Software Engineering Concepts Research Articles

Soft Computing-Based System for Performance Modeling of Object-Oriented Programming (OOP) Software

Performance is a vital attribute for most software, making performance investigation an essential software engineering task. The problem is that modern applications are challenging to analyse for performance. The advancement of Software engineering has seen the application of scientific approach at various stages of Software Development Life Cycle (SDLC). New technique is available for implementation known as soft computing. This approach is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or challenging to be modeled mathematically. The complexity, the commercial constraints and the expectation for high quality software demand, measuring the quality performance of an Object-Oriented Software (OOS). This work presents a set of testing metric (criteria) which hold the potential for ensuring remarkable improvements in quality performance of Object-Oriented software (OOS). A Prediction Model focused on identifying and evaluating the quality of the performance model based on the data set of software design components. The software design properties are comprehensive elucidated and integrating concepts of fuzzy logic and software engineering. The system enables the performance of modeling of Object-Oriented software using Fuzzy Inference System (FIS) to accurately predict the quality Object Oriented Software based on quality performance criteria such as reliability, efficiency, functionality and maintainability. Empirical validation of the results using checking data set is made to prove the usefulness of the design metrics and design quality attributes on the software prediction models. The purpose of this work is to provide development tool to solves practical problems, and focus on identifying and evaluating the quality performance of software design components. Again, the results demonstrate that, despite the research including approaches explicitly aimed at object-oriented software, there are substantial challenges in providing realistic feedback on the performance of large-scale object-oriented applications accordingly.

Revisiting Large Scale Defence Acquisition: Uncertainty and Acquisition Responsiveness

AbstractThis article re‐examines the model for large‐scale defence acquisition, aiming to establish a more adaptable framework that can effectively navigate the uncertainties of a dynamic and evolving operational environment. Drawing upon principles derived from Beer's Viable System Model (VSM), coupled with software engineering concepts from DevOps and innovation frameworks, the article proposes the development of a preliminary acquisition framework. The primary objective of this endeavour is to refine the framework, facilitating the creation of naval platforms that possess enhanced future‐proofing capabilities. Simultaneously, the aim is to minimize the time gap between significant acquisition decisions and achieving initial operating capability, all while upholding the fundamental requisites of the prevailing acquisition frameworks. Considering the extended operational lifespan of valuable assets, which can exceed two decades, there is a discernible risk that naval resources might become obsolete due to technological advancements driven by evolving adversarial threats. To counteract this potential scenario, it becomes imperative to regard naval acquisition as a continuous process, necessitating ongoing evolution and timely updates that align with the swiftly changing environmental conditions. This article asserts the significance of embracing a future‐proofing mindset. Such an approach holds the potential to curtail expenses associated with the swift and cost‐effective implementation of new capabilities as we advance into the future.

Software engineering for internet of underwater things to analyze oceanic data

Internet of Things (IoTs) represents a networked collection of heterogeneous sensors – enabling seamless integration between systems, humans, devices, etc. – to support pervasive computing for smart systems. IoTs unify hardware (embedded sensors), software (algorithms to manipulate sensors), and wireless network (protocols that transmit sensor data) to develop and operationalize a wide range of smart systems and services. The Internet of Underwater Things (IoUTs for short) is a specific genre of IoTs in which data about ocean ecosystems is continuously ingested via underwater sensors. IoUTs referred to as context-sensing eyes and ears under the sea operationalize a diverse range of scenarios ranging from exploring marine life to analyzing water pollution and mining oceanic data. This paper proposes a layered architecture that (i) ingests oceanic data as a sensing layer, (ii) computes the correlation between the data as an analytics layer, and (iii) visualizes data for human decision support via the interface layer. We unify the concepts of software engineering (SE) and IoTs to exploit software architecture, underlying algorithms, and tool support to develop and operationalize IoUTs. A case study-based approach is used to demonstrate the sensors’ throughput, query response time, and algorithmic execution efficiency. We collected IoUT sensor data, involving 6 distinct sensors from two locations including the Arabian Sea, and the Red Sea for 60 days. Evaluation results indicate (i) sensors’ throughput (daily average: 10000–20000 KB data transmission), (ii) query response time (under 30 ms), (iii) and query execution performance (CPU utilization between 60%–80%). The solution exploits SE principles and practices for pattern-based architecting and validation of emerging and next-generation IoUTs in the context of smart oceans.

Adopting Software Engineering Concepts in Scientific Research: Insights from Physicists and Mathematicians Turned Consultants

Adopting Software Engineering Concepts in Scientific Research: Insights from Physicists and Mathematicians Turned Consultants

Graph-based data management system for efficient information storage, retrieval and processing

Data management systems rely on a correct design of data representation and software components. The data representation scheme plays a vital role in how the data are stored, which influences the efficiency of its processing and retrieval. The system components design realizes software engineering concepts to enable performance metrics such as scalability, efficiency, flexibility, maintainability, and extendibility. This paper presents a data management system that uses a graph-based data representation scheme to achieve an efficient data retrieval when using graph-based databases. Input data are transformed into vertices, edges, and labels while inserting them into the database. The proposed system consists of three layers which are: system beans layer, data access layer, and the database engine. Healthcare data are used to evaluate the system in comparison with resource description framework (RDF) semantics. Extensive experiments are conducted to compare different scenarios of data storage and retrieval using Neo4J, OrientDB, and RDF4J. Experimental results show that the performance of the proposed graph-based approach outperforms RDF4J framework in terms of insertion and retrieval time.

USING SOFTWARE ENGINEERING TO DESIGN AND IMPLEMENT MIXER OF MULTIPLE CAMERAS, MICROPHONE, AND SCREENS

To connect with user media devices such as microphones and cameras, browsers formerly required Flash. Flash has essentially replaced Web Real-Time Communication (WebRTC) in recent years. The principles of WebRTC have not agreed on how browsers can capture audio, video, and data or screens. The major purpose of this research is to create a new WebRTC recording method that uses Google Chrome and Firefox to capture a mixture of cameras, microphones, and screens. In addition, this study used Software Engineering (SE) concepts such as the software design process and interface design, which is the description of a system's relationships with its environment, including the analysis and development of the designed systems. The MultiStreamsMixer.js libraries were used to design and implement a mixer of many cameras, microphones, and screens using the Ethernet and Wireless of the 4th generation (4G) network. The suggested technique also makes use of the JavaScript Library to capture audio, video, and screen (two-dimensional and three-dimensional animations); as well as numerous audio and video codecs, such as VP8 and VP9 for video and Opus for audio, were also utilized in Chrome and Firefox. Additionally, multiple bitrates ranging from 100 bytes per second to 1 Gigabit per second were also tested. Besides, various resolutions ranging from 480p to HD (3840* 2160) and frame rates ranging from 5 to 70, increasing by 5% each time were applied. In addition, the recording device, Quality of Experience (QoE) over real operators, and resources were evaluated.

Improving bioinformatics software quality through incorporation of software engineering practices.

BackgroundBioinformatics software is developed for collecting, analyzing, integrating, and interpreting life science datasets that are often enormous. Bioinformatics engineers often lack the software engineering skills necessary for developing robust, maintainable, reusable software. This study presents review and discussion of the findings and efforts made to improve the quality of bioinformatics software.MethodologyA systematic review was conducted of related literature that identifies core software engineering concepts for improving bioinformatics software development: requirements gathering, documentation, testing, and integration. The findings are presented with the aim of illuminating trends within the research that could lead to viable solutions to the struggles faced by bioinformatics engineers when developing scientific software.ResultsThe findings suggest that bioinformatics engineers could significantly benefit from the incorporation of software engineering principles into their development efforts. This leads to suggestion of both cultural changes within bioinformatics research communities as well as adoption of software engineering disciplines into the formal education of bioinformatics engineers. Open management of scientific bioinformatics development projects can result in improved software quality through collaboration amongst both bioinformatics engineers and software engineers.ConclusionsWhile strides have been made both in identification and solution of issues of particular import to bioinformatics software development, there is still room for improvement in terms of shifts in both the formal education of bioinformatics engineers as well as the culture and approaches of managing scientific bioinformatics research and development efforts.

The Internet of Things and Architectures of Big Data Analytics: Challenges of Intersection at Different Domains

The current exponential advancements in the Internet of Things (IoT) technologies pave a vast intelligent computing platform by integrating smart objects with sensing, processing and communication capabilities. The core element of IoT is the complex big data generated from different interconnected sources at real-time, presenting divergent processing and analysis challenges. Best practices in software engineering have been continuously addressed in IoT technologies to handle such big data efficiently at different domains. Despite of the massive studies dedicated for IoT, no explicit processing architecture is proposed based on real investigation of software engineering concepts and big data analytics characteristics in IoT. This paper provides a systematic literature review for the current state-of-the-art of IoT systems in different domains. The study investigates the current techniques and technologies that serve IoT systems from the big data analytics and software engineering perspectives, revealing a matrix for the specific IoT data features and their encountered challenges and gaps for each domain. The review deduces a proposed domain-independent software architecture for big IoT data analytics, maintaining various IoT data processing challenges, including data scalability, timeliness, heterogeneity, inconsistency, confidentiality and correlations. Finally, the main research gaps are emphasized for future considerations.

A multi-layered bigraphical modelling approach for context-aware systems

There exist several approaches proposed for building Context-Aware Systems (CAS). However, due to the continually changing environment, the large number of interrelated components, complexity and diversity of application domains make the modelling of context-aware systems a particularly challenging task. To address the increasing complexity of the modelling: i) It is critical to take into account the importance of the environment (operational context); and ii) rely on software engineering concepts such as abstraction and modularity in order to reduce the level of complexity. Also, a context-aware system may require intelligence and autonomy. These naturally lead us to apply intelligent agent-based engineering. This work introduces a formal layered design approach that combines intelligent control of multi-agent systems and bigraph's rigor to model context-aware systems. Bigraphical reactive systems are particularly compelling for their capacity to specify, simultaneously, the physical and logical distribution of system components and their interconnections using two distinct structures; that is: place graph and link graph. While the behaviour and dynamic evolution are expressed using defined reaction rules, and as a last step, the bigraph specifications are coded in the Maude language to allow their execution and the verification of their validity.

IBSI Education “SIWESI” Quality Measurement Based on System Technical Viewpoint

The need for information systems is increasing every year. The information system of an organization or company is useful for managing data to produce useful and effective information that supports activities and all levels of management that use it. The aspect of software quality is one of the important things in the development of a software. To determine the quality of software products, a measurement is needed. IBSI Education, one of which is a Tutoring Institution that uses “SiWeSi” to support administration, view schedules, see student progress, and so on. The success of the software that is built is based on whether or not the software works according to the objectives to be achieved. In the scientific concept of software engineering, the success of software is not only seen from the suitability of the resulting product to existing needs. The success of the software is also seen from the software development process. This study uses the McCall quality model because this method fulfills many components of the assessment and looks at quality from the user's point of view. The quality model used to measure the quality of SIWESI is determined from the results of the literature study.

Pengembangan Aplikasi Belajar Online Berbasis Web Menggunakan Waterfall

In this pandemic era, face-to-face learning cannot be done because the transmission of the virus is very dangerous and after all learning activities must continue, to improve the quality of education in Indonesia, therefore in this sophisticated era we must make the best use of technology for the wrong teaching and learning activities. the only way is by holding it online, but not all schools carry out learning activities with technology, there are still many who do conventional learning such as learning activities in school. The benefit of implementing online learning methods is to make it easier for teachers and students in terms of learning activities. The analysis method used is literature study. design methods that do use the concept of software engineering.

Requirements and Design Consistency: A Bi-directional Traceability and Natural Language Processing Assisted Approach

phase in the Software Development Life Cycle (SDLC). The design phase follows it. Traceability is one of the core concepts in software engineering; it is used to follow updates to make consistent items. This paper aimed to cover consistency through bi-directional traceability between requirements and design phase in a semi-automatic way. The Natural Language Processing (NLP) was used to analyze the requirements text and generate a class diagram; then, the generated items can be traced back to requirements. We developed a novel process to support consistency and bi-directional traceability. To ensure our proposed process's practical applicability, we implemented a tool named as Requirements and Design Bi-directional Traceability (RDBT). RDTB receives textual format requirements, performs NLP tasks (Tokenization, Part-of-Speech Tagging, etc.), generates UML class diagram, and finally performs traceability management to ensure consistency of requirements and UML class diagram. The work evaluation reveals good results, which indicates it can be used efficiently as a guide to generate the UML class diagram semi-automatically and manage traceability.

Requirements and Design Consistency: A Bi-directional Traceability and Natural Language Processing Assisted Approach

phase in the Software Development Life Cycle (SDLC). The design phase follows it. Traceability is one of the core concepts in software engineering; it is used to follow updates to make consistent items. This paper aimed to cover consistency through bi-directional traceability between requirements and design phase in a semi-automatic way. The Natural Language Processing (NLP) was used to analyze the requirements text and generate a class diagram; then, the generated items can be traced back to requirements. We developed a novel process to support consistency and bi-directional traceability. To ensure our proposed process's practical applicability, we implemented a tool named as Requirements and Design Bi-directional Traceability (RDBT). RDTB receives textual format requirements, performs NLP tasks (Tokenization, Part-of-Speech Tagging, etc.), generates UML class diagram, and finally performs traceability management to ensure consistency of requirements and UML class diagram. The work evaluation reveals good results, which indicates it can be used efficiently as a guide to generate the UML class diagram semi-automatically and manage traceability.

Android code smells: From introduction to refactoring

Object-oriented code smells are well-known concepts in software engineering that refer to bad design and development practices commonly observed in software systems. With the emergence of mobile apps, new classes of code smells have been identified by the research community as mobile-specific code smells. These code smells are presented as symptoms of important performance issues or bottlenecks. Despite the multiple empirical studies about these new code smells, their diffuseness and evolution along change histories remains unclear.We present in this article a large-scale empirical study that inspects the introduction, evolution, and removal of Android code smells. This study relies on data extracted from 324 apps, a manual analysis of 561 smell-removing commits, and discussions with 25 Android developers. Our findings reveal that the high diffuseness of mobile-specific code smells is not a result of releasing pressure. We also found that the removal of these code smells is generally a side effect of maintenance activities as developers do not refactor smell instances even when they are aware of them.

LEGO® Serious Play in Software Engineering Education

Nowadays, it is mandatory to complement the traditional learning methods with active ones that enhance the student's motivation and facilitate the development of technical and soft competences. LEGO®Serious Play is an experiential methodology designed to enhance innovation and performance in the business world and it is fully aligned with these needs. Previous researches show that this methodology has great potential in engineering education, and specifically in software engineering education. This paper presents an original LEGO®Serious Play activity to teach in a playful and active way software engineering concepts such as life cycle models and software development activities, which can be extrapolated to other engineering fields. This activity was validated through a case study involving 242 computer science students and it was supported by quantitative and qualitative data gathered from a survey and a post-test. The results indicate that the students found this activity highly fun and motivating as well as very useful to learn about the addressed topics and develop soft skills.

Florence: a Web-based Grammar of Graphics for Making Maps and Learning Cartography

Online, web-based cartography workflows use a dizzying variety of software suites, libraries, and programming languages. This proliferation of mapmaking technologies, often developed from a software engineering rather than a cartographic foundation, creates a series of challenges for cartography education, research, and practice.
 To address these challenges, we introduce a JavaScript-based open-source framework for web-based cartography and data visualization. It is built on top of existing open web standards that are already in intensive use for online mapmaking today, but provides a framework that is firmly based on cartographic and visualization theory rather than software engineering concepts. Specifically, we adopt concepts from Bertin’s Semiology of Graphics and Wilkinson’s Grammar of Graphics to create a language with a limited number of core concepts and verbs that are combined in a declarative style of “writing” visualizations. In this paper, we posit a series of design guidelines that have informed our approach, and discuss how we translate these tenets into a software implementation and framework with specific use cases and examples. We frame the development of the software and the discussion specifically in the context of the use of such tools in cartography education.
 With this framework, we hope to provide an example of a software for web-based data visualization that is in sync with cartographic theories and objectives. Such approaches allow for potentially greater cartographic flexibility and creativity, as well as easier adoption in cartography courses.

Innovative teaching practice on “software engineering laboratory course”

Teaching Software engineering is very difficult because it includes theory and practical approach. Applying the theoretical knowledge is very complex. At the same time theory can’t be understood without applying. In this paper, we present an innovative teaching practice on the course “Software Engineering Practical” by which students will have a practical knowledge. We use different teaching steps and software tools to build an interactive lab atmosphere for the students to learn, recognize and understand the concepts of software engineering.

Developed Authentication Method for Wireless Sensor Networks Based on Lightweight Protocol

Wireless Sensor Networks (WSNs) can be the most important solution for several problems, particularly in emergency cases. Software engineering security for WSN can confirm four goals including confidentiality, integrity, authentication, and availability. In this paper, an authentication method for WSN is proposed based on lightweight authentication and key management protocol as well as concepts of software engineering. Moreover, the interleaving process is added to the adopted protocol to improve the security side. The proposed method uses a Kath hashing in addition to salt and hash: the MD5 algorithm. This is to provide an allowance for the authentication of the added node to join the network. The proposed method is tested over different case studies and the obtained results show the superior performance for it in terms of processing the added nodes.

Design Pattern Elicitation Framework for Proof of Integrity in Blockchain Applications

An emerging technology with a secure and a decentralized nature, blockchain has the potential to transform conventional practices in an efficient and dynamic manner. However, migrating to blockchain can be challenging due to the complexity of its infrastructure and processes. The complexity of building applications on blockchain has been highlighted by many studies, thus stressing the need to investigate practical solutions further. A commonly known software engineering concept, software design pattern contributes to the acceleration of software development. It offers a holistic reusable solution for commonly occurring problems in a given context. It helps to identify problems that occur repetitively and describes best practices to address them. The present study is one of the first investigations to inquire into design patterns for blockchain application. Seeking to reduce the complexity in understanding and building applications on blockchain, this paper identifies a design pattern elicitation framework from similar blockchain applications. Next, it provides a demonstration of the Proof of Integrity (PoI) pattern elicited from two different applications on the blockchain. The applicability of the pattern is evaluated by building a blockchain application to verify the integrity of the academic certificates and by explaining how this integrity has been achieved empirically.

An Understandable, Extensible, and Reusable Implementation of the Hodgkin-Huxley Equations Using Modelica.

The Hodgkin-Huxley model of the squid giant axon has been used for decades as the basis of many action potential models. These models are usually communicated using just a list of equations or a circuit diagram, which makes them unnecessarily complicated both for novices and for experts. We present a modular version of the Hodgkin-Huxley model that is more understandable than the usual monolithic implementations and that can be easily reused and extended. Our model is written in Modelica using software engineering concepts, such as object orientation and inheritance. It retains the electrical analogy, but names and explains individual components in biological terms. We use cognitive load theory to measure understandability as the amount of items that have to be kept in working memory simultaneously. The model is broken down into small self-contained components in human-readable code with extensive documentation. Additionally, it features a hybrid diagram that uses biological symbols in an electrical circuit and that is directly tied to the model code. The new model design avoids many redundancies and reduces the cognitive load associated with understanding the model by a factor of 6. Extensions can be easily applied due to an unifying interface and inheritance from shared base classes. The model can be used in an educational context as a more approachable introduction to mathematical modeling in electrophysiology. Additionally the modeling approach and the base components can be used to make complex Hodgkin-Huxley-type models more understandable and reusable.