Specification Of Non-functional Requirements Research Articles

User Centered Non-Functional Requirements Specification – An Extended Use-Case Diagram

Requirements Engineering (RE) activity is often initiated with vaguely specified software requirements. The ambiguities must be overcome to the extent possible when the requirements are specified. Both functional (FRs) and non-functional (NFRs) requirements should be correctly and unambiguously specified. Users communicate about the NFRs in informal discussions. Requirements engineers use formal or semi-formal language notations to manually convey the NFRs. A laborious and ineffective manual approach, however, is unable to identify all likely NFRs and resolve ambiguities in those NFRs. This paper discusses an approach that attempts to overcome ambiguities from natural language requirements, recognize NFRs, and generate NFR specification through the extended Unified Modelling Language (UML) viz. use-case diagram. The empirical evaluation of the proposed approach on the PROMISE dataset achieves an average result of 79.76% recall, 90.05% precision, and 84.59% F-measure. The proposed approach allows the requirements analyst to semi-automatically recognize NFRs and visualize them using an extended use-case diagram at an early stage of RE.

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An Ontology as Support for Specification of Non-functional Requirements of AAL Systems Considering Compliance Aspects

Abstract Ambient assisted living (AAL) is a technological approach that emerged to meet the demands of seniors and people with disabilities. Because they are considered complex and multidisciplinary systems, it is necessary to identify and define which elements need to compose these systems. These challenges and the need for assistance in specifying requirements have led the academic community to explore and establish new approaches for the development of AAL systems. For this, there is the integration of different areas of knowledge, such as ontology, requirements engineering and compliance. Therefore, this work presents a central ontology to support the specification of requirements in AAL systems, where the elements that are part of the type of system are integrated. With the use of this ontology, it was possible to develop a domain ontology for vertical elevation platforms, where a validation was carried out with the industry in relation to the elements that constitute it and, later, a scenario was built to verify the syntactic correction of ontology. With the use of ontology, it will be possible to standardize the understanding of the associated terms and, at the same time, verify the relationships between the elements and help the designer in the requirements specification stage.

Automatically classifying non-functional requirements using deep neural network

Non-functional requirements are property that software products must have in order to meet the user’s business requirements, and are additional constraints on the quality and characteristics of software systems. They are generally written by software designers and documented in various parts of requirements documentation. When developing systems, developers need to classify non-functional requirements from requirements documents, and classifying these non-functional requirements requires professional skills, experience, and domain knowledge, which is challenging and time-consuming for developers. It would be beneficial to implement automatic classification of non-functional requirements from requirements documents, which could reduce the manual, time, and mental fatigue involved in identifying specific non-functional requirements from a large number of requirements. In this paper, a deep neural network model called NFRNet is designed to automatically classify non-functional requirements from software requirement documents. The network consists of two parts. One is an improved BERT word embedding model based on N-gram masking for learning context representation of the requirement descriptions, and the other is a Bi-LSTM classification network for capture context information of the requirement descriptions. We use a Softmax classifier in the end to classify the requirement descriptions. At the same time, in order to accelerate the training and improve the generalization ability of the model, the network uses multi-sample dropout regularization technology. This new regularization technology can reduce the number of iterations needed for training, accelerate the training of deep neural networks, and the networks trained achieved lower error rates. In addition, we expanded the original non-functional requirements dataset (PROMISE dataset) and designed a new dataset called SOFTWARE NFR. The new dataset far exceeds the original dataset in terms of the number of requirement description sentences and the number of non-functional requirements categories. It can be taken as a new testbed for non-functional requirements classification. Through cross-validation on the new dataset, the experimental results show that the network designed in this paper is significantly better than the other 17 classification methods in terms of Precision, Recall, and F1-score. At the same time, for the training set and the validation set, using the multi-sample dropout regularization technology can accelerate the training speed, reduce the number of iterations, and achieve lower error rates and loss.

Studying the commonalities, mappings and relationships between non-functional requirements using machine learning

Studying the interactions and relationships between non-functional requirements (NFRs) is important when developing software applications. This is because that a specific NFR may conflict, overlap or complement other NFRs. Moreover, one NFR may include characteristics and features of other NFRs. Most of the current studies focused on classifying NFRs into distinct different categories without considering the common characteristics or the relationships between these categories. This paper provides a study on how the results of various machine learning (ML) classifiers can be visualized and analyzed with the help of confusion matrices and principal component analysis (PCA) tools in order to examine the commonalities, mappings and relationships between NFRs. And to define which NFRs are mostly distinct and which NFRs are mostly overlapping. The paper also defines which ML classifier achieves the best performance through various classifications of NFRs. The experiments were performed using five different ML classifiers on the newly expanded PROMISE dataset and the achievements of these classifiers are evaluated based on precision, recall and F1-Score metrics. The results of this research help practitioners and researchers in the field of software engineering to pay more attention on the behavior of various NFRs. • ML techniques help in examining the behavior of NFRs. • ML techniques assist in defining the mostly distinct NFRs and the mostly overlapped NFRs. • ML classifiers perform better when understating the behavior of NFRs. • It is not necessarily for a classifier to perform better when the number of NFRs and their labels becomes smaller.

Formal Specification of Non-Functional Properties of Context-Aware Systems

During the recent years, there is an increasing demand for software systems that dynamically adapt their behavior at run-time in response to changes in user preferences, execution environment, and system requirements, being thus context-aware. Authors are referring here to requirements related to both functional and non-functional aspects of system behavior since changes can also be induced by failures or unavailability of parts of the software system itself. To ensure the coherence and correctness of the proposed model, all relevant properties of system entities are precisely and formally described. This is especially true for non-functional properties, such as performance, availability, and security. This article discusses semantic concepts for the specification of non-functional requirements, taking into account the specific needs of a context-aware system. Based on these semantic concepts, we present a specification language that integrates non-functional requirements design and validation in the development process of context-aware self-adaptive systems.

Web services selection a perspective of computational physics

Concerning computational physics, web services are conceived as mathematical units that are experienced in different systems that offer service composition. Due to the exponential growth of web services and their deployment on cloud platforms, quality of service parameters have now become an essential factor when searching for and selecting services that must satisfy specific non-functional requirements of a user application. A variety of service components are highly configurable and are dynamic scenarios because a significant number of services can meet these requirements. This work analyzes the systemic perspective of approaches for the selecting and searching of web services that have specifications of optimization strategies based on the configurable quality of service parameters with test scenarios in cloud environments that have a considerable number of services as input. The study shows that policies based on artificial intelligence and related areas are the ones with the most significant convergence, and the approaches analyzed to give a perspective of future work aimed at strategies based on automatic learning.

사이버 물리 시스템의 실시간 협업 환경에서 소프트웨어 비기능 요구사항의 모델 기반 명세

사이버 물리 시스템의 실시간 협업 환경에서 소프트웨어 비기능 요구사항의 모델 기반 명세

A Method for Verifying Non-Functional Requirements

In order to verify the correctness of functional requirements, we have been developing a verification method of the correctness of functional requirements specification using the Requirements Frame model. In this paper, we introduce a verification method of non-functional requirements specification, especially time-response requirements and usability requirements written with a natural language. We establish a verification method by extending the Requirements Frame model. We have also developed a prototype system based on the method using Java. The extended Requirements Frame model and the verification method will be illustrated with examples.

Specification of Non-Functional Requirements (NFRs) in Request for Proposal (RFP)

Software Requirement Analysis is one of the most important and critical activity of software development, that affects the development cost and success of end product. This paper proposes to add both formal and informal specifications of NFR to Request for Proposal document. It ought the developers to focus on each NFR right from the beginning of development process. In this paper NFRs are specified informally by extended use case and formally by proposed extension to Formal Reference Model. The paper claims that the proposed add-ons related to NFRs are qualitative one and can be considered as standard add-ons in RFP documents to deal with NFRs. It shall act as important step during early planning system for designing and implementing proposed software. The complete procedure is illustrated using a general case of cafeteria ordering framework.

A Bio-Inspired Model-Based Approach for Context-Aware Post-WIMP Tele-Rehabilitation.

Tele-rehabilitation is one of the main domains where Information and Communication Technologies (ICT) have been proven useful to move healthcare from care centers to patients’ home. Moreover, patients, especially those carrying out a physical therapy, cannot use a traditional Window, Icon, Menu, Pointer (WIMP) system, but they need to interact in a natural way, that is, there is a need to move from WIMP systems to Post-WIMP ones. Moreover, tele-rehabilitation systems should be developed following the context-aware approach, so that they are able to adapt to the patients’ context to provide them with usable and effective therapies. In this work a model-based approach is presented to assist stakeholders in the development of context-aware Post-WIMP tele-rehabilitation systems. It entails three different models: (i) a task model for designing the rehabilitation tasks; (ii) a context model to facilitate the adaptation of these tasks to the context; and (iii) a bio-inspired presentation model to specify thoroughly how such tasks should be performed by the patients. Our proposal overcomes one of the limitations of the model-based approach for the development of context-aware systems supporting the specification of non-functional requirements. Finally, a case study is used to illustrate how this proposal can be put into practice to design a real world rehabilitation task.

Extended Use Case for Specification of NFRs

The evolution of unified modelling language (UML) is absolutely required to make sure that UML will stay up to date with the latest developments in the software industry like modeling non-functional requirements (NFRs). In the past NFR literature many techniques have been identified that have used UML for modelling NFR. Because of great diversity in number and types of NFR it is difficult to be handled by common modelling techniques. So we think of extension of Use Case so that it can more effectively address the changing needs of many different classes of users and NFRs which further assists in specification and quantification of NFR.

Towards Model-Driven V&V assessment of railway control systems

Verification and Validation (V&V) activities aiming at certifying railway controllers are among the most critical and time-consuming in system development life cycle. As such, they would greatly benefit from novel approaches enabling both automation and traceability for assessment purposes. While several formal and Model-Based approaches have been proposed in the scientific literature, some of which are successfully employed in industrial settings, we are still far from an integrated and unified methodology which allows guiding design choices, minimizing the chances of failures/non-compliances, and considerably reducing the overall assessment effort. To address these issues, this paper describes a Model-Driven Engineering approach which is very promising to tackle the aforementioned challenges. In fact, the usage of appropriate Unified Modeling Language profiles featuring system analysis and test case specification capabilities, together with tool chains for model transformations and analysis, seems a viable way to allow end-users to concentrate on high-level holistic models and specification of non-functional requirements (i.e., dependability) and support the automation of the V&V process. We show, through a case study belonging to the railway signalling domain, how the approach is effective in supporting activities like system testing and availability evaluation.

Lessons from Developing Nonfunctional Requirements for a Software Platform

Employing a software platform is an approach to achieve a higher degree of software reuse by enabling multiple software products to share the platform-provided services. However, platform development usually involves stakeholders from different application domains. Their application situations vary widely and thus nonfunctional requirements (NFRs) for the software platform must address a wider range of needs than those for a single product. This article describes lessons learned in developing NFRs for a large software platform, the challenging issues, and the techniques used to address them. The techniques are pragmatic and helped with NFR reconciliation and management. The improved quality of the NFR specifications has permitted automation of platform performance testing for the past two years.

Semantic Management of Nonfunctional Requirements in an e-Health System

We have designed an ontological environment that makes provisions for choosing adequate devices for remote monitoring of patients who are suffering from poststroke health complications. We argue that nonfunctional requirements in e-health systems, designed for remote patient monitoring, can be managed through semantics stored in ontological models and reasoning performed on them. Our contribution is twofold: (1) we address the pervasiveness of e-health systems by choosing devices embedded in them, and through patients' expectations in terms of having access to pervasive health services personalized to their needs; and (2) we enrich the specification of nonfunctional requirements for remote patient monitoring by highlighting their role in the development of e-healthcare systems.

REquirements, Aspects and Software Quality: the REASQ model.

Object-oriented analysis and design have been more concerned with system functionality, neglecting non-functional aspects; the result is code which is tangled and dicult to maintain, contradicting main principles of object orientation. Aspect Oriented Software Development (AOSD) proposes the early specification of non-functional requirements. However, a standard and homogenous vision of the AOSD terminology is still missing. The goal of this work is to integrate AOSD concepts, classic requirements engineering notions, and the new standard ISO/IEC 25030 on software quality requirements.The main result of this study is the REASQ (REquirements, Aspects and Software Quality) conceptual model, expressed in UML. All the modelling concepts are formalized into three related ontologies, representing the ambits of aspect-orientation, software quality and requirements engineering. The ontologies can be used as an umbrella to specify quality requirements in aspect-oriented engineering processes.

Fuzzy quality function deployment based methodology for acquiring enterprise software selection requirements

In many software acquisition methods, functional software requirements are resolved, but non-functional requirements are more or less deliberately put aside. A large body of research exists on the necessity of handling specific non-functional requirements as major drivers in the software development process. However, prior research does not provide adequate support for managing non-functional requirements in the software selection process, and suggests a unique technique and methodology for identifying the selection criteria. This paper presents a fuzzy quality function deployment approach for determining which of the non-functional requirements reported by earlier studies are important to a company’s software selection decision based on and integrated with its functional requirements. The solution provided in this study not only assists decision makers in acquiring software requirements and defining selection criteria, but also supports determining the relative importance of these criteria. An actual case in Audio Electronics of Turkey’s electronic industry demonstrates the feasibility of applying the proposed framework in practice.