Requirements to Products and Processes for Software of Safety Important NPP I&C Systems

Features of software as a component of instrumentation and control (I&C) systems are analyzed. Attention is paid to the importance of functions performed by software and hazards of such software. Requirements for characteristics of software as a component of I&C systems are analyzed. Different regulatory documents are considered in order to disclose common approaches to the use of dedicated software and off-the-shelf software components. Classification of software, as well as classification of requirements, is described. Criteria of selection and structuring of requirements, as well as criteria for software verification, are defined. As long as the characteristics of software components directly depend on the quality of the processes of software development and verification, requirements for software life cycle processes are considered.

Disciplined or Agile?

Software requirements changes become necessary due to changes in customer requirements and changes in business rules and operating environments; hence, requirements development, which includes requirements changes, is a part of a software process. Previous studies have shown that failing to manage software requirements changes well is a main contributor to project failure. Given the importance of the subject, there is a plethora of efforts in academia and industry that discuss the management of requirements change in various directions, ways, and means. This chapter provided information about the current state-of-the-art approaches (i.e., Disciplined or Agile) for RCM and the research gaps in existing work. Benefits, risks, and difficulties associated with RCM are also made available to software practitioners who will be in a position of making better decisions on activities related to RCM. Better decisions can lead to better planning, which will increase the chance of project success.

Fuzzy Ontology for Requirements Determination and Documentation During Software Development

Every business has an underlying information system. Quality and creditability of a system depend mainly on provided requirements. Good quality requirements of a system increase the degree of quality of the system. Hence, requirements determinations is of prime importance. Inadequate and misunderstood requirements are major problems in requirements determination. Major stakeholders of the requirements are non-computer professional users, who may provide imprecise, vague, and ambiguous requirements. Further, the system development process may be partly automated and based on platform such as web or Semantic Web. In this case, a proper ontology to represent requirements is needed. The chapter proposes a fuzzy RDF/XML-based ontology to document various requirements. A generic architecture of requirements management system is also provided. To demonstrate the presented approach, a case of student monitoring and learning is presented with sample software requirements specifications and interfaces to collect requirements. The chapter concludes with advantages, applications, and future enhancements.

Design of a Home Automation App to Assist Elderly and Limited Mobility People

This research focuses on a solution to assist elderly and limited-mobility people. It aims to improve the autonomy, and, consequently, the quality of life of this target audience by automating daily tasks conducted at home, such as turning on the lights and manipulating electronic devices. However, it is important to consider the costs and quality attributes (e.g., usability) related to the design of solutions to automate a specific environment, that may include hardware platforms and physical adaptations. In this context, the authors present in this chapter the software requirements discovery and elicitation of a home automation app considering the real needs of the elderly and limited-mobility people. Additionally, we conduct the requirements specification using the unified modeling language (UML) to improve completeness, along with graphical user interface (GUI) prototypes. Finally, we present a mobile app prototype using the Android and Arduino platforms to illustrate a use scenario of the solution.

Studying human-to-computer bias transference

It is generally agreed that one origin of machine bias is resulting from characteristics within the dataset on which the algorithms are trained, i.e., the data does not warrant a generalized inference. We, however, hypothesize that a different ‘mechanism’ may also be responsible for machine bias, namely that biases may originate from (i) the programmers’ cultural background, including education or line of work, or (ii) the contextual programming environment, including software requirements or developer tools. Combining an experimental and comparative design, we study the effects of cultural and contextual metaphors, and test whether each of these are ‘transferred’ from the programmer to the program, thus constituting a machine bias. Our results show that (i) cultural metaphors influence the programmer’s choices and (ii) contextual metaphors induced through priming can be used to moderate or exacerbate the effects of the cultural metaphors. Our studies are purposely performed with users of varying educational backgrounds and programming skills stretching from novice to proficient.

Development of a model of selecting cloud software for a road construction organization under interval information

The object of research is the management processes of a road construction organization. The research is based on the principles of systems analysis for structuring design processes; methods of mathematical modeling, fuzzy mathematics, discrete programming, multicriteria assessment and optimization for the selection of cloud software for road construction organizations in terms of interval information. The information system of a road construction organization includes planning, reporting, regulatory and technical documentation that characterizes the state and movement of information in the enterprise. It is important to use systems that speed up the generation, processing and preparation of documents, as well as improve the storage and retrieval of information. The introduction of cloud technologies has become a necessary condition for increasing the mobility, flexibility and efficiency of the management system of a road construction organization. Formalized processes of information collection and internal distribution can better predict the dynamics of market trends and act more quickly, make decisions confidently and reasonably. In the final stages of selection for assessment, it is convenient to apply the criteria in conditions of interval uncertainty. The study was aimed at improving the efficiency of transport management by developing a model for choosing the cloud software of a road construction organization in terms of interval information. The following criteria of partial optimization were used in the developed model: maximum speed of execution of functions by cloud software; minimum cloud software requirements for internet connection speed; minimum cost of cloud software. The scope of permissible solutions is determined by restrictions: – execution of all functions must be provided by cloud software; – the minimum speed of execution of functions by the cloud software should be not lower than set; – cloud software requirements for Internet connection speed should not exceed the specified; – the cost of cloud software should be no more than specified. The developed model will reduce the cost of purchasing cloud software and increase the efficiency of transport management of a road construction organization.

Supporting Classification of Software Requirements system Using Intelligent Technologies Algorithms

The important first stage in the life cycle of a program is gathering and analysing requirements for creating or developing a system. The classification of program needs is a crucial step that will be used later in the design and implementation phases. The classification process may be done manually, which takes a lot of time, effort, and money, or it can be done automatically using intelligent approaches, which takes a lot less time, effort, and money. Building a system that supports the needs classification process automatically is a crucial part of software development. The goal of this research is to look into the many automatic classification approaches that are currently available. To assist researchers and software developers in selecting the suitable requirement categorization approach, those requirements were divided into functional and non-functional requirements. since natural language is full of ambiguity and is not well defined, and has no regular structure, it is considered somewhat variable. This paper presents machine requirement classification where system development requirements are categorized into functional and non-functional requirements by using two machine learning approaches. During this research paper, MATLAB 2020a was used, as well as the study's results indicate When applying Multinomial Naive Bayes technology, the model achieves the highest accuracy of 95.55 %,93.09 % sensitivity, and 96.48 % precision, However, when using Logist Regression, the suggested model has a classification accuracy of 91.23 %,91.54 % sensitivity, and 94.32 % precision.