Software Engineering Discipline Research Articles

Bringing Software Engineering Discipline to the Development of AI-Enabled Systems

Bringing Software Engineering Discipline to the Development of AI-Enabled Systems

Optimizing Disaster Response: OptiDrone- Advanced Integration of Dijkstra's Algorithm and Cutting-Edge Software Solutions for UAV Path Planning and Obstacle Avoidance Efficiency

The objective of the research is development of a specific concept called "OptiDrone," which is based on the integration of Dijkstra's Algorithm and the latest development of aerial vehicles' path planning and obstacle avoidance efficacy. The study involves a combination of theoretical and algorithmic refinement as well simulation-based experiments to test the effectiveness of OptiDrone in dynamic disaster scenarios. OptiDrone's combination of powerful route planning techniques along with advanced software programs is set to achieve a substantially higher response rate and operational resilience in the face of difficulties. The results add much value to the body of knowledge about UAV-assisted disaster management systems, indicating possible gains in efficiency and timeliness while addressing crisis situations. Different disciplines of disaster management, robotics, and software engineering can benefit from this research, which is a significant milestone towards the use of more efficient and innovative unmanned aerial systems in disaster response.

Adopting DevOps practices: an enhanced unified theory of acceptance and use of technology framework

<div align="center"><span lang="EN-US">DevOps software development approach is widely used in the software engineering discipline. DevOps eliminates the development and operations department barriers. The paper aims to develop a conceptual model for adopting DevOps practices in software development organizations by extending the unified theory of acceptance and use of technology (UTAUT). The research also aims to determine the influencing factors of DevOps practices’ acceptance and adoption in software organizations, determine gaps in the software development literature, and introduce a clear picture of current technology acceptance and adoption research in the software industry. A comprehensive literature review clarifies how users accept and adopt new technologies and what leads to adopting DevOps practices in the software industry as the starting point for developing a conceptual framework for adopting DevOps in software organizations. The literature results have formulated the conceptual framework for adopting DevOps practices. The resulting model is expected to improve understanding of software organizations’ acceptance and adoption of DevOps practices. The research hypotheses must be tested to validate the model. Future work will include surveys and expert interviews for model enhancement and validation. This research fulfills the necessity to study how software organizations accept and adopt DevOps practices by enhancing UTAUT.</span></div>

Systematic literature review on global software development based software cost estimation models and cost drivers

<p>Global software development (GSD) is a well - established discipline of software engineering that focuses on the advantage of a global environment. Effective cost estimation is critical for the success of GSD projects. Cost estimation in a GSD environment is a challenging task. As a re sult, GSD must emphasize cost estimation. Findings show that a number of researchers over the past few decades have emphasized GSD - based cost estimation in GSD; to the best of our knowledge, however, existing cost estimation have not taken into account man y GSD - based cost drivers that must be considered when estimating costs. Motivated by all this, the purpose of this study is to review the existing GSD - based cost estimation models/techniques and cost drivers that influence the accuracy of cost estimation. To identify and compile relevant research papers, a systematic literature review was carried out. From twenty - seven selected studies, initially, 86 GSD - based cost drivers and 12 GSD - based cost estimation models/techniques were extracted. After filtration, 26 cost drivers were identified as significant and to be considered in GSD - based cost estimation. This study significantly identifies GSD - based cost drivers and existing cost estimation techniques.</p>

Enhancing software engineering education in higher education institutions through cloud-based learning tools: methodological and practical perspectives

Objective: This study aims to develop a comprehensive methodology for integrating cloud-based learning tools into software engineering education for students in higher education institutions (HEIs).Research tasks: The research encompasses exploring the psychological and pedagogical aspects of software engineering education in HEIs, investigating the influence of cloud technologies on higher education, designing a robust model for implementing a methodological system that incorporates cloud-based learning tools, and conducting an experimental implementation of the proposed model.Research focus: The research focuses on the teaching and learning process of software engineering disciplines among students in HEIs, specifically emphasizing the utilization of cloud-based learning tools.Research methods: The research methodology involves analyzing relevant scholarly publications, dissertations, conference proceedings, and seminars, along with studying the experiences of educators through surveys and questionnaires. Additionally, the research incorporates practical experimentation with cloud-based learning tools.Research findings: The study highlights the crucial need to prioritize fundamental knowledge acquisition in software engineering education, which can be facilitated by the mobility features inherent in cloud-based learning tools. Furthermore, it reveals a significant correlation between emerging trends in information technology and the development of methodological teaching systems. The analysis underscores the transformative impact of cloud technologies on learning tools and other key components of the methodological teaching system. The research successfully implements an experimental model that integrates cloud-based learning tools into the methodological system.Conclusions and recommendations: The findings demonstrate that cloud technologies profoundly influence the technological aspects of the methodological system while simultaneously shaping the objectives and curriculum of IT professionals. The developed methodological system, which incorporates cloud technologies, plays a pivotal role in fostering the foundational education of IT professionals.

No Silver Bullets, Only Disciplined Reflections to Guide Course Corrections [From the Editor

In this article I reflect on the legacy of Frederick P. Brooks on the discipline of software engineering through the perspective of his infamous “no silver bullet” quote.

Assessing attitudes towards evidence-based software engineering in a government agency

Evidence-based practice (EBP) has allowed several disciplines to become more mature by emphasizing the use of evidence from well-designed and well-conducted research in decision-making. Its application in SE, Evidence-based software engineering (EBSE) can help to bridge the gap between academia and industry by bringing together academic rigor and research of practical relevance. To achieve this, it seems necessary to improve its adoption. We sought both to study the attitudes towards EBSE of stakeholders working in a government agency (GA) and to assess whether knowledge of EBSE would impact their working practices. We conducted a multi-stage field investigation in an Uruguayan national GA that is responsible for digital policies. First, we organized an EBSE awareness lecture and we collected and analyzed participants’ perceptions of the value and limitations of EBSE. Sixteen months later, in a second stage, we contacted the agency and asked participants whether they had made use of the information about EBSE we presented to them. Initially, participants reported that EBSE seemed useful for tackling challenging problems and, in particular, considered its use appropriate given the agency’s responsibilities. Perceived barriers to EBSE adoption were the need for institutional support, the lack of government practice reports, inadequate skills or motivation, the cost of conducting systematic reviews, and the lack of evidence about emerging issues. In the follow-up survey, although the participants were not undertaking systematic reviews themselves, many reported improvements in how they searched for and evaluated information to support their work. Our study presents some insights to better understand EBSE adoption. With the exception of GA-specific issues, perceived value and barriers to adoption were consistent with those reported in software engineering and other disciplines. Our follow-up study confirms the potential value of evidence in the context of IT regulatory and government bodies.

Software Fault Prediction Using an RNN-Based Deep Learning Approach and Ensemble Machine Learning Techniques

Alongside the modern software development life cycle approaches, software testing has gained more importance and has become an area researched actively within the software engineering discipline. In this study, machine learning and deep learning-related software fault predictions were made through a data set named SFP XP-TDD, which was created using three different developed software projects. A data set of five different classifiers widely used in the literature and their Rotation Forest classifier ensemble versions were trained and tested using this data set. Numerous publications in the literature discussed software fault predictions through ML algorithms addressing solutions to different problems. Some of these articles indicated the usage of feature selection algorithms to improve classification performance, while others reported operating ensemble machine learning algorithms for software fault predictions. Besides, a detailed literature review revealed that there were few studies involving software fault prediction with DL algorithms due to the small sample sizes in the data sets and the low success rates in the tests performed on these datasets. As a result, the major contribution of this research was to statistically demonstrate that DL algorithms outperformed ML algorithms in data sets with large sample values via employing three separate software fault prediction datasets. The experimental outcomes of a model that includes a layer of recurrent neural networks (RNNs) were enclosed within this study. Alongside the aforementioned and generated data sets, the study also utilized the Eclipse and Apache Active MQ data sets in to test the effectiveness of the proposed deep learning method.

Value-based Software Engineering: A Systematic Mapping Study

Background: Integrating value-oriented perspectives into the principles and practices of software engineering is fundamental to ensure that software development activities address key stakeholders’ views and also balance short-and long-term goals. This is put forward in the discipline of value-based software engineering (VBSE) Aim: This study aims to provide an overview of VBSE with respect to the research efforts that have been put into VBSE. Method: We conducted a systematic mapping study to classify evidence on value definitions, studies’ quality, VBSE principles and practices, research topics, methods, types, contribution facets, and publication venues. Results: From 143 studies we found that the term “value” has not been clearly defined in many studies. VB Requirements Engineering and VB Planning and Control were the two principles mostly investigated, whereas VB Risk Management and VB People Management were the least researched. Most studies showed very good reporting and relevance quality, acceptable credibility, but poor in rigour. Main research topic was Software Requirements and case study research was the method used the most. The majority of studies contribute towards methods and processes, while very few studies have proposed metrics and tools. Conclusion: We highlighted the research gaps and implications for research and practice to support VBSE.

Human-centred cyber secure software engineering

Software runs our modern day lives: our shopping, our transport and our medical devices. Hence, no citizen can escape the consequences of poor software engineering. A closely-aligned concern, which also touches every aspect of our lives, is cyber security. Software has to be developed with cybersecurity threats in mind, in order to design resistance and resilience into the software, given that they are often rooted in malicious human behaviour. Both software engineering and cyber security disciplines need to acknowledge and accommodate humans, not expect perfect performances. This is a position paper, delineating the extent of the challenge posed by this reality, and suggesting ways for accommodating the influence of human nature on secure software engineering.Practical Relevance: Socio-technical systems are made up of people, processes and technology. All can fail or be suboptimal. Software itself, being designed, developed and used by humans, is likely to malfunction. This could be caused by human error, or by malice. This paper highlights this reality, taking a closer look at all of the possible sources of malfunctioning technology. By doing so, I hope to infuse the management of socio-technical systems with an understanding and acknowledgement of this reality.

Engineering Blockchain-based Software Systems: Foundations, Survey, and Future Directions

Many scientific and practical areas have shown increasing interest in reaping the benefits of blockchain technology to empower software systems. However, the unique characteristics and requirements associated with Blockchain-based Software (BBS) systems raise new challenges across the development lifecycle that entail an extensive improvement of conventional software engineering. This article presents a systematic literature review of the state-of-the-art in BBS engineering research from the perspective of the software engineering discipline. We characterize BBS engineering based on the key aspects of theoretical foundations, processes, models , and roles . Based on these aspects, we present a rich repertoire of development tasks, design principles, models, roles, challenges, and resolution techniques. The focus and depth of this survey not only give software engineering practitioners and researchers a consolidated body of knowledge about current BBS development but also underpin a starting point for further research in this field.

A Tool for Supporting the Teaching and Modeling of Software Ecosystems Using SSN Notation

Software Ecosystems (SECO) are a set of actors and components that work as a unit, which establish relationships based on common interest to provide solutions or services for the software industry. As a company or organization expands its relationships and begins to interact with external actors, a network is formed and SECO includes both the actors and the involved artifacts. However, SECO is not commonly taught in the Software Engineering disciplines. The activity of modeling a SECO can assist in a better visualization and understanding of relationships. However, there is no official modeling standard for SECO, and the notations are quite varied. In this scenario, SSN (Software Supply Network) notation emerged to try to fill this gap. An eminent problem in the literature is the lack of support for modeling using SSN notation, the lack of available models and maintenance of models in general. In this context, this work aims to present a tool to support the teaching and modeling of SECO using the SSN notation, and thus alleviate the problem of the lack of specific modeling tools for SECO. In this work, the tool was applied in Software Engineering classes, where students filled out a questionnaire and a qualitative analysis was performed on the results. In general, the tool pleased both in terms of usability and understanding of SECO. Qualitative analysis revealed that the tool collaborates for SECO modeling, but it can improve usability and design, and there is a need for documentation and support for SECO teaching and modeling.

A systematic literature review of requirements engineering education

Requirements engineering (RE) has established itself as a core software engineering discipline. It is well acknowledged that good RE leads to higher quality software and considerably reduces the risk of failure or budget-overspending of software development projects. It is of vital importance to train future software engineers in RE and educate future requirements engineers to adequately manage requirements in various projects. To this date, there exists no central concept of what RE education shall comprise. To lay a foundation, we report on a systematic literature review of the field and provide a systematic map describing the current state of RE education. Doing so allows us to describe how the educational landscape has changed over the last decade. Results show that only a few established author collaborations exist and that RE education research is predominantly published in venues other than the top RE research venues (i.e., in venues other than the RE conference and journal). Key trends in RE instruction of the past decade include involvement of real or realistic stakeholders, teaching predominantly elicitation as an RE activity, and increasing student factors such as motivation or communication skills. Finally, we discuss open opportunities in RE education, such as training for security requirements and supply chain risk management, as well as developing a pedagogical foundation grounded in evidence of effective instructional approaches.

Cognition in Software Engineering: A Taxonomy and Survey of a Half-Century of Research

Cognition plays a fundamental role in most software engineering activities. This article provides a taxonomy of cognitive concepts and a survey of the literature since the beginning of the Software Engineering discipline. The taxonomy comprises the top-level concepts of perception, attention, memory, cognitive load, reasoning, cognitive biases, knowledge, social cognition, cognitive control, and errors, and procedures to assess them both qualitatively and quantitatively. The taxonomy provides a useful tool to filter existing studies, classify new studies, and support researchers in getting familiar with a (sub) area. In the literature survey, we systematically collected and analysed 311 scientific papers spanning five decades and classified them using the cognitive concepts from the taxonomy. Our analysis shows that the most developed areas of research correspond to the four life-cycle stages, software requirements, design, construction, and maintenance. Most research is quantitative and focuses on knowledge, cognitive load, memory, and reasoning. Overall, the state of the art appears fragmented when viewed from the perspective of cognition. There is a lack of use of cognitive concepts that would represent a coherent picture of the cognitive processes active in specific tasks. Accordingly, we discuss the research gap in each cognitive concept and provide recommendations for future research.

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.

A Framework for Aspectual Requirements Validation: an Experimental Study

Requirements engineering is a discipline of software engineering that is concerned with the identification and handling of user and system requirements. Aspect-Oriented Requirements Engineering (AORE) extends the existing requirements engineering approaches to cope with the issue of tangling and scattering resulted from crosscutting concerns. Crosscutting concerns are considered as potential aspects and can lead to the phenomena “tyranny of the dominant decomposition”. Requirements-level aspects are responsible for producing scattered and tangled descriptions of requirements in the requirements document. Validation of requirements artefacts is an essential task in software development. This task ensures that requirements are correct and valid in terms of completeness and consistency, hence, reducing the development cost, maintenance and establish an approximately correct estimate of effort and completion time of the project. In this paper, we present a validation framework to validate the aspectual requirements and the crosscutting relationship of concerns that are resulted from the requirements engineering phase. The proposed framework comprises a high-level and low-level validation to implement on software requirements specification (SRS). The high-level validation validates the concerns with stakeholders, whereas the low-level validation validates the aspectual requirement by requirements engineers and analysts using a checklist. The approach has been evaluated using an experimental study on two AORE approaches. The approaches are viewpoint-based called AORE with ArCaDe and lexical analysis based on Theme/Doc approach. The results obtained from the study demonstrate that the proposed framework is an effective validation model for AORE artefacts.

Software Project Management Education: A Systematic Review

Software project management (SPM) is a significant field, related to the discipline of software engineering, which has attracted a huge number of researchers and practitioners in recent years. The role of software project management education (SPME) is essential to instill appropriate competencies in SPM students so that they could be able to deliver effectively in the software industry as SPM professionals. As the demand of SPM professionals is continuously increasing, the responsibilities of academia have also been increased to ensure and provide the solid basis and quality education to SPM. In this context, a number of methods and tools have been deliberated to examine SPME from various dimensions. The usefulness of these methods and tools need to be synthesized and evaluated to investigate the areas that could be used to improve the various aspects of SPME. The main objective of this research is to evaluate the techniques that have been applied to teach SPME and identify the future directions that could lead to make improvements in SPME. This article presents a review of eighty-nine research papers of SPME that have been classified and synthesized according to different aspects of SPME. These aspects include type and approach of conducted research, empirical type, SPM knowledge areas, and curricula. The principal findings emerged after analyzing the results of reviewing the SPME research have been discussed in detail. Lastly, a list of advice to SPM instructors, based on the prominent and effective practices of SPME, has also been presented in this study.

Understanding peer review of software engineering papers

ContextPeer review is a key activity intended to preserve the quality and integrity of scientific publications. However, in practice it is far from perfect.ObjectiveWe aim at understanding how reviewers, including those who have won awards for reviewing, perform their reviews of software engineering papers to identify both what makes a good reviewing approach and what makes a good paper.MethodWe first conducted a series of interviews with recognised reviewers in the software engineering field. Then, we used the results of those interviews to develop a questionnaire used in an online survey and sent out to reviewers from well-respected venues covering a number of software engineering disciplines, some of whom had won awards for their reviewing efforts.ResultsWe analyzed the responses from the interviews and from 175 reviewers who completed the online survey (including both reviewers who had won awards and those who had not). We report on several descriptive results, including: Nearly half of award-winners (45%) are reviewing 20+ conference papers a year, while 28% of non-award winners conduct that many. The majority of reviewers (88%) are taking more than two hours on journal reviews. We also report on qualitative results. Our findings suggest that the most important criteria of a good review is that it should be factual and helpful, which ranked above others such as being detailed or kind. The most important features of papers that result in positive reviews are a clear and supported validation, an interesting problem, and novelty. Conversely, negative reviews tend to result from papers that have a mismatch between the method and the claims and from papers with overly grandiose claims. Further insights include, if not limited to, that reviewers view data availability and its consistency as being important or that authors need to make their contribution of the work very clear in their paper.ConclusionsBased on the insights we gained through our study, we conclude our work by compiling a proto-guideline for reviewing. One hope we associate with our work is to contribute to the ongoing debate and contemporary effort to further improve our peer review models in the future.

On the Definition of Quantum Programming Modules

There are no doubts that quantum programming and, in general, quantum computing, is one of the most promising areas within computer science and one of the areas where most expectations are being placed in recent years. Although the days when reliable and affordable quantum computers will be available is still a long way off, the explosion of programming languages for quantum programming has grown exponentially in recent years. The software engineering community has been quick to react to the need to adopt and adapt well-known tools and methods for software development, and for the design of new ones tailored to this new programming paradigm. However, many key aspects for its success depend on the establishment of an appropriate conceptual framework for the conception and design of quantum programs. This article discusses the concept of module, key in the software engineering discipline, and establishes initial criteria for determining the cohesion and coupling levels of a module in the field of quantum programming as a first step towards a sound quantum software engineering. As detailed in the article, the conceptual differences between classical and quantum computing are so pronounced that the translation of classical concepts to the new programming approach is not straightforward.

Reuse Alternatives based on the Sources of Software Assets

Abstract— Since the idea of software reuse appeared in 1968, software reuse has become a software engineering discipline. Software reuse is one of the main techniques used to enhance the productivity of software development, which it helps reducing the time, effort, and cost of developing software systems, and enhances the quality of software products. However, software reuse requires understanding, modifying, adapting and testing processes in order to be performed correctly and efficiently. This study aims to analyze and discuss the process of software reuse, identify its elements, sources and usages. The alternatives of acquiring and using software assets either normal or reusable assets are discussed. As a result of this study, four main methods are proposed in order to use the concept of reuse in the software development process. These methods are proposed based on the source of software assets regardless the types of software assets and their usages.