Software Development Practices Research Articles

A new taxonomy of global software development best practices using prioritization based on a fuzzy system

AbstractEffective management of development projects is crucial to delivering high‐quality software within time and budget constraints. However, organizing geographically distributed software development activities presents unique challenges, including difficulties in face‐to‐face interaction and coordination. To assist the global software development community in updating and developing new project management techniques, identifying and prioritizing best practices is essential. This study aims to develop a taxonomy based on the prioritization of management practices for software development, drawing from empirical data. Fifty‐five best practices associated with the Project Management Body of Knowledge (PMBOK) fields were identified from the existing literature. The study also empirically examines the acceptability and relevance of these practices within the industry. An analytic hierarchy process within a fuzzy system is employed to prioritize these practices based on their importance in managing global software development.

TCCCD: Triplet-Based Cross-Language Code Clone Detection

Code cloning is a common practice in software development, where developers reuse existing code to accelerate programming speed and enhance work efficiency. Existing clone-detection methods mainly focus on code clones within a single programming language. To address the challenge of code clone instances in cross-platform development, we propose a novel method called TCCCD, which stands for Triplet-Based Cross-Language Code Clone Detection. Our approach is based on machine learning and can accurately detect code clone instances between different programming languages. We used the pre-trained model UniXcoder to map programs written in different languages into the same vector space and learn their code representations. Then, we fine-tuned TCCCD using triplet learning to improve its effectiveness in cross-language clone detection. To assess the effectiveness of our proposed approach, we conducted thorough comparative experiments using the dataset provided by the paper titled CLCDSA (Cross Language Code Clone Detection using Syntactical Features and API Documentation). The experimental results demonstrated a significant improvement of our approach over the state-of-the-art baselines, with precision, recall, and F1-measure scores of 0.96, 0.91, and 0.93, respectively. In summary, we propose a novel cross-language code-clone-detection method called TCCCD. TCCCD leverages the pre-trained model UniXcode for source code representation and fine-tunes the model using triplet learning. In the experimental results, TCCCD outperformed the state-of-the-art baselines in terms of the precision, recall, and F1-measure.

Hybrid software testing model to improve software quality assurance

Software testing is a very critical factor in determining the quality, robustness and reliability of applications. Testing methods have advanced to accommodate the various software development practices that are being churned out at frequent rates and representing complex systems. One such method is the hybrid software testing model, which combines the strengths of different testing techniques to achieve comprehensive testing coverage. This study provides an in-depth analysis of the hybrid software testing model, exploring its definition, benefits, challenges, and best practices. Furthermore, it discusses various testing techniques commonly used in hybrid testing and presents case studies showcasing the successful implementation of the hybrid model in real-world scenarios.

Modelling Robot Architectures with AADL

Robots are complex systems composed of many interacting subsystems, each coordinating a multitude of hardware and software components. In the last twenty years, robotic frameworks helped accelerate the development process by providing a reference structure and publicly available software components. However, current practices are not sustainable for modern robotic systems. In this work, we present a modelling approach based on the Architecture Analysis and Design Language (AADL) to define robotic systems and enhance software development practices for robotics. Additionally, we exploit the model to perform automatic code generation, which reduces development time and guarantees a more reliable and robust implementation.

A Comprehensive Analysis on the Student Behaviour in Open.uom.lk: A Large-scale Asynchronous Open Online Platform

The open learning platform (open.uom.lk) of the University of Moratuwa, Sri Lanka has attracted over 180,000 registered students in just over one year of its launch. This platform offers the Trainee Full Stack Developer (TFSD) programme, enabling the participants to enter the Information Technology (IT) industry to address the much needed human resources for the growing IT industry of the country. The programme consists of six courses related to IT covering Python Programming, Web Development and Professional Practice in Software Development. The platform operates with minimal restrictions for registrants and has students from all parts of the country with some foreign students with an equitable gender distribution. The steady growth of the registration numbers shows a high level of enthusiasm from the community to explore the potential opportunities in the IT industry. While the platform is being used actively by thousands of participants and new users are registered on a daily basis, it is also observed that some of the participants have shown slow progress at different stages. This study presents analyses performed at different stages of the programme to study the student behaviour and identify the possible causes for the participants not being able to achieve steady progress. The findings of the study indicate that the participants generally find it difficult to get through the programming exercises and assignments. Correlating learning patterns of the students help understanding the overall learning strategies which can be adopted by developers of similar asynchronous learning programmes. Furthermore, the study goes on to suggest and discuss possible solutions to clear the bottlenecks identified at different stages of the programme. The subsequent analyses allow the prediction of completions by participants leading to a machine learning based model for predictive analytics.

Understanding the influencing factors and mechanism of social compensation for Chinese older adults using social media in the context of smart home: a qualitative analysis.

As a new generation of necessary terminals for future homes, smart homes have become one of the essential mediums for smart aging at home. This paper aims to explore how older adults who age at home can overcome the digital divide of the new medium and achieve social participation in the home context to realize active aging. Based on the theory of social compensation, we select the smart-home smart screen, a representative new medium product in China, and carry out open coding, spindle coding, selective coding, and theoretical construction of the original interview data through the grounded theory research method. The results show that the main factors affecting the social compensation of older adults to smart home social media include user interface quality, interaction quality, content quality, and service quality, and these four factors are used as external variables to compensate older adults socially, thereby stimulating the emotional experience and perception changes at the cognitive level of older adults and then affecting the adoption and acceptance of smart home social media by older adults. This study refines the factors influencing the older adults' use of smart home social media from the perspective of social compensation. It explains the mechanism of acceptable behavior of older adults, bridging the gap in previous literature on the influencing factors and behavioral mechanisms of older adults of smart home social media. This paper provides a theoretical basis and guidance for the subsequent academic research and software development practice of social media under new technological devices to further help older adults in China achieve active and healthy aging.

Nudge goes to Silicon Valley: designing for the disengaged and the irrational

ABSTRACT An array of software apps, from fitness to finance, enrolls behavioral economics, and economists, in their product designs, value propositions, or else sales pitches, to make products more engaging and to afford users new capabilities in their daily lives. Drawing on 30 interviews with product strategists, designers, and user researchers who work on these self-styled ‘behavior change apps,’ this paper empirically studies the behavioral economic proposition and its operationalization in routine practices of software development and design. Setting aside the behavioral addiction and manipulation frame that critical work on app design typically summons, I approach behavioral economics applications as market work and tease out the different, co-existing logics of attachment between products and their users, that emerge from how market actors decide what product to build, which features to have and how to design the user experience. In doing so, I show that strictly focusing on the frequency of repeated interaction is also empirically inadequate. The product is rather strategized, developed, and designed to become something that the user ‘cannot do without,’ not because it is addictive, but because it is made indispensable to the distributed action universe of the behavioral problem that it addresses.

Hypermedia-based software architecture enables Test-Driven Development.

Using agile software development practices, develop and evaluate an architecture and implementation for reliable and user-friendly self-service management of bioinformatic data stored in the cloud. Comprehensive Oncology Research Environment (CORE) Browser is a new open-source web application for cancer researchers to manage sequencing data organized in a flexible format in Amazon Simple Storage Service (S3) buckets. It has a microservices- and hypermedia-based architecture, which we integrated with Test-Driven Development (TDD), the iterative writing of computable specifications for how software should work prior to development. Relying on repeating patterns found in hypermedia-based architectures, we hypothesized that hypermedia would permit developing test "templates" that can be parameterized and executed for each microservice, maximizing code coverage while minimizing effort. After one-and-a-half years of development, the CORE Browser backend had 121 test templates and 875 custom tests that were parameterized and executed 3031 times, providing 78% code coverage. Architecting to permit test reuse through a hypermedia approach was a key success factor for our testing efforts. CORE Browser's application of hypermedia and TDD illustrates one way to integrate software engineering methods into data-intensive networked applications. Separating bioinformatic data management from analysis distinguishes this platform from others in bioinformatics and may provide stable data management while permitting analysis methods to advance more rapidly. Software engineering practices are underutilized in informatics. Similar informatics projects will more likely succeed through application of good architecture and automated testing. Our approach is broadly applicable to data management tools involving cloud data storage.

Packaging cost-effectiveness models in R: A tutorial.

Background: The use of programming languages such as R in health economics and decision science is increasing, and brings numerous benefits including increasing model development efficiency, improving transparency, and reducing human error. However, there is limited guidance on how to best develop models using R. So far, no clear consensus has emerged. Methods: We present the advantages of creating health economic models as R packages - structured collections of functions, data sets, tests, and documentation. Assuming an intermediate understanding of R, we provide a tutorial to demonstrate how to construct a basic R package for health economic evaluation. All source code used in or referenced by this paper is available under an open-source licence. Case Study: We use the Sick Sicker Model as a case study applying the steps from the tutorial to standardise model development, documentation and aid review. This can improve the distribution of code, thereby streamlining model development, and improving methods in health economic evaluation. Conclusion: R packages offer a valuable framework for enhancing the quality and transparency of health economic evaluation models. Embracing better, more standardised software development practices, while fostering a collaborative culture, has the potential to significantly improve the quality of health economic models, and, ultimately, support better decision making in healthcare.

The Business Impact of Inner Source and How to Quantify It

Inner source software development is the practice of using open source practices for firm-internal software development. Practitioner reports have shown that inner source can increase flexibility and reduce costs. Despite the potential benefits of inner source, there has been little research on its impact on businesses and their processes. To address this gap, we conducted a systematic literature review that identified which business processes are affected by inner source development, particularly within the accounting and management domain. Our review revealed the need for new dedicated community building processes within companies. In addition, we examined computational tools and techniques that can be used to measure inner source development. We found that existing tools and techniques are insufficiently suitable to manage inner source processes. Based on this, we propose research topics for future work on quantifying inner source.

Redesigning Graphical User Interface of Open-Source Geospatial Software in a Community-Driven Way: A Case Study of GRASS GIS

Learning to use geographic information system (GIS) software effectively may be intimidating due to the extensive range of features it offers. The GRASS GIS software, in particular, presents additional challenges for first-time users in terms of its complex startup procedure and unique terminology associated with its data structure. On the other hand, a substantial part of the GRASS user community including us as developers recognized and embraced the advantages of the current approach. Given the controversial nature of the whole issue, we decided to actively involve regular users by conducting several formal surveys and by performing usability testing. Throughout this process, we discovered that resolving specific software issues through pure user-centered design is not always feasible, particularly in the context of open-source scientific software where the boundary between users and developers is very fuzzy. To address this challenge, we adopted the user-centered methodology tailored to the requirements of open-source scientific software development, which we refer to as community-driven design. This paper describes the community-driven redesigning process on the GRASS GIS case study and sets a foundation for applying community-driven design in other open-source scientific projects by providing insights into effective software development practices driven by the needs and input of the project’s community.

Software Engineering: New Methodologies, Tools, and Best Practices in Software Development

Software engineering is a dynamic field that is always evolving to meet the demands of difficult software development projects. This journal article investigates contemporary software engineering methodologies, tools, and best practices in order to enhance the efficiency, quality, and dependability of software development processes. We discuss the most recent advancements in quality assurance, DevOps, agile software development, and automated testing. We also look at the role that cooperation, communication, and project management have in efficient software engineering methods. By highlighting these advances, this article aims to promote the delivery of high-quality software products and improve software development processes.

Resist the Hype!: Practical Recommendations to Cope With Résumé-Driven Development

Technology trends play an important role in the hiring process for software and IT professionals. In a recent study of 591 software professionals in both hiring (130) and technical (558) roles, we found empirical support for a tendency to overemphasize technology trends in résumés and the application process. 60% of the hiring professionals agreed that such trends would influence their job advertisements. Among the software professionals, 82% believed that using trending technologies in their daily work would make them more attractive for potential future employers. This phenomenon has previously been reported anecdotally and somewhat humorously under the label Résumé-Driven Development (RDD). Our article seeks to initiate a more serious debate about the consequences of RDD on software development practice. We explain how the phenomenon may constitute a harmful self-sustaining dynamic, and provide practical recommendations for both the hiring and applicant perspectives to change the current situation for the better.

Artificial Intelligence-Based Tools in Software Development Processes: Application of ChatGPT

Software development processes are continuously evolving and rapidly transforming alongside the rapid changes in technology. Recently, innovations in the field of Artificial Intelligence (AI) have led to significant changes in software development practices. AI tools can greatly enhance traditional software development processes by offering developers the ability to create projects more intelligently, swiftly, and effectively. These tools can be employed in various tasks, such as code generation, test automation, error analysis, and performance improvements. Particularly, ChatGPT, an AI-based language model that has had a profound impact on almost every domain, can assist software developers in writing code faster and in a more natural language manner. In this research article, essential information about the usage of ChatGPT in the software development process is presented. To evaluate some capabilities of ChatGPT in the software development context, applications were performed on a software project. For this purpose, a software development process was constructed based on the responses provided by ChatGPT. Various questions related to software development processes were formulated, and the responses generated by GPT were evaluated. The obtained results indicated that ChatGPT exhibited excellent performance in the software development process. Based on these findings, it was observed that AI-based models like ChatGPT could be effectively utilized as assisting tools in software development processes, accelerating traditional workflows. Furthermore, AI-based tools can automate testing processes, enhancing software quality while saving time and effort.

Pragmatic evidence of cross-language link detection: A systematic literature review

There is a rising trend for heterogeneous software applications involving multilingual source code. The key focus of reverse engineers is to unravel the cross-language links (XLLs) and their dependencies. This study aims to perform a systematic literature review (SLR) to compile different approaches, tools, techniques, and shortcomings of such techniques and understand the XLLs and their dependencies while performing reverse engineering on state-of-the-art software applications. This SLR selects 76 primary studies and uses them to create a ’go-to’ literature database, where professionals from software engineering could find all the content pertinent to the analysis and XLL detection for major multilingual applications like Java enterprise applications, Android applications, etc. It has been observed that traditional source code analysis mechanisms to reverse engineer contemporary software applications face scores of problems and limitations that need to be addressed. To assist the community in the above-mentioned goal, a general schema with definitions of XLLs and associated concepts is furnished. This study provides an SLR on XLLs, comprehensive taxonomy called cross-language analysis, which incorporates all the methods for XLL detection in multilingual source code. By pursuing future directions suggested in the end, researchers and practitioners can advance the field of multilingual applications; such as Enterprise resource planning (ERP) solutions, and cross-language software corpora, leading to improved software development practices and better understanding of language interactions in multilingual environments. The research data provided in the survey presents a comprehensive analysis of the complexities involved in working with diverse programming languages and frameworks, offering valuable insights for language technology researchers, software developers, academics, and decision-makers. This integration will enable them to identify and manage dependencies across diverse languages, leading to more efficient and reliable multilingual software systems.

The Convergence of AI/ML and DevSecOps: Revolutionizing Software Development

The convergence of Artificial Intelligence (AI) and Machine Learning (ML) with DevSecOps represents a groundbreaking paradigm shift in software development practices. This paper explores the transformative impact of integrating AI/ML technologies into the DevSecOps framework, revolutionizing the way software is designed, developed, and secured. Through a comprehensive analysis of current trends, challenges, and opportunities, the paper elucidates the key strategies and best practices for leveraging AI/ML in DevSecOps. Topics addressed include automated threat detection, predictive analytics for vulnerability management, intelligent automation, and the ethical considerations surrounding AI/ML deployment in security-sensitive environments. By embracing this convergence, organizations can enhance their security posture, accelerate software delivery, and foster a culture of continuous improvement. Case studies and real-world examples are presented to illustrate the practical applications and benefits of AI/ML in transforming DevSecOps practices.

A Narrative Review of Factors Affecting the Implementation of Privacy and Security Practices in Software Development

Privacy and security are complex topics, raising a variety of considerations and requirements that can be challenging to implement in software development. Determining the security and privacy related factors that have an influence on software systems development and deployment project outcomes has been the focus of extensive and ongoing research over the past two decades. To understand and categorize the factors that have an impact on developers’ adoption and implementation of privacy and security considerations and practices in software development, we carried out a narrative review of the literature. The resulting mapping of factors provides a foundation for future interventions targeting organizational and individual behavior change, to increase the adoption of privacy and security practices in software development.

Rethinking Your Application Security Posture from Code to Cloud

This paper explores the importance of reevaluating the application security posture in the context of modern software development practices and the shift towards cloud computing. It highlights the challenges posed by the evolving threat landscape and emphasizes the need for a comprehensive and proactive security strategy. The paper also discusses various techniques and best practices for securing applications from the code level to the cloud environment, encompassing secure coding practices, and the effective utilization of cloud security services. By adopting a holistic approach to application security, organizations can mitigate risks and protect their applications and data throughout the software development lifecycle. Keywords: Application Security, Software Development, Cloud Computing, Secure Coding, Vulnerability Assessment, Penetration Testing, Cloud Security Services Proceedings Citation Format Afolabi, O. (2023): Rethinking Your Application Security Posture from Code to Cloud. Proceedings of the Cyber Secure Nigeria Conference. Nigerian Army Resource Centre (NARC) Abuja, Nigeria. 11-12th July, 2023. Pp 35-40. https://cybersecurenigeria.org/conference-proceedings/volume-2-2023/ dx.doi.org/10.22624/AIMS/CSEAN-SMART2023P5

Best Practices to Implement and Pitfalls to Avoid in Cloud Application Security

This paper explores the importance of reevaluating the application security posture in the context of modern software development practices and the shift towards cloud computing. It highlights the challenges posed by the evolving threat landscape and emphasizes the need for a comprehensive and proactive security strategy. The paper also discusses various techniques and best practices for securing applications from the code level to the cloud environment, encompassing secure coding practices, and the effective utilization of cloud security services. By adopting a holistic approach to application security, organizations can mitigate risks and protect their applications and data throughout the software development lifecycle. Keywords: Application Security, Software Development, Cloud Computing, Secure Coding, Vulnerability Assessment, Penetration Testing, Cloud Security Services Proceedings Citation Format Oyitso, E.J. & Ordia, E.D. (2023): Best Practices to Implement and Pitfalls to Avoid in Cloud Application Security. Proceedings of the Cyber Secure Nigeria Conference. Nigerian Army Resource Centre (NARC) Abuja, Nigeria. 11-12th July, 2023. Pp 41-48. https://cybersecurenigeria.org/conference-proceedings/volume-2-2023/ dx.doi.org/10.22624/AIMS/CSEAN-SMART2023P6

Identifying components existing in Agile software development for achieving “light but sufficient” documentation

The Agile nature allows changes within the development procedure which can sometimes be non-predictable and affect the cost and time of the software. Face-to-face communication appears to be a faster process in Agile Software Development (ASD) in practice, but issues such as understandability and communicativeness cause ambiguity between the customer and the developer. Among the existing works, achieving light but sufficient documentation in ASD remains a challenge. Most previous studies have simply highlighted the issues associated with less documentation, its limitations, and challenges, but no proper solution has yet been proposed. As an initial step in our theoretical study, we conducted a systematic literature review (SLR) to identify the related components and subcomponents that are applicable in supporting Agile documentation. As such, the fundamental concepts related to software documentation have been studied in order to align with documentation in ASD. The identification of these components can be useful in achieving the concept of “light but sufficient” documentation in Agile, which will aid in achieving customer satisfaction.