Requirements Traceability Research Articles

X-RMTV: An Integrated Approach for Requirement Modeling, Traceability Management, and Verification in MBSE

Formal requirements modeling and traceability management are essential for effectively implementing Model-Based Systems Engineering (MBSE). However, few studies have explored the integration of requirement modeling, traceability management, and verification within MBSE-based systems engineering methodologies. Moreover, the predominant modeling language for MBSE, SysML, lacks sufficient capabilities for requirement description and traceability management and for depicting physical attributes and executable capabilities, making it challenging to verify functional and non-functional requirements collaboratively. This paper proposes an integrated approach for requirement modeling, traceability management, and verification, building on the previously proposed integrated modeling and the simulation language called X language. Our contributions primarily include defining the ReqXL specification for MBSE-oriented requirement modeling based on X language, proposing an algorithm for automatically generating requirement traces, and an integrated framework for requirements modeling, traceability management, and verification was developed by combining the X language with ReqXL. These functionalities were customized on the self-developed integrated modeling and simulation platform, XLab, which is specifically tailored for the X language. Furthermore, we showcase the efficacy and promise of our approach through a case study involving the design of an aircraft electrical system.

Intellectual Property Management and Legal Protection Mechanism of Blockchain-based Crowdsourced Testing

While promoting the vigorous development of crowdsourced testing services, Internet technology has also generated problems such as non-standard intellectual property management, unclear ownership of rights, and lack of trustworthiness. Based on the characteristics of being decentralized, traceable and tamper-proof of blockchain, IPFS, SHA256 algorithm, and digital certificate technology, this paper puts forward a new intellectual property management framework for crowdsourced testing to meet the requirements of intellectual property traceability of crowdsourced testing, right confirmation and query, and proposes the idea of applying on the chain and off chain decomposition and integration technology to address the storage performance bottleneck problem caused by data expansion on the chain, thus realizing a trusted intellectual property management system of crowdsourced testing. Meanwhile, this paper puts that the intellectual property of crowdsourced testing cannot be fully maintained only by technical means, and corresponding legal support means should be supplemented, including improving the laws and regulations on judicial and administrative protection of intellectual property, and properly handling the legal risk control of intellectual property of crowdsourced testing.

Enhancing requirements-to-code traceability with GA-XWCoDe: Integrating XGBoost, Node2Vec, and genetic algorithms for improving model performance and stability

This study addresses the challenge of requirements-to-code traceability by proposing a novel model, Genetic Algorithm-XGBoost With Code Dependency (GA-XWCoDe), which integrates eXtreme Gradient Boosting (XGBoost) with a Node2Vec model-weighted code dependency strategy and genetic algorithms for parameter optimisation. XGBoost mitigates overfitting and enhances model stability, while Node2Vec improves prediction accuracy for low-confidence links. Genetic algorithms are employed to optimise model parameters efficiently, reducing the resource intensity of traditional methods. Experimental results show that GA-XWCoDe outperforms the state-of-the-art method TRAceability lInk cLassifier (TRAIL) by 17.44% and Deep Forest for Requirement traceability (DF4RT) by 33.36% in terms of average F1 performance across four datasets. It is significantly superior to all baseline methods at a confidence level of α¡0.01 and demonstrates exceptional performance and stability across various training data scales.

Establishing Metrics to Encourage Broader Use of Atomic Requirements - A Call for Exchange and Experimentation

There are seemingly many advantages to being able to identify, document, test, and trace single or "atomic" requirements during system development and maintenance. Ongoing work with Agile development has focused on "user stories" that can capture individual features for implementation. However, it is still difficult to evaluate the quality of such requirements and teaching their creation is difficult. Based on a working definition of atomic requirement, this paper proposes a set of metrics for their evaluation. Ten metrics designed to measure atomic requirements are presented here: five used on individual requirements statements and five applied to a requirements document or set of requirement statements. Example metrics for individual requirements include Requirement Atomic Completeness and Requirement Atomic Verifiability. Requirement Traceability is a proposed metric for a set of atomic requirements (such as a traditional requirements specification document.) Further work is needed to make the suggested metrics more consistent and precise, including exploring the use of tools that may automate some of the measures. However, a first step is to refine the metrics themselves and ensure they adequately measure atomic requirement quality. Hence this note shares the proposed metrics to encourage discussion and to recommend experimentation. The author is applying the metrics in software engineering courses doing team software development. The goal is the eventual acceptance of a set of requirements metrics specifically designed to evaluate atomic requirements. Better metric definitions may lead to wider utilization of atomic requirements and improved requirements engineering in general.

Elevating Recycling Standards: Global Requirements for Plastic Traceability and Quality Testing

Globally, we produced 489 million tonnes of plastic in 2023 and we recycled only 8.17%. This study navigates the landscape of recycling practices, highlighting the imperative to reevaluate and upgrade industry-standard protocols. The central focus of this study is on integrating more robust traceability criteria and advanced quality testing methodologies to improve recycled plastics with intrinsic value, particularly in anticipation of future market applications. The investigation examines the prevailing industry standard traceability and quality framework. It then assesses the applicability of those standards using technical datasheets for recycled high-density polyethylene resin grades. This study proposes a paradigm shift toward a more sophisticated analytical approach. This comprehensive framework aims to transcend traditional quality and traceability evaluation. This paper employs a mixed methodological approach, including a thematic analysis of relevant industry standard regulations and an in-depth literature review, to address the need for an operational framework for recycling quality. This study highlights that recycling quality depends on technical attributes determining functionality and application suitability. While some properties are measured, the conventional framework does not address the degradation level of recycled plastic. This study concludes with broader considerations, emphasising the need for a traceability model to disclose material history and composition. This study advocates an industry-wide upgrade in recycling standards, prioritising traceability and quality testing. The proposed enhancements in testing grids and the improved understanding of recycling quality collectively contribute to a holistic framework, unlocking the intrinsic value of recycled plastics for future market applications.

Emergent knowledge patterns in verification artifacts

AbstractKnowledge graphs have recently been introduced to the verification strategy field successfully representing the complexity of verification in real‐life applications. This format provides a scale‐free analysis of verification strategies compared to the more traditional verification artifacts such as requirement traceability matrices and verification matrices. Complexities can be observed visually and numerically both in terms of the problem scope and the entity interdependencies. In this paper, we retrieve verification strategy information patterns representing different aspects of verification. This is achieved by tapping into the network properties of knowledge graphs. They are dissected to detect knowledge patterns emerging from different parts of the verification artifacts. Similarities and differences between the two verification strategies are explained numerically and semantically. Seemingly unrelated requirements and verification activities are connected through indirect connections, and orthogonalities between independent requirements are analyzed. These findings validate the scalability of verification planning and assessment based on knowledge graphs.

A framework for creating an IoT system specification with ChatGPT

The Internet of Things (IoT) is a core concern for the digital transformation of the industry. However, the development of IoT systems, starting from creating specifications, is a serious and time-consuming effort, which requires high levels of expertise. This paper introduces a novel approach leveraging large language models, specifically ChatGPT, to streamline the generation of IoT system specifications from initial, unstructured customer requirements. A framework, adapting the ISO IEC/IEEE 12,207:2017 standard, is developed for this purpose. The utility of this framework is validated through the development and expert evaluation of a specification for a campus laboratory IoT use case. The findings demonstrate ChatGPT's effectiveness in producing specifications that are understandable, complete, and unambiguous, thus offering a substantial aid to the industry in overcoming the complexities of IoT system specification development. At the same time, the study identified specific tasks within the requirements engineering process for IoT systems that ChatGPT could not effectively perform, such as verification, obtaining agreements, and maintaining traceability of requirements between stakeholders. The findings offer valuable insights into the practical applications of AI in the domain of IoT development, particularly in automating the specification generation process. These contributions not only advance the understanding of AI's role in IoT development but also open pathways for further research on refining AI-assisted methodologies for system specification and beyond.

Enhancing Health Product Traceability on the Blockchain: A Novel Approach for Supply Chain Management inspection to AI

INTRODUCTION: Blockchain technology is being investigated as a viable solution due to the industry's growing requirement for accountability and traceability. This study describes a fresh method for tracking down medical products that makes use of a decentralised smart contract network set up on the Ethereum blockchain. In order to enable secure and auditable tracking of health products throughout their lifecycle, the suggested system, named "HealthProductTraceability," makes use of the transparency and immutability of blockchain. 
 OBJECTIVES: The system uses a "Product" struct to hold pertinent data such the product name, batch number, temperature, producer, and distributors. To quickly get product information depending on the batch number, a mapping is used. The use of tools to manufacture items, send them to distributors, and market them is one significant contribution of this research.By demanding validation tests, such as verifying that batch numbers are unique and exist before carrying out certain activities, these functions protect the integrity of the traceability system. 
 METHODS: In order to enable interested parties to track the product's travel and temperature changes, the system additionally emits events for product manufacture, distribution, and temperature adjustments. The suggested system is innovative because it can track the temperature of health items from beginning to end on a decentralised, open platform. 
 RESULTS: By utilising blockchain technology, the system lessens reliance on centralised authorities, fosters stakeholder trust, and minimises the likelihood of fraud, forgery, and tampering in the supply chain for health products. The contract's architecture recognises some of the issues with blockchain technology, including scalability and privacy. By investigating solutions like sidechains, off-chain transactions, and enhancements to consensus methods, scalability issues are solved.
 CONCLUSION: In summary, the suggested HealthProductTraceability system offers a creative and practical solution to the traceability issues facing the health product sector. The solution provides improved transparency, security, and accountability by utilising blockchain technology, paving the path for a more dependable and trustworthy health product supply chain. To increase the system's usefulness and adoption in real-world circumstances, further research can investigate scalability and privacy issues.

Multi-type requirements traceability prediction by code data augmentation and fine-tuning MS-CodeBERT

Requirement traceability is a crucial quality factor that highly impacts the software evolution process and maintenance costs. Automated traceability links recovery techniques are required for a reliable and low-cost software development life cycle. Pre-trained language models have shown promising results on many natural language tasks. However, using such pre-trained models for requirement traceability needs large and quality traceability datasets and accurate fine-tuning mechanisms. This paper proposes code augmentation and fine-tuning techniques to prepare the MS-CodeBERT pre-trained language model for various types of requirements traceability prediction including documentation-to-method, issue-to-commit, and issue-to-method links. Three program transformation operations, namely, Rename Variable, Swap Operands, and Swap Statements are designed to generate new quality samples increasing the sample diversity of the traceability datasets. A 2-stage and 3-stage fine-tuning mechanism is proposed to fine-tune the language model for the three types of requirement traceability prediction on provided datasets. Experiments on 14 Java projects demonstrate a 6.2% to 8.5% improvement in the precision, 2.5% to 5.2% improvement in the recall, and 3.8% to 7.3% improvement in the F1 score of the traceability prediction models compared to the best results from the state-of-the-art methods.

Meaningful human control and variable autonomy in human-robot teams for firefighting.

Introduction: Humans and robots are increasingly collaborating on complex tasks such as firefighting. As robots are becoming more autonomous, collaboration in human-robot teams should be combined with meaningful human control. Variable autonomy approaches can ensure meaningful human control over robots by satisfying accountability, responsibility, and transparency. To verify whether variable autonomy approaches truly ensure meaningful human control, the concept should be operationalized to allow its measurement. So far, designers of variable autonomy approaches lack metrics to systematically address meaningful human control. Methods: Therefore, this qualitative focus group (n = 5 experts) explored quantitative operationalizations of meaningful human control during dynamic task allocation using variable autonomy in human-robot teams for firefighting. This variable autonomy approach requires dynamic allocation of moral decisions to humans and non-moral decisions to robots, using robot identification of moral sensitivity. We analyzed the data of the focus group using reflexive thematic analysis. Results: Results highlight the usefulness of quantifying the traceability requirement of meaningful human control, and how situation awareness and performance can be used to objectively measure aspects of the traceability requirement. Moreover, results emphasize that team and robot outcomes can be used to verify meaningful human control but that identifying reasons underlying these outcomes determines the level of meaningful human control. Discussion: Based on our results, we propose an evaluation method that can verify if dynamic task allocation using variable autonomy in human-robot teams for firefighting ensures meaningful human control over the robot. This method involves subjectively and objectively quantifying traceability using human responses during and after simulations of the collaboration. In addition, the method involves semi-structured interviews after the simulation to identify reasons underlying outcomes and suggestions to improve the variable autonomy approach.

A systematic literature review of pre-requirements specification traceability

Requirements traceability (RT) is the ability to link requirements to other software development artifacts. In pre-requirements (pre-RS) traceability, requirements are linked to their origin, such as interviews with stakeholders, meeting protocols, or legacy systems. Compared with post-RS traceability, which links requirements to source code and other later artifacts, pre-RS traceability has seen much less research. This article presents a systematic literature review of pre-RS traceability based on 77 articles published between 1992 and 2022, aiming to provide a comprehensive overview of its use cases, benefits, problems, and solutions. Through the analysis of existing literature, this review identifies gaps for future research and establishes a foundation for future investigations in the field of pre-RS traceability.

Practical considerations on redesigning internal quality control process to verify the traceability of clinical results for decision-making.

Traceability is an important tool in the harmonization and standardization of reporting laboratory results, making them comparable across measurement systems. Driven by International Standardization Organization (ISO) 15189 accreditation requirements, medical laboratories have entered the era of metrological traceability. Although calibrators are a key component in the entire metrological traceability system, there is controversy over internal quality control (IQC) materials. It has been proposed that trueness materials supplied by the system's manufacturer with metrological traceability can be used to confirm that the performance of the measuring system is properly unbiased. This article focuses on the implementation challenges and operational hurdles of applying traceability concepts to IQC materials for trueness verification in medical laboratories regarding the most recent 2022 edition of ISO 15189 standard requirements for IQC and metrological traceability. There are practical considerations concerning the acquiring of IQC materials. We must acknowledge the limitations and restrictions that manufacturers and laboratories face before the recommendations can be applied in routine practices.

Contract-Based Hierarchical Modeling and Traceability of Heterogeneous Requirements

Contract-Based Hierarchical Modeling and Traceability of Heterogeneous Requirements

Exploring MBSE for asset digitalisation in the energy sector. A Battery Energy Storage System design study

This study explores an approach to improve the design process for complex systems in the energy industry, with a focus on how digitalisation-enhanced procedures and Model-Based System Engineering (MBSE) methodologies are assisting in their goals. The main purpose is to analyse how MBSE tools can be used for enhancing design and development. processes with special emphasis on Battery Energy Storage Systems (BESS). The use of digital technologies in the design process of complex systems expands the possibilities and ambitions of technological solutions. A complex system seeks to solve problems that address multiple areas of knowledge. For its design, collaboration in multidisciplinary teams is essential. The increase in the scope of projects makes it essential to formalize the integration of partial solutions in a System of Systems (SoS) that solves the general problem consistently and cohesively. In a more detailed case study, the present research applies System Composer from Mathworks for supporting requirements management, traceability, and system architecture design. Among the main findings of this contribution, it describes the use of MBSE and how it might integrate with digitalisation as well as servitization. Summarizing, this research states that the advantages of MBSE are the increase of efficiency in the internal processes, providing additional value in services to customers. In fact, there is a need for more research about the relationship of MBSE, digitalisation, and servitization.

Requirements Management Methods During Project Implementation in Conditions of Uncertainty

The purpose of the article is to study the issue of application of software requirements management methods during project management under conditions of uncertainty. It has been established that the management of requirements under conditions of uncertainty should be considered as permanent processes of system management of requirements throughout all stages of the project life cycle, which involves activities aimed at maintaining, tracking and checking requirements from the moment of their formation to their implementation and beyond. Based on the results of the research, it was found that the most common requirements management methods are: flexible (Agile) approach; advanced requirements analysis; the "Gradual Disclosure" method; models of iterative and incremental development; the "Minimum Viable Product" method; "Just-in-Time" method etc. It has been established that the use of software requirements management methods becomes especially relevant in conditions of uncertainty, as these methods allow you to effectively deal with dynamic changes and ensure the flexibility of the project. It was found that requirements management should focus on the organization, communication and development of requirements, among which the following can be distinguished: change management, traceability of requirements, communication, version control of requirements documents, etc. It has been investigated that change management involves making corrections to specified requirements during project implementation, as well as assessing the impact of corrections, obtaining permission to modify and update the necessary documents. Traceability, in turn, means defining and maintaining traceable relationships between requirements and other project artifacts, such as project documentation, test cases, and code. Therefore, traceability makes it possible to guarantee that all requirements are taken into account and corrections can be traced throughout the development of the project. At that time, communication facilitates effective communication between project stakeholders regarding the requirement and involves the conversion of updates, resolution of problematic aspects, and facilitating that all members of the working group have a common understanding of the formulated requirements. Also, control over the versions of requirements documents in order to track corrections in time. The obtained results of the conducted research serve as a basis for further research in the part of more effective use of requirements management methods during the implementation of projects in conditions of uncertainty.

Routes to standardisation for tau protein measurement in CSF

AbstractBackgroundCSF biomarkers are the target of several commercially available in vitro diagnostic (IVD) kits allowing an early diagnosis of Alzheimer’s disease (AD) and eventually the monitoring of treatment effects in clinical trials. Tau hyper‐phosphorylation is one of the main hallmarks of AD and its measurement provides higher accuracy to stratify patients at an early‐stage.Due to the rapid advancements in proteomics, standardisation of measurements can be achieved through the development of reference measurement procedures (RMPs) and certified reference materials (CRMs).MethodSI‐traceable protein and peptide primary calibrators were developed for t‐tau and p‐tau: mass fraction was determined by amino acid analysis and purity was assessed by LC‐MS at high resolution. CSF pools at different tau concentration were used for the development and validation of LC‐IDMS candidate RMP and their commutability was assessed.ResultAn LC‐IDMS candidate reference method was develop and validated in CSF for t‐tau using a SI‐traceable candidate protein primary calibrator. Three different CSF pools (low, medium, high) were successfully quantified with a relative expanded uncertainty below 10%. The commutability of 13 matrix‐based CRMs was assessed involving 8 immunoassays from 5 IVD providers by measuring 40 single CSF donations.According to the AT(N) classification, high levels of p‐tau(181) are highly correlated to tau pathology and commercially available immunoassays are able to target this specific epitope. We conducted a feasibility study on the development of a candidate reference method for p‐tau(181) in CSF relying on a SI‐traceable peptide primary calibrator and an antibody‐free sample preparation workflow.New assays targeting p‐tau(217) in CSF and plasma were also developed, making it necessary the organisation of standardisation initiatives. We sourced and characterised multiple phosphopeptide primary calibrators as well as a GSK3beta‐phosphorylated protein primary calibrator for the development of an LC‐MS RMP including an immunoprecipitation step in the sample preparation workflow.Conclusiontau is considered as a priority for the IFCC WG on NDD and the development of SI traceable RMPs and CRMs is essential to underpin a worldwide standardisation of results. This will help IVD providers to address the traceability requirements of the IVDR thus facilitating regulatory approvals of the kits.

Monitoring Techniques and Performance of Construction Projects in Rwanda. A case of Rehabilitation of Amahoro National Stadium in Gasabo District

This research aimed to evaluate the relationship between monitoring techniques and construction project performance in Rwanda, specifically in the rehabilitation of Amahoro National stadium. The study used a survey method with a well-structured questionnaire, with a sample size of 127 participants. Data was collected using descriptive statistical analysis, inferential statistics, and Pearson correlation (r) and multiple linear regression analysis. Results showed that 66.2% of participants agreed that requirements were well-planned in the rehabilitation of Amahoro National stadium, 89.8% agreed that requirements were communicated correctly, 63.7% agreed that process variation in the rehabilitation was consistent, and 68.5% agreed that project schedule status was continuously reviewed in meetings. Pearson correlation analysis revealed that the Requirement Traceability Matrix, control chart, and status review meeting all had positive and statistically significant relationships with project performance. The multiple regression model was significant, indicating that 57.2% of construction project performance can be attributed to the effectiveness of monitoring techniques used in the project. The researcher concluded that monitoring techniques have a positive effect on the performance of construction projects in Rwanda. To ensure inclusivity in the review process, the researcher recommends using status review meetings as an approach to communicate top-down project needs and reviewing from bottom-up. Customizing control charts to fit the specific project being monitored is highly recommended. For the rehabilitation of Amahoro stadium and other construction projects, owners should be keen to monitor progress to ensure effectiveness in performance. Keywords: Monitoring Techniques, Performance, Construction, Projects, Rwanda

Improved traceability in seafood supply chains is achievable by minimising vulnerable nodes in processing and distribution networks

Seafood is a globally traded commodity, often involving complex supply chains which have varying degrees of traceability. A robust traceability system for seafood supply chains enables the collection and communication of key information about catch and fisheries origins vital for assurance of the legality and sustainability of seafood products. End-to-end traceability is increasingly demanded by retailers, consumers, NGOs and regulatory bodies to ensure food safety, deter IUU fishing and verify sustainable and ethical credentials. Here, we map three UK seafood supply chains and evaluate traceability performance in: Dover sole landed in the south west of England, North-East Atlantic (NEA) mackerel landed at Peterhead, Scotland, and brown crab and European lobster, landed at Bridlington, England. Through a comparative analysis of traceability performance, this study suggests improvements to the technologies, processes, and systems for traceability in the seafood sector. The application of monitoring technologies and regulatory changes across the sector have increased traceability and potentially reduced instances of IUU fishing. While shorter supply chains are more likely to achieve end-to-end traceability, vulnerable nodes in processing and distribution networks may result in a loss of seafood traceability. While traceability systems may provide sustainability information on seafood, a high level of traceability performance does not necessarily equate to a sustainable source fishery. Encouragingly, while UK seafood supply chains are meeting minimum regulatory requirements for traceability, in the present study, many stakeholders have indicated ambitions towards traceability best practice in order to provide confidence and trust in the UK fishing industry.

Study on calibration method of electrical parameter tester for industrial digital electronic detonator

By the end of 2022, the civil explosive industry has realized the full use of industrial electronic detonators, which has promoted the upgrading of the electrical parameter tester of industrial electronic detonators. The original calibration method can no longer meet its traceability requirements. According to the working principle of the industrial digital electronic detonator electrical parameter tester, this paper studies the calibration method of the delay time, DC resistance (firing bridge wire resistance), DC current, internal crystal oscillator signal (frequency) and other parameters, simulates and assembles a set of measuring standard device, and analyzes the sources of uncertainty of the industrial digital electronic detonator electrical parameter tester, which is solved the problem of quantity value traceability of industrial digital electronic detonator electrical parameter tester in civil explosive industry.

Research and Application of Calibration Device for Fire Emergency Lighting Detector

In order to solve the problem of quantitative traceability of detection devices for fire emergency lighting and evacuation indication systems. Method analysis and research were conducted on parameters such as emergency switching time, emergency working time, DC charging voltage, DC discharge voltage, DC charging current, DC discharge current, environmental test temperature, and environmental test humidity. We searched for appropriate calibration methods for the technical characteristics of each parameter and designed a set of calibration devices for fire emergency lighting detectors. The test results show that the technical indicators of the calibration device can meet the traceability requirements of the fire emergency lighting and evacuation indication system.