Properties Of Software Research Articles

Virtual Reality Software: empowering tourism marketing through technology

ABSTRACT The dynamic evolution of consumer demands in the tourism sector necessitates continual adaptation and innovation in marketing strategies to counter increasing competitiveness. To address these shifts, emerging technologies play a pivotal role. This study focuses on the investigation of Information and Communication Technologies (ICTs) in shaping tourism marketing, culminating in the development of Tour View 360° software. Employing qualitative research methods, including bibliographical analysis and technological prospecting, the study identified prerequisites for the software's creation. Leveraging the Scrum framework for its adaptability, the software was meticulously designed using C# programming language with Unity 3D software. Findings reveal the early-stage adoption of interactive virtual reality technologies for promoting tourism. Nonetheless, Tour View 360° emerges as an innovative tool. The study comprehensively details the software's attributes, functionalities, interfaces, requirements, usability configurations, and final modeling, offering insights into ICT integration in enhancing tourism marketing strategies.

How accessibility affects other quality attributes of software? A case study of GitHub

How accessibility affects other quality attributes of software? A case study of GitHub

Development and validity of the expectations of physiotherapists questionnaire on practice management software.

Despite the growing trend in the use of digital technologies in physiotherapy, the overall adoption of both, practice management software (PMS) and electronic health records in physiotherapy clinics has been low and slow over time. In order to learn what factors determine the adoption of these technologies by physiotherapists, there is a need to examine the expectations of physiotherapists (EPs) on specific software attributes. The main aims of this study were to develop a questionnaire to measure and describe the EPs towards PMS. The knowledge of these EPs will be useful to guide PMS design in order to improve physiotherapists' satisfaction. Instrument development study with validity and reliability testing. The development of this questionnaire was conducted in three phases: identification of attributes to be explored, development of the items, pilot study, and psychometric testing. The questionnaire was distributed to chartered physiotherapists. A total of 272 participants completed the questionnaire. A series of analysis were conducted to assess item reduction, factor structure of the questionnaire and metric properties of multi-item scales. From the initial 43 attributes, the final version of the questionnaire consisted of 26 items on EPs, grouped in nine scales and two areas (clinical care and administrative activities). As a result, all scores had strong item-scale correlations, excellent item scaling success, and good internal consistency (Cronbach alpha coefficients of >.7). Our study also showed that current EPs were high towards most of the items, only two scales concentrated most of the attributes with the least expectations (monitoring quality of care and digital health interventions). Our study included physiotherapists with and without experience with PMS, and it showed that both groups had a similar pattern of expectations. Our study provides a valuable questionnaire of EP on PMS attributes for clinical care and administrative activities and shows a detailed development process.

Use of software for automation of academic libraries in Sialkot

PurposeThe aim of this study was to investigate the use of software for the automation of academic libraries in Sialkot. This study consisted of three objectives, including recognizing the reasons to adopt the software for library automation, investigating the problems faced by librarians while using library software and identifying the satisfaction level with the attributes of library software.Design/methodology/approachA quantitative research approach was used to achieve the objectives of this study. A survey was conducted to collect data from the library information science professionals working in the academic libraries of Sialkot. The data was collected from 46 library professionals through a structured questionnaire.FindingsThe findings showed that the economic cost of implementation, maintenance and the software providing multilingual support were the major reasons for adoption of software for the purpose of automation. In this study, compliance with the internet, noncooperation in library automation by university/institution, availability of training facilities, insufficient library budget, a lack of financial/economic resources, staff transfer and a lack of consultancy and technical service were identified as major issues when using library automation software. However, the respondents were quite satisfied with the performance of software attributes including circulation modules, easy to use cataloguing modules, reports’ modules, software attributes of administration modules and multilingual facility.Originality/valueThis study persuades library and information science professionals to automate their libraries through the adoption of library software.

Optimized fuzzy clustering‐based k‐nearest neighbors imputation for mixed missing data in software development effort estimation

AbstractContextSoftware development effort estimation (SDEE) is one of the most challenging aspects in project management. The presence of missing data (MD) in software attributes makes SDEE even more complex. K‐nearest neighbors imputation (KNNI) has been widely used in SDEE to deal with the MD issue. However, KNNI, in its classical process, has low tolerance to imprecision and uncertainty especially when dealing with categorical features. When dealing with categorical attributes, KNNI uses a classical approach, employing mainly numbers or classical intervals to represent software attributes and similarity measures originally designed for numerical attributes.ObjectivesThis paper evaluates the use of an optimized fuzzy clustering‐based KNNI (FC‐KNNI) and compares it with classical KNN when dealing with mixed data in the context of SDEE.MethodsWe investigate the effect of two imputation techniques (FC‐KNNI and KNNI) on five SDEE techniques: case‐based reasoning, fuzzy case‐based reasoning, support vector regression, multilayer perceptron, and reduced‐error pruning tree. The evaluation is carried out using six publicly available datasets for SDEE using two performance measures, standardized accuracy (SA), and Pred (0.25). The Wilcoxon statistical test is also performed to assess the significance of results.ResultsThe results are promising in the sense that using an imputation technique designed for mixed data is better than reusing methods originally designed for numerical data. We found that FC‐KNNI significantly outperforms KNNI regardless of the SDEE technique and dataset used. Another important finding is that F‐CBR improved the analogy process compared to CBR.ConclusionThe introduction of fuzzy sets and fuzzy clustering in the analogy process improves its performances in terms of SA and Pred (0.25).

Разработка алгоритма выявления вредоносных программ для платформы Android путем проведения анализа файла манифеста

The available algorithms for detecting malicious software are often not enough to detect new types of viruses. In this regard, the issues related to the use of reverse engineering of malicious software codes intended for the Android operating system are considered. It is proposed to conduct a comprehensive analysis of the code and manifest of the mobile application in order to form the attributes of malicious software and create detection algorithms for a specific operating system. Research objective: to show the relevance of reverse engineering and to develop a heuristic analysis algorithm that allows detecting the presence of hidden malicious code in mobile applications by analyzing code metadata. Methods: the article uses the reverse engineering method on the example of actual Trojans to form attributes that characterize the possibility of hidden malicious code in a mobile application, according to the logical values of which the algorithm makes a cumulative decision about the possibility of hidden malicious load. Results: the proposed approach was tested using the VirusTotal database to evaluate errors of the first and second kind and showed 78% efficiency in detecting malicious software only from code metadata using the proposed attributes, does not require complex calculations and time-consuming costs and can be the basis for using artificial intelligence in combination with static and dynamic analysis to identify viruses of the Android operating system. Practical significance: the developed algorithm can be used as an additional element in the integrated antivirus protection system of a smartphone against malware infection.

Preferential Selection of Software Quality Models Based on a Multi-Criteria Decision-Making Approach

Software engineering mainly aims to produce software of good quality that is delivered on time and on budget. Software quality becomes an important concern for quantifying the performance of software attributes. The seminal objective of the work is to choose the appropriate software quality model according to the client's needs where the client can give more importance to specific criteria compared to others as per his/her application's requirements. The proposed approach will help to decide the best alternative suitable for the application. The work is based on selecting the most suitable software quality model taking all the parameters into consideration while making the decision using multi-criteria decision-making techniques.

Attributes of communication aids as described by those supporting children and young people with AAC.

Those supporting children and young people who use augmentative and alternative communication (AAC) contribute to ongoing complex decision-making about communication aid selection and support. Little is known about how these decisions are made in practice and how attributes of the communication aid are described or considered. To understand how communication aid attributes were described by those involved in AAC recommendations and support for children and young people, and how these attributes were described as impacting on AAC use. A secondary qualitative analysis was completed of interview and focus group data from 91 participants involved in the support of 22 children and young people. Attributes of communication aids described by participants were extracted as themes and this paper reports a descriptive summary of the identified software (non-hardware) attributes. Decisions were described in terms of comparisons between commercially available pre-existing vocabulary packages. Attributes related to vocabulary, graphic representation, consistency and intuitiveness of design, and ease of editing were identified. Developmental staging of vocabularies, core and fringe vocabulary, and vocabulary personalization were attributes that were described as being explicitly considered in decisions. The potential impact of graphic symbol choice did not seem to be considered strongly. The physical and social environment was described as the predominant factor driving the choice of a number of attributes. Specific attributes that appear to be established in decision-making in these data have limited empirical research literature. Terms used in the literature to describe communication aid attributes were not observed in these data. Practice-based evidence does not appear to be supported by the available research literature and these findings highlight several areas where empirical research is needed in order to provide a robust basis for practice. What is already known on the subject Communication aid attributes are viewed as a key consideration by practitioners and family members in AAC decision-making; however, there are few empirical studies investigating language and communication attributes of communication aids. It is important to understand how those involved in AAC recommendations and support view communication aid attributes and the impact different attributes have. What this paper adds to existing knowledge This study provides a picture of how communication aids are described by practitioners and family members involved in AAC support of children and young people. A range of attributes is identified from the analysis of these qualitative data as well as information about how participants perceive these attributes as informing decisions. What are the potential or actual clinical implications of this work? This study provides a basis on which practitioners and others involved in AAC support for children and young people can review and reflect on their own practice and so improve the outcomes of AAC decisions. The study provides a list of attributes that appear to be considered in practice and so also provides a resource for researchers looking to ensure there is a strong empirical basis for AAC decisions.

Evaluation of Software Quality in Test-driven Development: A Perspective of Measurement and Metrics

A software product is expected to be subjected to critical evaluation on its quality attributes in order to ascertain that target quality requirements are met, and that those quality attributes responsible for revealing software quality are not omitted in the software development process. Software metrics are essential to accomplish the task. This paper has carried out an exploratory study of software measurement and software metrics in tandem. The study took into cognizance the interwoven nature of the duo in measuring and revealing software quality. The study formulated a model that expressed the mutual bonding that propels both measurement and metrics to describing software quality in numeric quantities of software attributes. The study identified six software attributes whose values are considered enough quantities to reveal the quality of a software product. The identification enabled the study to create a model equation aimed at giving a numeric value for the complete evaluation of a software system. The result of the implementation of the six software attributes into the model equation showed that two software products employed in the study are of high-quality, having quality values of 0.93 and 0.86 respectively. The attributes produced values that confirmed the maintainability (25 seconds & 20 seconds respectively) and reliability (0.78 & 0.80 respectively) of both software products among other differing features that characterize them.

A review of embodied life cycle assessment tools used to support the building design process

Buildings and construction have a significant effect on our natural environment and are major contributors towards global energy use and greenhouse gas emissions. Understanding and improving the environmental performance of buildings is critical to reducing these effects. While there has been some success reducing the operational effects of buildings, the significance of embodied environmental effects is rising. Built environment professionals must be better equipped to understand and integrate these considerations into iterative decision-making processes. Life cycle assessment (LCA) is a commonly used technique to quantify environmental effects across the life cycle of a building, however, it is not widely used by building designers. This is partially due to time constraints, the complexity of conducting detailed LCA, and the limited amount of building information available during early building design. The aim of this review is to identify the breadth of LCA tools available that support the building design process, with a focus on embodied environmental effects. A review of literature is conducted which identifies attributes and properties of these tools including: software attributes, relevance to design phases, features for building design, life cycle coverage, and data attributes. The review finds a lack of consistency between LCA tools, with varying levels of data transparency and completeness, and challenges for incorporating these tools into prevalent design workflows.

Development Of Iris Based Age And Gender Detection System

Biometric recognition has shown their utility in different aspect including reducing search space significantly which has led to improve recognition performance, reduced computation time and faster processing time, a person is identified automatically by processing the unique features that are posed by the individual. The existing biometric systems recognize and accept a person, else simply reject a person if not enrolled, but these systems do not give software attributes of a person which is needed to search impostor as it has been observed in many occasions and especially in Nigeria that identification of an individual’s age and gender does not go beyond physical factors which in most cases can be manipulated or spoofed to carry out nefarious activities. This project focuses on developing an iris-based age and gender detection system for certain individuals to identify a person in real time. Left and right irises of 190 subjects constituting 1,716 images were acquired and Five Hundred and Seventy (570) left Irises were normalized to a uniform size of 250 by 250 pixels. Three Hundred and Forty-Two (342) images were used for training while the remaining Two Hundred and Twenty-Eight (228) were used for testing. The acquired images were preprocessed by performing segmentation, filtering and normalization using Daugman’s Rubber Sheet Model. Deep learning pre-trained networks are adopted to extract features from iris images. Further, these features are trained and classified using the multi-class Support Vector Machines (SVM) model for performance evaluation of the system. The system was implemented in Matrix Laboratory 9.0 (R2016a). The performance of the system was evaluated using accuracy, precision, recall and False Positive Rate (FPR). The hypothesis stating ‘the iris has age, and gender-related information’ is proven correct from experimental results. The evaluation results showed that False Positive Rate, Recall, Precision and Accuracy of gender prediction were 2.19%, 92.31%, 96.55% and 95.62% respectively at 0.75 threshold while for age prediction, the best values were obtained at age group of 20-24 for FPR, Recall, Precision and Accuracy which were 5.61%, 94.37%, 96.18% and 94.38% respectively. The developed model gave good performance with high recognition accuracy, recall, precision and low FPR values. Therefore, the developed model can be used in all firms and industries where security and personal identification is desired for security purpose and in going through investigation of criminal records for detecting age and gender of individuals.

An integrative Whole Building Life Cycle Assessment (WBLCA) framework: A survey of software developers’ perspective

Whole Building Life Cycle Assessment (WBLCA) is an effective way of evaluating the environmental impact of a building's systems and materials. Designers usually rely on software tools to evaluate a building's environmental performance, and the barriers to the smooth use of these tools during design are extensive. Given the critical role software tools are playing in design practice, this research sought the opinions of WBLCA software tool developers to create a framework that better integrates WBLCA into the Building Project Process (BPP). A questionnaire of software attributes in each stage of BPP and the challenges associated with incorporating WBLCA into the BPP was followed by interviews to establish a greater understanding of the software tool developers' responses. The integrative framework illustrates the character of the WBLCA in each stage of BPP, including the goal of the assessment, the relevant software attributes, the applicable databases, and the primary stakeholders engaged in the process. For instance, design-oriented software attributes are more relevant in the early stages, and, as the BPP progresses, the assessment requires more transparency in the assumptions and outcomes. The findings from this study will guide software developers and policymakers to develop tools and procedures more aligned with designers interests. • Sustainability software capabilities define the design process. • The sustainable design process moves from qualitative to quantitative metrics. • The key decision for LCA building design does not match certification requirements. • In-use results need to feed into the early stages of future projects.

Self-Adaptive Framework With Master–Slave Architecture for Internet of Things

The Internet of Things (IoT) connects a wide range of entities and can be applied to various types of environments. In addition, IoT environments can be dynamically changed at runtime; thus, IoT systems can be deployed in various environments. To support stable operation, IoT systems must adapt to dynamic environmental changes. The self-adaptive software aims to adjust various artifacts or attributes of software to adapt the detected context by itself, and various studies have applied self-adaptive methods in IoT-related research. In this study, we proposed a self-adaptive software framework with master–slave architecture-based finite-state machine modeling. In addition, model checking is applied, which is a formal method to verify IoT systems at runtime, and a cache-based mechanism is applied to reduce the computational time required for verification. To demonstrate the efficiency of the proposed framework, an empirical evaluation was performed with several model-checking tools (RINGA, NuSMV, nuXmv, and CadenceSMV), and the results showed the efficiency of the proposed framework with the cache-based mechanism. In addition, an example application was investigated with smart greenhouse scenarios, and the application was implemented on Android and Arduino. The application was operated in physical environments, and the results showed the practical usability of the proposed framework with verification at runtime.

Decentralized Review and Attestation of Software Attribute Claims

Software can be described, like human users and other objects, through attributes. For this work, we define software attributes as humanly verifiable, falsifiable, or judgeable statements regarding characteristics of said software. Much like attributes in general, software attributes require robust identities for their source but also for their target, meaning a software in general or a binary in particular. As software can be of critical importance, performing an independent review of attribute claims appears beneficial. We posit that decentralized platforms that were developed and refined over the past decade can bridge the gap between existing tools and methods for software review and their open, transparent, and accountable use for the benefit of users. In this work, we explore the feasibility and implications of decentralizing an independent review of software attribute claims. We envision the decentralization of a review process from initialization and execution to the persistent recording of results. We sketch the available design space by decomposing the overall process into a modular design and describe how each component covers overarching objectives. To illustrate practical implications and trade-offs, we present ETHDPR, a proof of concept implementation based on Ethereum and IPFS. Through a quantitative and qualitative evaluation, we show that a decentralized software review is practically feasible. We illustrate the flexibility of the proposed approach using a toy example of a software component in automotive systems. Lastly, we provide a discussion on fundamental limits and open issues of facilitating independent reviews via technological means.

Privacy preserving defect prediction using generalization and entropy-based data reduction

The software engineering community produces data that can be analyzed to enhance the quality of future software products, and data regarding software defects can be used by data scientists to create defect predictors. However, sharing such data raises privacy concerns, since sensitive software features are usually considered as business assets that should be protected in accordance with the law. Early research efforts on protecting the privacy of software data found that applying conventional data anonymization to mask sensitive attributes of software features degrades the quality of the shared data. In addition, data produced by such approaches is not immune to attacks such as inference and background knowledge attacks. This research proposes a new approach to share protected release of software defects data that can still be used in data science algorithms. We created a generalization (clustering)-based approach to anonymize sensitive software attributes. Tomek link and AllNN data reduction approaches were used to discard noisy records that may affect the usefulness of the shared data. The proposed approach considers diversity of sensitive attributes as an important factor to avoid inference and background knowledge attacks on the anonymized data, therefore data discarded is removed from both defective and non-defective records. We conducted experiments conducted on several benchmark software defect datasets, using both data quality and privacy measures to evaluate the proposed approach. Our findings showed that the proposed approach outperforms existing well-known techniques using accuracy and privacy measures.

COMPARISON OF SOFTWARE METRICS FOR QUALITY ESTIMATION OF THE SOFTWARE PRODUCTS

There is a well known principle, that you can manage only what you can measure – therefore adequate measurement and estimation of different elements in any engineering area is a very important development factor, and software engineering is not an exception. Software metrics represent numeric values of software characteristics and are used for analysis of different aspects of the product in order to predict possible problems. Software metrics can be applied to any stage of the software life cycle. For instance, on a stage of requirement analysis and the problem formulation, these metrics help to estimate the required amount of work and, respectively, the amount of financial and work resources. In addition, the metrics can be used directly in estimation of the program code complexity to assess it’s performance, effectiveness and the ability to modify it if needed. Software metrics are an important part of the whole software quality management process as they can be easily automated and applied in order to achieve some valuable technical characteristics. Moreover, they can be combined with another quality management tools and are a beneficial addition to any software product development model. In general, measuring the attributes of software during any phase of development gives a number of beneficial results to the developers as it helps to use the time, finances and effort effectively. This is achieved because of early problems identification, estimation and prevention and because of that the size, cost, quality and simplicity of the maintenance of the product is always under control. This article describes the results of research on different software metrics types and the actual representatives of these types. It assesses the usage area and the convenience of it’s usage on evaluating the quality of both a finished product and a product in the development stage.

Efficient Parametric Model Checking Using Domain Knowledge

We introduce an efficient parametric model checking (ePMC) method for the analysis of reliability, performance and other quality-of-service (QoS) properties of software systems. ePMC speeds up the analysis of parametric Markov chains modelling the behaviour of software by exploiting domain-specific modelling patterns for the software components (e.g., patterns modelling the invocation of functionally-equivalent services used to jointly implement the same operation within service-based systems, or the deployment of the components of multi-tier software systems across multiple servers). To this end, ePMC precomputes closed-form expressions for key QoS properties of such patterns, and uses these expressions in the analysis of whole-system models. To evaluate ePMC, we show that its application to service-based systems and multi-tier software architectures reduces the analysis time by several orders of magnitude compared to current parametric model checking methods.

An ordered ranking multi-attributive model for decision-making systems with attributes of control systems software

The authors present a compensation model for the general ranking of alternatives in their order of preference, considering the dependence of the attributes of software for spacecraft control systems. Among the discussed features is one that consists in the use of a set of target functions, which cannot be optimized simultaneously, due to their inherent incommensurability and target conflict.

Hybrid model for evaluation of quality aware DevOps

ABSTRACT Today most of the organizations are switching to DevOps for faster and reliable delivery. It promotes the collaboration between developers and IT teams. In ancient development practices, development and operation teams were working in silos and when DevOps introduced, it combines both teams to integrate and automate the processes. A single team with cross functioning members provides not only technical advantages but also cultural benefits. Faster delivery of software, less complex designs, stable operating environments, customer satisfaction is some of the outcomes of DevOps. Although it proved to be a responsive environment for software delivery yet lacks in quantifiable perspective. There is no metric defined to measure performance and that can be estimated by using key attributes of software. In this research hybrid framework is proposed to improve the software reliability and productivity. Proposed framework for DevOps is named TDMBD (Test Driven Measurement Based DevOps) which provides solutions to challenges in DevOps like performance issues, poorly defined methodologies, and unstandardized processes. Paper focuses on defining and measuring metrics that are derived from measurement-based system of software and TDMBD is evaluated based on metrics analysis. To validate results of proposed approach a comparison is shown in between existing approach and proposed approach. Finally, through proposed method better quality of product is retrieved.

МОДЕЛЬ ИНФОРМАЦИОННО-СОВЕТУЮЩЕЙ СИСТЕМЫ ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИЯ ПРИ ВЫБОРЕ СПОСОБА ТЕСТИРОВАНИЯ ПРО-ГРАММНОГО ОБЕСПЕЧЕНИЯ

High quality software systems is an urgent task for any enterprise. Improving quality increases the competitiveness and relevance of software products. One of the tools to ensure quality is testing software systems. This article discusses the basic principles of building an information-advisory system (IAS) of decision support when choosing a method for testing software. The conceptual approaches to testing based on the functional characteristics of software classes are analyzed. When choosing a testing method, it is recommended to take into account not only the financial component, but also the specific characteristics of the tested software system. A list of questions has been developed with the help of which the qualitative properties of software systems are formalized. The list of questions is based on the ISO / IEC 25010: 2011 model. Questionnaires and tables of pairwise comparisons of questions are invited to fill out a group of experts. Questions have equivalent significance with respect to the criterion of “Importance for Automation”. When selecting experts, it is not always possible to create a homogeneous group, therefore, it is proposed to calculate the weighting coefficients of competence of each expert. Based on the data obtained, weights are calculated for answers to questions. Next, the convolution is calculated and, depending on the result, a recommendation is made on choosing the type of testing. The analytical and structural model of IAS is constructed. In the developed software system, a data input subsystem, a subsystem for ranking questions and expert competencies, and a unit for generating the resulting data are allocated. The proposed IAS will make it possible to calculate the competency coefficients of experts, to rank questions according to the degree of importance for testing automation, and to choose the optimal approach to testing software systems.