Classification and Comprehension of Software Requirements Using Ensemble Learning

The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional requirements.To address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human effort.However,existing techniques often struggle with complex instructions and large-scale projects.In our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer trees.Experimental results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT dataset.Both datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse scenarios.These findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

How to implement a knowledge graph completeness assessment with the guidance of user requirements

In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.

An Investigation on Open-RAN Specifications:Use Cases,Security Threats,Requirements,Discussions

The emergence of various technologies such as terahertz communications,Reconfigurable Intelligent Surfaces(RIS),and AI-powered communication services will burden network operators with rising infrastructure costs.Recently,the Open Radio Access Network(O-RAN)has been introduced as a solution for growing financial and operational burdens in Beyond 5G(B5G)and 6G networks.O-RAN promotes openness and intelligence to overcome the limitations of traditional RANs.By disaggregating conventional Base Band Units(BBUs)into O-RAN Distributed Units(O-DU)and O-RAN Centralized Units(O-CU),O-RAN offers greater flexibility for upgrades and network automation.However,this openness introduces new security challenges compared to traditional RANs.Many existing studies overlook these security requirements of the O-RAN networks.To gain deeper insights into the O-RAN system and security,this paper first provides an overview of the general O-RAN architecture and its diverse use cases relevant to B5G and 6G applications.We then delve into specifications of O-RAN security threats and requirements,aiming to mitigate security vulnerabilities effectively.By providing a comprehensive understanding of O-RAN architecture,use cases,and security considerations,thisworkserves as a valuable resource for future research in O-RAN and its security.

Requirements ranking based on crowd-sourcing high-end product USs

Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.

Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

Research Progress on Nutritional Requirements of Carp

Carp is a temperate freshwater fish native to Asia,distributed in all regions of the world except Australia and South America.With the improvement of comprehensive and healthy breeding technology of carp,the unit yield has been greatly increased mainly due to the exten-sive use of compound feed.In this study,the nutritional requirements of carp were summarized from the aspects of protein,amino acids,fat,carbohydrate,calcium and phosphorus,vitamins and taurine.This study provides a certain theoretical reference for scientific formula of carp feed.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

Requirement Engineering for E-Coaching in Higher Education

This paper presents a requirement engineering for developing an e-coaching environment in the higher education sector. This research demonstrates that IT experts encounter challenges in establishing a system that matches a university’s expectations, as they are usually uncertain about its goals and system requirements. The paper illustrates a business goal-focused requirement induction technique, which encompasses demonstrating the business procedures through Business Process Modelling Notation (BPMN), assessing the university goals via the tree diagram, and drawing out the system requirements from the university objectives through UML state diagrams. A case study of supporting the development of a new IT course is used as a case study and applied using BPMN.

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

The paper presents a new approach to managing software requirement elicitation techniques with a high level of analyses based on domain ontology techniques, where we established a mapping between user scenario, structured requirement, and domain ontology techniques to improve many attributes such as requirement consistency, completeness and eliminating duplicate requirements to reduce risk of overrun time and budgets. One of the main targets of requirement engineering is to develop a requirement document with high quality. So, we proposed a user interface to collect all vital information about the project directly from the regular user and requirement engineering;After that, the proposal will generate an ontology based on semantic relations and rules. Requirements Engineering tries to keep requirements throughout a project’s life cycle consistent necessities clear, and up to date. This prototype allows mapping requirement scenarios into ontology elements for semantically interrupted. The general points of our prototype are to guarantee the identification requirements and improved nature of the Software Requirements Specification (SRS) by solving incomplete and conflicting information in the requirements specification.

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

Forecasting on success or failure of software has become an interesting and,in fact,an essential task in the software development industry.In order to explore the latest data on successes and failures,this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework?What human factors contribute to success or failure of a software?What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work?In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors,misinterpretation,and miscommunication of requirements and decision-making processes play their roles in software success forecasting.We discussed a potential relationship between forecasting of software success or failure and the development processes.We noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study,and they were more likely to rate software success forecasting linking to the development processes.Our analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success rate.The results of this empirical study also validated that requirements’misinterpretation and miscommunication were themain causes behind software systems’failure.It has been seen that reliable,relevant,and trustworthy sources of information help in decision-making to predict software systems’success in the software industry.This empirical study highlights a need for other software practitioners to avoid such bias while working on software projects.Future investigation can be performed to identify the other human factors that may impact software systems’success.

On the Assessment of Generative AI in Requirements Analysis and Modeling Tasks with UML:An Exploratory Study

Generative AI is rapidly employed by software developers to generate code or other software artifacts.However,the analysis and assessment of generative AI with respect to requirements analysis and modeling tasks,especially with UML,has received little attention.This paper investigates the capabilities of generative AI to aid in the creation of three types of UML models:UML use case models,class diagrams,and sequence diagrams.For this purpose,we designed an AI-aided UML modeling task in our course on software requirements modeling.50 undergraduates who majored in Software Engineering at Wuhan University completed the modeling task and the corresponding online survey.Our findings show that generative AI can help create these three types of UML models,but its performance is limited to identifying essential modeling elements of these UML models.

IoT for Streetlighting-Requirements for Modelling of Management Services-Part I

Energy conservation is the effort to reduce the overconsumption of energy by the usage of less energy services.Energy conservation could be user oriented or industry sector oriented.One of these sectors is the streetlighting-major energy consumer in the town-forming nearly 30%of each country’s consumption.Intelligent designed management of streetlighting not only reduces the energy consumption of the town,but also increases the public safety and the wellbeing.The article focuses the management of IoT for streetlighting in smart city.This is the first stage of project“Service management for IoT in streetlighting”.While the basic management principles are efficiency and fairness,the requirements of all actors must be defined.On the base of requirements,the authors synthesize the management functions with selected granularity.The chosen methodology is unified modelling language(UML):use case diagrams.The models are intended to business developers,university professors,and students.

Automated Test Case Generation from Requirements: A Systematic Literature Review

Software testing is an important and cost intensive activity in software development.The major contribution in cost is due to test case generations.Requirement-based testing is an approach in which test cases are derivative from requirements without considering the implementation’s internal structure.Requirement-based testing includes functional and nonfunctional requirements.The objective of this study is to explore the approaches that generate test cases from requirements.A systematic literature review based on two research questions and extensive quality assessment criteria includes studies.The study identies 30 primary studies from 410 studies spanned from 2000 to 2018.The review’s nding shows that 53%of journal papers,42%of conference papers,and 5%of book chapters’address requirementsbased testing.Most of the studies use UML,activity,and use case diagrams for test case generation from requirements.One of the signicant lessons learned is that most software testing errors are traced back to errors in natural language requirements.A substantial amount of work focuses on UML diagrams for test case generations,which cannot capture all the system’s developed attributes.Furthermore,there is a lack of UML-based models that can generate test cases from natural language requirements by rening them in context.Coverage criteria indicate how efciently the testing has been performed 12.37%of studies use requirements coverage,20%of studies cover path coverage,and 17%study basic coverage.

Intelligent Identification and Resolution of Software Requirement Conflicts:Assessment and Evaluation

Considerable research has demonstrated how effective requirements engineering is critical for the success of software projects.Requirements engineering has been established and recognized as one of the most important aspects of software engineering as of late.It is noteworthy to mention that requirement consistency is a critical factor in project success,and conflicts in requirements lead to waste of cost,time,and effort.A considerable number of research studies have shown the risks and problems caused by working with requirements that are in conflict with other requirements.These risks include running overtime or over budget,which may lead to project failure.At the very least,it would result in the extra expended effort.Various studies have also stated that failure in managing requirement conflicts is one of the main reasons for unsuccessful software projects due to high cost and insufficient time.Many prior research studies have proposed manual techniques to detect conflicts,whereas other research recommends automated approaches based on human analysis.Moreover,there are different resolutions for conflicting requirements.Our previous work proposed a scheme for dealing with this problem using a novel intelligent method to detect conflicts and resolve them.A rule-based system was proposed to identify conflicts in requirements,and a genetic algorithm(GA)was used to resolve conflicts.The objective of this work is to assess and evaluate the implementation of the method of minimizing the number of conflicts in the requirements.The methodology implemented comprises two different stages.The first stage,detecting conflicts using a rule-based system,demonstrated a correct result with 100% accuracy.The evaluation of using the GA to resolve and reduce conflicts in the second stage also displayed a good result and achieved the desired goal as well as the main objective of the research.

Specifying Requirements of Real-Time System with Rules and Templates

This paper presents a model specifying requirements of real-time systems. Different from existing researches, this model mainly uses rules and templates to represent hierarchical FSMs (Finite State Machine). In this model, one rule corresponds to one state transition of FSM and one template corresponds to one FSM. Rules and information with respect to a FSM can be written in a template. So templates include not only state diagrams, but also information that can not be described by FSM, such as performance requirements. The specification using this model consists of a collection of templates and it is easy for users to understand and to review. After introduced the related researches and principles of the model, this paper specifies requirements of a real-time system with this model, and discusses characters of this model in the end.

Investigation of crop evapotranspiration and irrigation water requirement in the lower Amu Darya River Basin, Central Asia

High water consumption and inefficient irrigation management in the agriculture sector of the middle and lower reaches of the Amu Darya River Basin(ADRB)have significantly influenced the gradual shrinking of the Aral Sea and its ecosystem.In this study,we investigated the crop water consumption in the growing seasons and the irrigation water requirement for different crop types in the lower ADRB during 2004–2017.We applied the FAO Penman–Monteith method to estimate reference evapotranspiration(ET0)based on daily climatic data collected from four meteorological stations.Crop evapotranspiration(ETc)of specific crop types was calculated by the crop coefficient.Then,we analyzed the net irrigation requirement(NIR)based on the effective precipitation with crop water requirements.The results indicated that the lowest monthly ET0 values in the lower ADRB were found in December(18.2 mm)and January(16.0 mm),and the highest monthly ET0 values were found in June and July,with similar values of 211.6 mm.The annual ETc reached to 887.2,1002.1,and 492.0 mm for cotton,rice,and wheat,respectively.The average regional NIR ranged from 514.9 to 715.0 mm in the 10 Irrigation System Management Organizations(UISs)in the study area,while the total required irrigation volume for the whole region ranged from 4.2×109 to 11.6×109 m3 during 2004–2017.The percentages of NIR in SIW(surface irrigation water)ranged from 46.4%to 65.2%during the study period,with the exceptions of the drought years of 2008 and 2011,in which there was a significantly less runoff in the Amu Darya River.This study provides an overview for local water authorities to achieve optimal regional water allocation in the study area.

Macromineral requirements of Dorper×thin-tailed Han crossbred female lambs

A comparative slaughter trial was conducted to determine the net mineral requirements for maintenance and growth of Dorper crossbred female lambs raised from 20 to 35 kg of body weight（BW）.Thirty-five Dorper×thin-tailed Han crossbred female lambs of（20.3±1.14） kg BW were used： 7 lambs were randomly chosen and slaughtered at the beginning of the experiment as the baseline group for measuring the initial body composition; another 7 lambs were randomly chosen and offered a pelleted mixed diet ad libitum and slaughtered at（27.0±0.73） kg BW; the remaining 21 lambs were randomly divided into 3 groups of 7 animals each and subjected to the same diet either ad l ibitum or at 70 or 40% of ad libitum intake.The 21 lambs were fed in 7 slaughter groups, with each group consisting of one lamb from each treatment（ad libitum, 70 or 40% of ad libitum intake）.The 3 groups were slaughtered when the sheep fed ad libitum attained（33.8±0.52） kg of BW.The body composition of five minerals（Ca, P, Na, K, and Mg） was determined.The net mineral requirements for maintenance were 35.01, 25.18, 9.30, 31.35, and 2.03 mg kg–1 empty BW（EBW） for Ca, P, Na, K, and Mg, respectively, and the net growth requirement per kg of EBW gain ranged from 9.73 to 8.87 g of Ca, 5.83 to 5.27 g of P, 1.73 to 1.63 g of Na, 3.73 to 4.08 g of K, and 0.26 to 0.25 g of Mg for Dorper crossbred lambs in China, respectively.The estimates of mineral requirements with Dorper crossbred lambs in the current study were not consistent with the recommendations from previous studies.

Effective Hybrid Content-Based Collaborative Filtering Approach for Requirements Engineering

Requirements engineering(RE)is among the most valuable and critical processes in software development.The quality of this process significantly affects the success of a software project.An important step in RE is requirements elicitation,which involves collecting project-related requirements from different sources.Repositories of reusable requirements are typically important sources of an increasing number of reusable software requirements.However,the process of searching such repositories to collect valuable project-related requirements is time-consuming and difficult to perform accurately.Recommender systems have been widely recognized as an effective solution to such problem.Accordingly,this study proposes an effective hybrid content-based collaborative filtering recommendation approach.The proposed approach will support project stake-holders in mitigating the risk of missing requirements during requirements elicitation by identifying related requirements from software requirement repositories.The experimental results on the RALIC dataset demonstrate that the proposed approach considerably outperforms baseline collaborative filtering-based recom-mendation methods in terms of prediction accuracy and coverage in addition to mitigating the data sparsity and cold-start item problems.

Implications of future climate change on crop and irrigation water requirements in a semi-arid river basin using CMIP6 GCMs

Agriculture faces risks due to increasing stress from climate change,particularly in semi-arid regions.Lack of understanding of crop water requirement(CWR)and irrigation water requirement(IWR)in a changing climate may result in crop failure and socioeconomic problems that can become detrimental to agriculture-based economies in emerging nations worldwide.Previous research in CWR and IWR has largely focused on large river basins and scenarios from the Coupled Model Intercomparison Project Phase 3(CMIP3)and Coupled Model Intercomparison Project Phase 5(CMIP5)to account for the impacts of climate change on crops.Smaller basins,however,are more susceptible to regional climate change,with more significant impacts on crops.This study estimates CWRs and IWRs for five crops(sugarcane,wheat,cotton,sorghum,and soybean)in the Pravara River Basin(area of 6537 km^(2))of India using outputs from the most recent Coupled Model Intercomparison Project Phase 6(CMIP6)General Circulation Models(GCMs)under Shared Socio-economic Pathway(SSP)245 and SSP585 scenarios.An increase in mean annual rainfall is projected under both scenarios in the 2050s and 2080s using ten selected CMIP6 GCMs.CWRs for all crops may decline in almost all of the CMIP6 GCMs in the 2050s and 2080s(with the exceptions of ACCESS-CM-2 and ACCESS-ESM-1.5)under SSP245 and SSP585 scenarios.The availability of increasing soil moisture in the root zone due to increasing rainfall and a decrease in the projected maximum temperature may be responsible for this decline in CWR.Similarly,except for soybean and cotton,the projected IWRs for all other three crops under SSP245 and SSP585 scenarios show a decrease or a small increase in the 2050s and 2080s in most CMIP6 GCMs.These findings are important for agricultural researchers and water resource managers to implement long-term crop planning techniques and to reduce the negative impacts of climate change and associated rainfall variability to avert crop failure and agricultural losses.