Measurement in Software Engineering

Measurement in software is a basic process in all parts of the software development life cycle because it helps to express the quality of a software. But in software engineering, measurement is difficult and not precise. However, researchers accept that any measure is better than zero measure. In this chapter, the software metrics are explained, and some software testing tools are introduced. The software metric sets of Chidamber and Kemerer Metric Set (CK Metric Set), MOOD Metric Set (Brito e Abreu Metric Set), QMOOD Metric Set (Bansiya and Davis Software Metric Set), Rosenberg and Hyatt Metric Set, Lorenz and Kidd Metric Set (L&K Metric Set) are explained. The software testing tools such as Understand, Sonargraph, Findbugs, Metrics, PMD, Coverlipse, Checkstyle, SDMetrics, and Coverity are introduced. Also, 17 literature studies are summarized.

Synthesis of MOF, MDA, PIM, MVC, and BCE Notations and Patterns

Publications, including academic handbooks, contain numerous inconsistencies in the descriptions of applications of architectural methods and patterns hidden under the abbreviations such as MOF, MDA, PIM, MVC, BCE. An efficient analysis and the following software design, particularly when we are speaking of projects realized in large teams, requires standardization of the production process and the applied patterns and frameworks. This study attempted to sort out the system of notations describing this process and used to describe architectural patterns. Analysis of key notations—MOF and MDA, patterns MVC and BCE—was carried out, and a consistent system combining them into a whole was created.

Lowering Coupling in Distributed Applications With Compliance and Conformance

The interaction of applications in distributed system raises an integration problem that application-developing methods need to solve, even if the initial specifications change, which is actually the normal case. Current integration technologies, such as Web Services and RESTful APIs, solve the interoperability problem but usually entail more coupling than required by the interacting applications, since they share data schemas between applications, even if they do not actually exercise all the features of those schemas. The fundamental problem of application integration is therefore how to provide at most the minimum coupling possible while ensuring at least the minimum interoperability requirements. This chapter proposes compliance and conformance as the concepts to achieve this goal by sharing only the subset of the features of the data schema that applications actually use, with the goal of supporting a new architectural style, structural services, which seeks to combine the advantages of both SOA and REST.

A Blood Bank Management System-Based Internet of Things and Machine Learning Technologies

Nearly all of the Egyptian hospitals are currently suffering from shortage in rare blood types (e.g., -AB, -B, +AB), which are needed to perform vital surgeries. This leads them (hospitals or doctors) to ask patients' relatives to donate the amount of the required blood. The alternative is that they are forced to pay for the blood if the required type and amount is already available in these hospitals or the blood banks. The main idea of this work is solving problems related to the blood banks from collecting blood from donators to distributing blood bags for interested hospitals. This system is developed in order to enhance the management, performance, and the quality of services for the management of blood banks, which will be positively reflected on many patients in hospitals. This chapter targets undergraduate students, academic researchers, development engineers, and course designers and instructors.

Software Architecture Patterns in Big Data

Traditional monolithic systems are composed of software components that are tightly coupled and composed into one unit. Monolithic systems have scalability issues as all components of the entire system need to be compiled and deployed even for simple modifications. In this chapter, the evolution of the software systems used in big data from monolithic systems to service-oriented architectures was explored. More specifically, the challenges and strengths of implementing service-oriented architectures of microservices and serverless computing were investigated in detail. Moreover, the advantages of migrating to service-oriented architectures and the patterns of migration were discussed.

The Role of Science, Technology, and the Individual on the Way of Software Systems Since 1968

The NATO conference held in Garmisch in 1968 was on the future of the computer and software world, and it presented the process of realization of what has been talked about in those dates to the present day. This chapter also examines the development of software systems since 1968, depending on the technological developments. The contribution of mathematics and physics to the development of information systems was explained in chronological order by comparing the possibilities of yesterday and today. Complementary contributions of science and technology have been evaluated in the evolutionary and revolutionary developments ranging from the definition of information theory in 1948 to teleportation. It can clearly be seen that discrete mathematics directly affects the improvements in computer science. This review study clearly shows that it would not be possible to talk about digital transformation and quantum computation if the discoveries of Shannon, Turing and Neumann, and the studies of other scientists before them did not exist.

A General Overview of RESTful Web Services

This chapter aims to present a general overview of today's dominant software architectural style for developing web services, namely REST, by comparing the core elements of this paradigm with the big web service model. The study evaluates the HTTP requests, responses, and thus, the SOAP/JSON payloads involved in consuming a big web service and a RESTful service that is developed in the ASP.NET Core Web API framework. After summarizing the REST constraints, the chapter elucidates how the example RESTful web service satisfies these constraints and lists some scenarios suited to each paradigm. The study notes the object-oriented elements that are inherent in RESTful services, specifically how polymorphism and abstraction principles can be applied to RESTful services.

Big Data Processing

Big data has attracted significant and increasing attention recently and has become a hot topic in the areas of IT industry, finance, business, academia, and scientific research. In the digital world, the amount of generated data has increased. According to the research of International Data Corporation (IDC), 33 zettabytes of data were created in 2018, and it is estimated that the amount of data will scale up more than five times from 2018 to 2025. In addition, the advertising sector, healthcare industry, biomedical companies, private firms, and governmental agencies have to make many investments in the collection, aggregation, and sharing of enormous amounts of data. To process this large-scale data, specific data processing techniques are used rather than conventional methodologies. This chapter deals with the concepts, architectures, technologies, and techniques that process big data.