Software Organizations Research Articles

Unravelling DevOps Agile Methodologies: A Comprehensive Review of Recent Research

Abstract: This study report offers a thorough analysis of current studies on DevOps Agile techniques. The study summarizes and dissects the major discoveries made in peer-reviewed literature, conference proceedings, and other academic publications. The article examines the most recent DevOps Agile practice trends and advances, as well as how they affect software development, testing, deployment, and operations. The analysis emphasizes the advantages of applying DevOps Agile approaches, including enhanced collaboration, faster time to market, and higher-quality software products. The paper also examines the challenges and potential limitations of DevOps Agile adoption, such as cultural resistance, lack of skills, and integration issues. Finally, the study concludes with recommendations for practical implications for software development teams and organizations seeking to implement DevOps Agile methodologies. The review provides valuable insights and guidance for researchers, practitioners, and decision-makers in the field of software engineering and information technology.

Software Industry Perception of Technical Debt and Its Management

Technical debt (TD) expresses the lack of internal quality directly affecting software evolution. Therefore, it has gained the attention of software researchers and practitioners recently. Software researchers have performed empirical studies to observe the perspective of TD in different software cultures and organizations. However, it is important to replicate such studies in more places and with more practitioners to strengthen the perception of TD. In this paper, we present the results of a set of new research questions from an evolved survey design of a survey replication in the Uruguayan software industry to characterize how the software industry professionals understand, perceive, and adopt TD management (TDM) activities. The results allow us to observe that different participant contexts (startups, government, job roles) show different levels of awareness and perception of TD. Details in the form of the adoption of each TDM activity were presented. We could observe some difficulties in conducting some TDM activities that the practitioners consider very important, especially in TDM and monitoring. Differences in specific organizational contexts like startups and government could indicate the need for research efforts in other software engineering communities that meet their specific TD challenges and needs.

Second-Class Citizens or Free Agents? Social Construction of Equity Perceptions of Contractors in Global Offshoring Arrangements

This study examines the ways in which perceptions of equity are socially constructed among contractors involved in global offshoring arrangements. A comparative case study of two global software organizations involved in offshore outsourcing reveals that global contractors across sites constructed different equity perceptions of similar foreign assignments due to a number of contextual factors. These contextual differences combined to produce social comparison processes that led to the construction of different equity perceptions. Drawing on a perceptual model of equity theory, we find that global contractors from one case felt stigmatized and treated inequitably as “second-class citizens”, while those from the other case felt empowered as “free agents.” Our findings contribute a context-sensitive explanation for the construction of different equity perceptions in global offshoring arrangements, with implications for global work design more broadly.

Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

AbstractIncreasingly, software organizations are implementing DevOps culture to benefit from it in terms of continuous testing, delivery, improvement, and so forth. Implementing DevOps is difficult due to a lack of understanding about the practices and their effective application for its effective implementation. This paper aims to explore different DevOps practices that can be implemented in software organizations. The study involves conducting a systematic literature review (SLR) to identify DevOps implementation practices, followed by the utilization of the fuzzy best–worst method (FBWM) to establish a taxonomy or classification of software practices. We have used an SLR to investigate the practices, and subsequently, the survey method was followed to validate the identified practices. Moreover, the best–worst method (BWM) was considered to evaluate the significance and develop the taxonomy of the practices. The results of this study extracted 19 practices that have been identified in the SLR process. The identified factors are further classified into six core DevOps lifecycle phases. The results of the BWM approach are shown. The outcomes of the study conclude that the proposed taxonomy of the practices could help DevOps practitioners and researchers effectively implement them in software development organizations.

Comparative Analysis of Performance Management Systems in the Softare Industry: A Study across Public and Private Sectors

While steering organizational objectives, the performance management system involves overseeing employees, commencing with the allocation of duties and responsibilities. Nowadays, employees strive to swiftly advance their careers, prompting organizations to offer developmental opportunities to attract and retain talent. In the software industry, organizational success hinges on the efficient and effective contributions of employees, a balance upheld by an adept performance management system. Serving as a crucial tool, this system ensures organizational triumph by cultivating employees to meet both individual and collective goals. The current study seeks to discern variations in the performance management systems of public and private sector software organizations.

A machine learning approach to predict DevOps readiness and adaptation in a heterogeneous IT environment

Software and information systems have become a core competency for every business in this connected world. Any enhancement in software delivery and operations will tremendously impact businesses and society. Sustainable software development is one of the key focus areas for software organizations. The application of intelligent automation leveraging artificial intelligence and cloud computing to deliver continuous value from software is in its nascent stage across the industry and is evolving rapidly. The advent of agile methodologies with DevOps has increased software quality and accelerated its delivery. Numerous software organizations have adopted DevOps to develop and operate their software systems and improve efficiency. Software organizations try to implement DevOps activities by taking advantage of various expert services. The adoption of DevOps by software organizations is beset with multiple challenges. These issues can be overcome by understanding and structurally addressing the pain points. This paper presents the preliminary analysis of the interviews with the relevant stakeholders. Ground truths were established and applied to evaluate various machine learning algorithms to compare their accuracy and test our hypothesis. This study aims to help researchers and practitioners understand the adoption of DevOps and the contexts in which the DevOps practices are viable. The experimental results will show that machine learning can predict an organization's readiness to adopt DevOps.

Risk Mitigation and Monitoring Challenges in Software Organizations: A Morphological Analysis

Context: The present body of research on risk mitigation focuses mostly on sparse and dispersed research using various approaches during project development.
 Objectives: This paper's goals are to conceptualize and construct a morphological analysis (MA) framework, examine the literature that has already been published on these risks and how to mitigate them in software development, and identify research gaps that suggest areas for further study.
 Methods: Based on a survey of 102 works, we provide an MA framework. The MA framework, which is composed of five dimensions and 17 variants, identifies 33 distinct research gaps as the maximum number of potential areas for future study. The implications for future research are covered in the paper's conclusion. Risk reduction during the project development process is extremely beneficial for project managers at an organization in delivering high-quality goods on time and within budget.
 Results: Based on a review of the literature, it was discovered that the development of software projects used a very low percentage of official risk mitigation and elimination methods. Research also revealed the significance of people-related risks in the risk mitigation process for the benefit of the organization. Some key research demonstrated experimentation, case studies, and empirical approaches for evaluation. Future work may include examining project managers' perceptions and knowledge of risk management. Managers of software development teams require greater risk-mitigation strategies.
 Conclusion: Scholars and researchers need to put more effort into developing quantitative and intelligent risk models. It is crucial to identify major risks so that they won't compromise the project's future success. In our future work, we can employ more models that are helpful for combining quantitative and intelligent risk models using various AI strategies to reduce hazards.

Software Requirement Risk Prediction Using Enhanced Fuzzy Induction Models

The development of most modern software systems is accompanied by a significant level of uncertainty, which can be attributed to the unanticipated activities that may occur throughout the software development process. As these modern software systems become more complex and drawn out, escalating software project failure rates have become a critical concern. These unforeseeable uncertainties are known as software risks, and they emerge from many risk factors inherent to the numerous activities comprising the software development lifecycle (SDLC). Consequently, these software risks have resulted in massive revenue losses for software organizations. Hence, it is imperative to address these software risks, to curb future software system failures. The subjective risk assessment (SRM) method is regarded as a viable solution to software risk problems. However, it is inherently reliant on humans and, therefore, in certain situations, imprecise, due to its dependence on an expert’s knowledge and experience. In addition, the SRM does not allow repeatability, as expertise is not easily exchanged across the different units working on a software project. Developing intelligent modelling methods that may offer more unbiased, reproducible, and explainable decision-making assistance in risk management is crucial. Hence, this research proposes enhanced fuzzy induction models for software requirement risk prediction. Specifically, the fuzzy unordered rule induction algorithm (FURIA), and its enhanced variants based on nested subset selection dichotomies, are developed for software requirement risk prediction. The suggested fuzzy induction models are based on the use of effective rule-stretching methods for the prediction process. Additionally, the proposed FURIA method is enhanced through the introduction of nested subset selection dichotomy concepts into its prediction process. The prediction performances of the proposed models are evaluated using a benchmark dataset, and are then compared with existing machine learning (ML)-based and rule-based software risk prediction models. From the experimental results, it was observed that the FURIA performed comparably, in most cases, to the rule-based and ML-based models. However, the FURIA nested dichotomy variants were superior in performance to the conventional FURIA method, and rule-based and ML-based methods, with the least accuracy, area under the curve (AUC), and Mathew’s correlation coefficient (MCC), with values of approximately 98%.

Development of a Maturity Model for Software Quality Assurance Practices

The advancements in the technology landscape and software development in recent years mandate paying attention to Software Quality Assurance (SQA) because it is becoming significantly important and complex. SQA is a set of activities within the software development lifecycle that aims at reducing development and testing costs, improving the quality of the software systems, and increasing customer satisfaction. Thus, the objective of this paper is to build a SQA maturity model, particularly in the telecommunication industry. To achieve this, this research identified perspectives and factors based on a comprehensive literature review and experts’ inputs using Hierarchical Decision Modeling (HDM) as the methodology. The proposed model consists of five perspectives, which are requirements validation, testing, software change management control, technology, and organization and culture with every perspective containing relevant factors. The factors and perspectives are validated and quantified using SQA inputs from subject matter experts. The findings of this study suggest that requirements validation is the most important perspective. Two case studies were conducted to identify the maturity score for each case, demonstrate the practicality of the research model, identify areas of deficiencies, and propose corrective actions. This paper provides an in-depth look at software quality factors and their relative importance, targeting to help SQA practitioners understand and assess their SQA practices.

نموذج مقترح لإدارة المخاطر في الشركات ذات المشروعات المتعددة

Recently, the importance of risk management has increased in the field of project management, especially software projects. The importance of risk management is because it has direct effects on the success of the project. Therefore, software organizations face a major challenge in achieving effective and efficient risk management. Therefore, measuring risks in software development is a key activity to be undertaken in risk management. Risk measurement is also one of the important topics that need more effort, especially in a work environment with multiple software projects. A multi-project environment involves multiple projects sharing the same available resources. This research aims to conduct a literature review to discover patterns or trends in software development to measure project risks and to reveal aspects of the measurement process, risk indicators, and various metrics for software projects. This research also aims to present a proposed framework for assessing risks in a multi-project work environment with shared resources for different levels in organizations with different capabilities.

A literature review for measuring maintainability of code clone

Software organizations face constant pressure due to stakeholder requirements and the increasing complexity of software systems. This complexity, combined with defects in code quality and failures, can pose risks to software systems. To ensure code is understood before maintenance, developers must spend over 60% of their time modifying and improving code quality, which is costly. This study examines the impact of code refactoring activities on software maintainability and quality by reviewing relevant research and explaining key terms. The research finds that refactoring activities can enhance specific quality characteristics, including maintainability, understandability, and testability. The study also identifies important factors that should be considered when developing refactoring tools. Refactoring enables code improvement without altering program behavior and can be applied multiple times to source code.

Machine learning based predictive modeling to effectively implement DevOps practices in software organizations

Machine learning based predictive modeling to effectively implement DevOps practices in software organizations

Continuous Software Engineering: Introducing an Industry Readiness Model

Software is becoming essential for most products, manufacturing processes, and back-office functions. The speed of delivering new features and refining the product is critical to remaining competitive. Software organizations may adopt continuous engineering practices to become more efficient. However, retrofitting an organization with a pipeline is challenging. Importantly, the most significant challenges and opportunities, are related to, but stem from outside the engineering realm and require rethinking customer relationships and business models. This paper presents a hierarchy of continuous engineering benefits and challenges. It is aimed to guide the adoption of continuous practices in an organization to determine the current and target level of adoption, given organizational context, ambitions, and domain constraints.

Characterization of continuous experimentation in software engineering: Expressions, models, and strategies

Continuous Experimentation (CE) has become increasingly popular across industry and academic communities. Major software organizations use CE to increase their revenue by adding value to end-users, and researchers are investigating the CE adoption process and usage to expand its success. Given this rapid evolution, observing a shared understanding of CE definitions, processes, and experiment strategies is difficult, potentially jeopardizing new implementations and focused research efforts. To characterize CE from the perspective of its definitions, processes, and strategies for experimentation available in the technical literature and to evolve the understanding perspectives for “continuous experimentation” and “data-driven development” definitions. To select and analyze sources of information in the technical literature dealing with different aspects of continuous experimentation through a Literature Study using an ad hoc search improved with snowballing (backward and forward). Organize the findings into new perspectives for CE definitions, processes, and experiment strategies. It was possible to identify many different definitions, processes, and experimental strategies used to describe CE in the 72 analyzed empirical papers, making it difficult to decide on their combination to be applied in a real software development project. Therefore, it has been proposed to evolve the CE understanding perspective, to categorize its experiment strategies, and to offer a combined development process for CE combining parts of other processes. Besides, conjectural requirements have been identified, which can contribute to better differentiating requirements and hypotheses in the CE context. Likely, a better understanding of CE is still missing. It can contribute towards organizing a common taxonomy to facilitate the possible choices for the experiment strategies. Therefore, there is space for more investigations on its applicability and value in different categories of software systems, despite all the advancements of CE and its promotion in developing modern software systems.

Facilitators and inhibitors of Agile methods adoption: Practitioners view

AbstractThis study provides empirical evidence to the body of knowledge in Agile methods adoption in small, medium, and large organizations in the global context. This research explores facilitators and inhibitors of Agile methods adoption in software development organizations. A survey was conducted among Agile professionals to gather survey data from 52 software organizations in seven countries across the world. This study found many facilitators of Agile adoption to be significant such as customers’ dominant issues, encouragement, project champion, highly competent team, use of tools, etc. Similarly a correlation analysis revealed multiple inhibitors as significant: absence of a full set of right Agile practices, absence of customer presence, absence of tracking mechanisms during Agile progress, and failure to determine the role of the client. The present study identifies that an Agile team with high expertise and competence leads to higher quality in software, customer satisfaction along with return on investment (ROI) while a small Agile team increases ease in handling changing requirements, customer satisfaction, reduced delivery time, and increased ROI. Frequent delivery accelerates better control over work, adds to software quality, customer satisfaction, and in shortening delivery time along with increase ROI. It has also been observed that providing essential features early leads to increase in software quality and customer satisfaction. This study confirms that active customer focus leads to better control over work. Further, absence of customer decreases dealing with changing requirements, and customer satisfaction while absence of progress tracking lowers customer satisfaction.

Hybrid Scrum-XP: A Proposed Model based on Effectiveness of Agile Model on Varieties of Software Companies in Bangladesh

The Agile Methodology is a term which refers to a method of software development that is incremental and iterative in nature and is used to manage and incorporate constantly changing needs. This entails decomposing the entire development process cycle into a series of tasks. The process is further divided into a number of sub-tasks, each function is independently. The Agile Development technique, which is a popular and growth-oriented strategy, provides not only speedy project delivery, but also software responsiveness, which leads to total corporate growth and agility. The organization's project management capabilities and performance are improved through the adoption of Agile practices. In their business, the companies employ Agile methods. As a result, the goal of this study is to see how effective agile approaches are in Bangladeshi software organizations. A survey of established software companies in Bangladesh is being conducted to accomplish the objective. The Scrum and XP agile technique is the most widely used according to the findings. It is proposed that Scrum and the XP model be combined to achieve maximum effectiveness and overcome their respective limits.

Agile software development and software practitioners’ productivity amidst the COVID-19 pandemic: a narrative review

PurposeAs the novel coronavirus 2019 (COVID-19) impacts the world, software practitioners are collaboratively working remotely from home. The pandemic has disrupted software practitioners’ productivity forcing changes to agile methodology adopted by software practitioners in software organizations. Therefore, this study aims to provide implication on the issues and recommendations for improving software practitioners’ productivity and also examine the impact of the COVID-19 pandemic on agile software development.Design/methodology/approachThis paper adopts a narrative literature review to provide early assessment based on secondary data from the literature and available document reports from studies published from 2019 to 2022 to explore software practitioners’ productivity and agile software development during the working from home directive amidst the COVID-19 pandemic. A total of 60 sources which met the inclusion criteria were used to provide preliminary evidence grounded on secondary data from the literature. Descriptive analysis was used to provide qualitative findings from the literature.FindingsFindings from this study present the significance of working from home directive on agile software development and software practitioners’ productivity. More importantly, findings from the secondary data shed light on software practitioners’ productivity adopting agile software development amidst the COVID-19 pandemic. Additionally, the findings present virtual collaborative platforms used by software practitioners, technical and social barriers of agile software development during the pandemic and recommendations for remote agile software development.Originality/valueThis study explores the significance of working from home directive on software practitioners’ productivity during COVID-19 pandemic and further investigates how are software practitioners’ productivity adopting agile software development practices amidst the COVID-19 pandemic. Besides, this study discusses the challenges software practitioners currently face and offers some strategies to bridge the gaps in agile software development to help software practitioners, system developers, software managers and software organizations adapt to the changes caused by the pandemic.

An Actionable Framework for Understanding and Improving Developer Experience

Developer experience is an important concern for software organizations as enhancing developer experience improves productivity, satisfaction, engagement and retention. We set out to understand what affects developer experience through semi-structured interviews with 21 developers from industry, which we transcribed and iteratively coded. Our findings elucidate factors that affect developer experience and characteristics that influence their respective importance to individual developers. We also identify strategies employed by individuals and teams to improve developer experience and the barriers that stand in their way. Lastly, we describe the coping mechanisms of developers when developer experience cannot be sufficiently improved. Our findings result in the DX Framework, an actionable conceptual framework for understanding and improving developer experience. The DX Framework provides a go-to reference for organizations that want to enable more productive and effective work environments for their developers.

How to Move from Agile to Agility in Software Organizations

Agility adoption in software development organizations is considered a strong solution to managing a rapidly changing, uncertain, and unsteady workplace. Especially, as the objective of Agility is to control changes that may happen. So, moving from Agile to Agility increases the organizations’ ability in swiftly and effectively react to unexpected variations in market requests. Agile refers to a mindset emphasizing teamwork, frequent value delivery, and the ability to deal with functional changes. The distinction between Agile and Agility needs to be understood in order to prevent misunderstandings, because Agility is recognized as one of the most important attributes of an organization against market turbulence. Through systematic mapping, this research explores the transition from Agile to Agility in software development companies. Systematic mapping is a technique for gathering, collating, and presenting research evidence. Eight research questions were identified, and to provide answers to these questions, several research papers have been explored in electronic databases. Eventually, 33 research papers were inspected, and answers to all research questions were provided. The results that have been achieved by this research proved that Agile and Agility differ in terms of definitions, attributes, numbers of dimensions, and the dimensions themselves

Knowledge Condensation Model to Support Expertise Location in Software Development

inding relevant expertise is a critical need in software organizations since developers use it to support their knowledge needs. Developers accumulate expertise from the technologies they used, and the problems solved within projects (e.g., bug solving, requirements, architecture design). However members of the organizations do not benefit from this expertise, so knowing how to model it then could grant access to the best practices, training practices, and data across applications. In this work, we present a model that implements the knowledge condensation concept to capture exprtise during the software developing process, which aims to classify, retrieve, and share valuable knowledge among stakeholders in an unsuitable form for its recovery. The model consists of three modules: formal grammar, semantic knowledge, and expertise tools. In the formal grammar module, an approach is made to formalize the description of how developers store and share their knowledge. An architectural knowledge model is proposed in the semantic knowledge module. Finally, in the module of expertise tools, two prototypes were developed using the elements from the semantic knowledge module.