of the “smart home” security system has been developed and studied. In an experimental study of threats and vulnerabilities of the developed prototype of a fragment of the "smart home" system, the threat of interception of critical information of the system was studied in detail. Based on the results of the development and research of the Security Inspector, conclusions were drawn about the effectiveness of the use of the intrusion detection module.

A Distributed Virtual Reality System Based on Real-Time Dynamic Calculation and Multi-Person Collaborative Operation Applied to the Development Of Subsea Production Systems

To train inexperienced workers for the construction, production, and maintenance of subsea production systems, a virtual reality simulation platform was developed. The entire framework, software, and hardware platforms of the system were designed and introduced. A multi-person collaborative simulation was achieved based on the high-level architecture protocol. The real-time dynamic calculation software Vortex was used to add physical properties to each geometrical model and set collision detections and motion constraints so that the VR system can reflect the real motion response of the structures in real-time during virtual simulation. Visual simulation software Vega Prime and Vortex were integrated to realise the real-time rendering and drawing of virtual ocean engineering scenes. Thus, a virtual simulation system with large-scale complex scenes based on real-time dynamic calculation and multi-person collaborative operation was established. A typical ocean engineering case of subsea manifold installation was simulated using the virtual simulation system, and the detailed simulation flow was explained. A multibody dynamics system of the ship-cable-subsea manifold was established using Orcaflex to obtain the accurate motion response of the subsea manifold during lowering. In the virtual simulation process, the obtained hydrodynamic calculation results can provide an important guideline and reference to the operators. The developed simulation system is a suitable tool for training ocean engineering workers and realistically simulating ocean operation cases.

Finger Vein Recognition System Based on Convolutional Neural Network and Android

With the rapid development of science and technology, biotechnology has developed rapidly. Among the many biometric technologies, finger vein technology has the characteristics of vitality, portability, and non-replicability, so it is considered to be the most promising biometric technology. However, the accuracy of finger vein recognition is affected by the collection device, the surrounding temperature and the algorithm. The flaws cannot be applied to real life on a large scale. This paper designs a finger vein recognition system based on convolutional neural network and Android, which mainly includes the following three parts. First, the system hardware includes the design of the acquisition device, the selection of the core development board and the display screen. Second, the design of the entire system software architecture is based on the MVVM architecture, which ensures low coupling of the program and is easy for later expansion and maintenance. The software includes collection function, recognition function and administrator function. Finally, a lightweight neural network is proposed for finger vein feature extraction, and proposed a storage method based on MMKV to meet the real-time performance of the system.

Performance optimization opportunities in the Android software stack

The smartphone hardware and software ecosystems have evolved very rapidly. Multiple innovations in the system software, including OS, languages, and runtimes have been made in the last decade. Although, performance characterization of microarchitecture has been done, there is little analysis available for application performance bottlenecks of the system software stack, especially for contemporary applications on mobile operating systems.In this work, we perform system utilization analysis from a software perspective, thereby supplementing the hardware perspective offered by prior work. We focus our analysis on Android powered smartphones, running newer versions of Android. Using 11 representative apps and regions of interest within them, we carry out performance analysis of the entire Android software stack to identify system performance bottlenecks.We observe that for the majority of apps, the most time-consuming system level thread is a frame rendering thread. However, more surprisingly, our results indicate that all apps spend a significant amount of time doing Inter Process Communication (IPC), hinting that the Android IPC stack is a ripe target for performance optimization via software development and a potential target for hardware acceleration.

Test Oracle Generation Based on BPNN by Using the Values of Variables at Different Breakpoints for Programs

Automatic test oracle generation is a bottleneck in realizing full automation of the entire software testing process. This study proposes a new method for automatically generating a test oracle for a new test input on the basis of several historical test cases by using a backpropagation neural network (BPNN) model. The new method is different from existing test oracle techniques. Specifically, our method has two steps. First, the values of variables are collected as training data when several historical test inputs are used to execute the program at different breakpoints. The test oracles (pass or fail) of these test cases are utilized to classify and label the training data. Second, a new test input is used to execute the program at different breakpoints, where the trained BPNN prediction model automatically generates its test oracle on the basis of the collected values of the variables involved. We conduct an experiment to validate our method. In the experiment, 113 faulty versions of seven types of programs are used as experimental objects. Results show that the average prediction accuracy rate of 74,651 test oracles is 95.8%. Although the failed test cases in the training data account for less than 5%, the overall average recall rate (prediction accuracy of test case execution failure) of all programs is 78.9%. Furthermore, the trained BPNN can reveal not only the impact of the values of variables but also the impact of the logical correspondence between variables in test oracle generation.

Effects of common requirements engineering techniques on requirements engineering success in agile environments: A case study from Sri Lanka

Requirements engineering is the process of exploring, analyzing, documenting and handling the needs to be facilitated through a computer-based system that is being developed. Though software solutions fail due to many reasons, Flawed Requirements Engineering (RE) is one of the main causes leading to failure of software projects especially in agile environments where requirements and solutions evolve through collaboration between self-organizing cross-functional teams. Therefore, succeeding in RE is an essential factor which influences success of the entire software project. In the light of achieving project success, various methods have been introduced to deal with RE. Main aim of this study is to explore the relationship between commonly used techniques and successful agile requirements engineering in agile environments with a special emphasis to Sri Lankan context. A secondary objective was to suggest innovative recommendations to software solution developers to achieve RE success. Five research questions were formulated to explore the relationship between mostly common techniques of requirements management and success of agile requirements engineering. Through key readings related to agile project development, authors have identified five key success factors as having an influence on successful project completion in an agile environment and are being tested in this research. Authors have designed the study taking an epistemological standpoint of positivism, using quantitative methods and case study strategy to derive conclusions. The entire population 130 employees of the case organization been considered for this study. The quantitative analysis of was conducted based on 105 valid responses gained through a five-point Likert scaled questionnaire from the case organization. It has been discovered that these common requirement engineering techniques are correlated with project success in agile environments. Further, scrutiny of each requirements engineering phase, led to finding a set of most effective techniques to be utilized in an agile environment contributing to software development project success.
 Keywords: Requirements engineering, agile software development, project failures

The design and implementation of GECAM satellite payload performance monitoring software

Background The Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is primarily designed to spot gamma-ray bursts corresponding to gravitational waves. In order to achieve stable observations from various astronomical phenomena, the payload performance need to be monitored during the in-orbit operation. Method This article describes the design and implementation of GECAM satellite payload performance monitoring (GPPM) software. The software extracts the payload status and telescope observations (light curves, energy spectrums, characteristic peak fitting of energy spectrums, etc) from the payload data. Considering the large amount of payload status parameters in the engineering data, we have designed a method of parameter processing based on the configuration tables. This method can deal with the frequent changes of the data formats and facilitate program maintenance. Payload status and performance are monitored through defined thresholds and monitoring reports. The entire software is implemented in python language and the huge amount of observation data is stored in MongoDB. Conclusion The design and implementation of GPPM software have been completed, tested with ground and in-orbit payload data. The software can monitor the performance of GECAM payload effectively. The overall design of the software and the data processing method can be applied to other satellites.

Serendipity in Library Retrieval: Reinforcing Discovery through Visualization of Bibliographic Relationships

This work starts with a background study of serendipity, its meaning in the context of information discovery, its interrelation with bibliographic relationships, and the technical possibilities for practical implementation of a relationships based visual navigation in a library discovery interface to achieve serendipitous resource discovery. The methodology for developing the prototype consists of two components – theoretical base and practical steps. The theoretical framework includes an indepth study of the concept of bibliographic relationships as proposed by experts, as reflected in bibliographic data models and as included in bibliographic formats and metadata schemas. The practical sides deal with the application of the theoretical framework in designing a prototype that, in addition to other typical retrieval features, supports visual navigational facility driven by bibliographic relationships. The components, tools and standards of the entire software architecture are all open source and open standards.

Factors Influencing the Software Development Process in Small Scale Industries

Software development is a complex process which is divided into many phases. According to the software type and industries the development process is restructured. During the entire development what are the main factors which is influencing the process and affecting the quality. The main objective of this study is to focus on factors influencing the development process and how it affects the small scale industries after coming in to the real practice.
 Entire Software development is a layered process in which different factors are responsible to get the best products. This paper is focused on different technical and non-technical influencing factors which give major impact on the software quality. With influencing factors, their applicability in small scale industries also studied.
 Three important technical factors i.e. SDLC model and its principles, Cost estimation and Risk parameter whereas two important influencing factors in non-technical.i.e. success factors and environmental factors. Non-technical factors more influencing than technical factors. 
 All technical and non-technical factors have their own role but to apply all these quality parameters in small scale industries we need to make them more easy for their applicability. If quality development process and its parameters are tuned to easy and affordable level more businessmen will shift from manual working environment to the digital working environment.

Autonomous Mission of Multi-UAV for Optimal Area Coverage.

This study proposes an entire hardware and software architecture from operator input to motor command for the autonomous area coverage mission using multiple unmanned aerial vehicles. Despite the rapid growth of commercial drone services, there are many limitations on operations, such as a low decision-making autonomy and the need for experienced operators to intervene in the whole process. For performing the area coverage mission more efficiently and autonomously, this study newly designs an optimization problem that allocates waypoints created to cover that area to unmanned aerial vehicles. With an optimized list of waypoints, unmanned aerial vehicles can fill the given areas with their footprints in a minimal amount of time and do not overlap each other during the mission. In addition, this study performs both various simulations for quantitative analysis and an outdoor experiment through real hardware implementation in order to verify the performance sufficiently. The methodologies developed in this study could be applied to endless applications using unmanned aerial vehicles equipped with mission-specific sensors.

Lags in the release, adoption, and propagation of npm vulnerability fixes

Security vulnerability in third-party dependencies is a growing concern not only for developers of the affected software, but for the risks it poses to an entire software ecosystem, e.g., Heartbleed vulnerability. Recent studies show that developers are slow to respond to the threat of vulnerability, sometimes taking four to eleven months to act. To ensure quick adoption and propagation of a release that contains the fix (fixing release), we conduct an empirical investigation to identify lags that may occur between the vulnerable release and its fixing release (package-side fixing release). Through a preliminary study of 231 package-side fixing release of npm projects on GitHub, we observe that a fixing release is rarely released on its own, with up to 85.72% of the bundled commits being unrelated to a fix. We then compare the package-side fixing release with changes on a client-side (client-side fixing release). Through an empirical study of the adoption and propagation tendencies of 1,290 package-side fixing releases that impact throughout a network of 1,553,325 releases of npm packages, we find that stale clients require additional migration effort, even if the package-side fixing release was quick (i.e., package-side fixing releasetypeSpatch). Furthermore, we show the influence of factors such as the branch that the package-side fixing release lands on and the severity of vulnerability on its propagation. In addition to these lags we identify and characterize, this paper lays the groundwork for future research on how to mitigate propagation lags in an ecosystem.

Data Membership Identification using Bloom Filter in Cloud Storage for Effective Resource Allocation

Cloud computing has recently been the buzz word that had changed the entire software industry with its PaaS, IaaS and SaaS architecture model. The legacy systems operational in the organizations across different industries have been using the database that had an overhead in terms of cost of data storage, runtime operation and frequent data maintenance. Cloud database concept had challenged the existing storage and operational norms of data. In the distributed environment, resources used in the cloud databases need to identify whether the requested data belongs to the data nodes of a cluster. With databases began to be ubiquitous, the data storage needed to satisfy heterogeneous data structures rather the unstructured data storage support is looked for. The Use of Bloom's filter for data membership identification is the novel approach and can effectively improve the resource organization strategy on cloud. Dynamic resource organization can further improve the query efficiency as well. The concern raised during this is the data privacy which can also be ascertain by maintaining the data access authority levels. Bloom filter uses less memory space against the large dataset to store it's information. A Bloom filter is proposed to be used to determine whether an element is part of a reference set. It is a very compact hash-based data structure with efficient look-up times and a manageable risk of giving false positives.

Industry 4.0 technologies incorporated with Delta PLC based Smart Home Automation for Rural Development

The Programmable Logic Controller (PLC) is commonly used for electromechanical process automation. A home automation system is being developed using PLC. The proposed control module will consist of Model Functional Blocks device emulation. Upgrading human standards of living is the most important source of inspiration for the continuation of technological advances. Technology innovation directly and indirectly offers and enhances the protection and comfort of human beings. The advancement of technology for this reason directly affects the quality of living through the design of smart home systems. Smart home systems can be classified as local and remote in two ways. In this research, a smart home automation system design was carried out by using Delta PLC (Programmable Logic Controller). The control module provides fault detection, tolerance and switching on or off in sensitive areas for multiple components. Combining the PLC model with other devices, such as GSM is also possible. By supplying voice control and protection products, such a form of application would be highly helpful for the elderly and disabled persons. World is developing increasingly across the Internet of Things (IoT). In this paper, we are designing a system that will track home appliances automatically and generate email or messanger notifications or make smart decisions using the IoT model. The key contribution of this paper is that it summarizes the use of IoT to track and regulate the market in industries with artificial intelligence. By optimizing the entire hardware assembly and software algorithms, the Delta PLC device is adjustable to satisfy demands, incorporating distinct home appliances in a short time. The PLC is simple to understand, and by using a single model, the system offers several solutions. The PLC will become the epic center for many new applications, as it is new but more powerful than previous systems.

ACTUALITY OF CONDUCTING MODULAR TESTING IN SOFTWARE DEVELOPMENT

The testing process in creating software, as a separate stage, has its own life cycle. The testing lifecycle is part of the entire software cycle, and they must be synchronized with each other. Designing and developing testing in creating new software systems is a complex and time consuming task. The work of any software system is organized as a set of modules that can perform various functions. To ensure the correct operation of the system as a whole, you must first test each software module separately. In case of defects, this procedure will make it easier to identify the problem in the modules and completely eliminate the relevant shortcomings. Testing all modules separately is called modular testing. The article examines the main aspects of modular testing. The software life cycle is considered and the stages of the computer program development cycle are graphically presented. It is investigated that one of the most important stages is the stage software testing. The main definitions concept of "testing" are analyzed in detail and the main types of testing process are listed. It is established that modular testing is one of the most important types of testing. Modular testing is considered to be the simplest step in testing the entire system because the modules to be tested are usually small in size. When using this method, the complexity of creating test cases increases. To put the whole system into operation, you need to set the values of the test variables correctly, and to bring part of the real system to the required state, you need to run the whole scenario. However, modular testing is associated with significant problems, which are explored in the article. The main tasks and approaches to modular testing are evaluated. The article thoroughly reveals the characteristics of modular testing as a method of structural testing.

K-Step Crossover Method based on Genetic Algorithm for Test Suite Prioritization in Regression Testing

Software is an integration of numerous programming modules  (e.g., functions, procedures, legacy system, reusable components, etc.) tested and combined to build the entire module. However, some undesired faults may occur due to a change in modules while performing validation and verification. Retesting of entire software is a costly affair in terms of money and time. Therefore, to avoid retesting of entire software, regression testing is performed. In regression testing, an earlier created test suite is used to retest the software system's modified module. Regression Testing works in three manners; minimizing test cases, selecting test cases, and prioritizing test cases. In this paper, a two-phase algorithm has been proposed that considers test case selection and test case prioritization technique for performing regression testing on several modules ranging from a smaller line of codes to huge line codes of procedural language. A textual based differencing algorithm has been implemented for test case selection. Program statements modified between two modules are used for textual differencing and utilized to identify test cases that affect modified program statements. In the next step, test case prioritization is implemented by applying the Genetic Algorithm for code/condition coverage. Genetic operators: Crossover and Mutation have been applied over the initial population (i.e. test cases), taking code/condition coverage as fitness criterion to provide a prioritized test suite. Prioritization algorithm can be applied over both original and reduced test suite depending upon the test suite's size or the need for accuracy. In the obtained results, the efficiency of the prioritization algorithms has been analyzed by the Average Percentage of Code Coverage (APCC) and Average Percentage of Code Coverage with cost (APCCc). A comparison of the proposed approach is also done with the previously proposed methods and it is observed that APCC & APCCc values achieve higher percentage values faster in the case of the prioritized test suite in contrast to the non-prioritized test suite.

Optimal Operating Point of a Hydrogen Fueled SOFC Models Using Al-Nour Software

The solid oxide fuel cell (SOFC) is considered extremely suitable for electrical power plant application. Both high temperature (HT) and intermediate temperature (IT) SOFC performances are investigated using models which are built in Aspen customer modeller. Moreover, this paper introduces a new simulation software, called Al-Nour V.1.0-2012 software application. The interface of Al-Nour V.1.0-2012 software was mainly implemented based on the educational theory of User’s Split Attention, that is; the entire software works with only one screen for all operations without any scrolling (user-friendly interface). This application reflects the fact that Al-Nour software does not require the user to have any previous training. The performance of HT-SOFC and IT-SOFC models is evaluated and compared using both software applications . The simulation results show that, the cell voltage value increases by raising the operating pressure, operating temperature, and hydrogen partial pressure. The electrical power output value from the SOFC is increased simultaneously by increasing the current density . Furthermore, the IT-SOFC has a higher cell voltage than the HT-SOFC.

Optimize Continuous Integration and Continuous Deployment in Azure DevOps for a controlled Microsoft .NET environment using different techniques and practices

Delivering a software is not a simple process, even if it is a completely new software created from the scratch, the enhancement of an existing software or fixing the bugs of an existing application. As per the new industrial standard most of the companies follow the DevOps methodologies to deliver the software products, which leverage the flexibilities of the software delivery with expected quality on time with minimal errors. One of the most important factors of the DevOps methodology is Continuous Integration and Continuous Deployment. As the entire software industry is moving towards Cloud Computing one of the most powerful, cost effective and easily maintainable environment to host the software applications. There are various Cloud computing providers available in the industry now. Most of them have its own advantage and dis-advantages. There are many researches going on various topics on these areas and the importance of these topics are getting more relevant in the industry now. There are lot of gaps on the Continuous Integration and Continuous Deployment concepts and more improvement options have to be identified and certified throughout the various researches. To understand the importance of this platform, we decided to concentrate the research on the Continuous Integration and Continuous Deployment in Azure DevOps for a controlled Microsoft .NET environment using different techniques and practices. Here our intention is to identify the various factors which helps the industry to do a better Continuous Integration and Continuous Deployment in the Azure DevOps for a controlled Microsoft .NET environment using different techniques and practices. Among the “n” number of factors identified on this subject, only couple of factors are considered as part of this research.

Probabilistic Estimation of Threat Intrusion in Embedded Systems for Runtime Detection

With billions of networked connected embedded systems, the security historically provided by the isolation of embedded systems is no longer sufficient. Millions of new malware are created every month and zero-day attacks are becoming an increasing concern. Therefore, proactive security measures are no longer enough to provide protection to embedded systems. Instead, reactive approaches that detect attacks that can circumvent the proactive defenses and react upon them are needed. Anomaly-based detection is a common reactive approach employed to detect malware by monitoring anomalous deviations in the system execution. Timing-based anomaly detection detects malware by monitoring the system's internal timing, which offers unique protection against mimicry malware compared to sequence-based anomaly detection. However, previous timing-based anomaly detection methods focus on each operation independently at the granularity of tasks, function calls, system calls, or basic blocks. These approaches neither consider the entire software execution path nor provide a quantitative estimate of the presence of malware. This article presents a novel model for specifying the normal timing for execution paths in software applications using cumulative distribution functions of timing data in sliding execution windows. A probabilistic formulation is used to estimate the presence of malware for individual operations and sequences of operations within the paths. Operation and path-based thresholds are determined during the training process to minimize false positives. Finally, the article presents an optimization method to assist system developers in selecting which operations to monitor based on different optimization goals and constraints. Experimental results with a smart connected pacemaker, an unmanned aerial vehicle, and seven sophisticated mimicry malware implemented at different levels demonstrate the effectiveness of the proposed approach.

IDCube Lite: Free Interactive Discovery Cube software for multi- and hyperspectral applications.

Multi- and hyperspectral imaging modalities encompass a growing number of spectral techniques that find many applications in geospatial, biomedical, machine vision and other fields. The rapidly increasing number of applications requires convenient easy-to-navigate software that can be used by new and experienced users to analyse data, and develop, apply and deploy novel algorithms. Herein, we present our platform, IDCube Lite, an Interactive Discovery Cube that performs essential operations in hyperspectral data analysis to realise the full potential of spectral imaging. The strength of the software lies in its interactive features that enable the users to optimise parameters and obtain visual input for the user in a way not previously accessible with other software packages. The entire software can be operated without any prior programming skills allowing interactive sessions of raw and processed data. IDCube Lite, a free version of the software described in the paper, has many benefits compared to existing packages and offers structural flexibility to discover new, hidden features that allow users to integrate novel computational methods.

An Open Source Platform for Computational Histopathology

Computational histopathology is a fast emerging field which converts the traditional glass slide based department to a new examination platform. Such a paradigm shift also brings the in silico computation to the field. Much research have been presented in the past decades on the algorithm development for pathology image analysis. On the other hand, a comprehensive software platform with advanced visualization and computation capability, large developer community, flexible plugin mechanism, and friendly transnational license, would be extremely beneficial for the entire community. In this work, we present SlicerScope: an open platform for whole slide histopathology image computing based on the highly successful 3D Slicer. We present rationale on the choice of such an architecture, introducing new modules/tools for giga-pixel whole slide image viewing, and four specific analytical modules for qualitative presentation, nucleus level analysis, tissue scale computation, and 3D pathology. The entire software is publicly available at https://slicerscope.github.io/ , facilitating the algorithmic, clinical, and transnational researches.