Agile Processes in Software Engineering and Extreme Programming

The lack of core theories is a challenge for the whole software engineering (SE) discipline, particularly crucial for the agile software development (ASD) field, which is largely practice-driven. Without solid and continuous theoretical development glued by core theories, ASD risks repeating wrong practices and oversimplifying real-world phenomena. To address this issue and foster a strong link between empirical evidence and theoretical development, we conduct this critical review using the Complex Network Analysis (CNA) approach, in response to the editors’ call on the XP2020 conference. Based on 83 selected articles and 88 identified theories, our analysis traced the originating disciplines of these theories and synthesized 3 key theory communities. We position ASD core theories between empirical generalization and middle-range theories in the SE theory spectrum and offer practical guidelines for researchers to use, borrow, and generate ASD theories. It is further recommended that new theory development be aligned with the theory of coordination and control theory while employing Complex Adaptive Systems (CAS) theory as a theoretical lens when borrowing theories to ASD.

Agile coaching has emerged as a key enabler of agile adoption and organisational transformation. Despite its growing prevalence, there has not been much research into agile coaching, and there is a need for a better understanding of the current state of research and where the gaps lie. To fill this gap, we present a systematic mapping study (SMS) of agile coaching to identify and categorise existing research. An initial search identified 497 studies, of which 22 primary studies were selected based on inclusion and exclusion criteria. We provide a thematic analysis of the included papers and a summary of challenges and benefits associated with agile coaching. Key findings indicate a steady rate of research studies since 2013, predominantly from Europe. The most extensively researched areas are coaches’ skills, roles, and responsibilities. However, there is a noticeable lack of research depth in other areas and an absence of theory in all papers. Finally, we propose a roadmap for further research, highlighting unexplored aspects of agile coaching, including its impact across diverse organisational contexts. These findings provide a foundation for future research and offer practical insights for practitioners and researchers in the agile domain.

The Agile Manifesto emphasizes individuals and interactions over processes and tools. However, after the COVID-19 pandemic, interaction in software development changed, and companies are trying to find new practices in the hybrid environment. Hybrid work research points to the benefits for the individual, whereas companies have begun to form new rules and policies to get employees back to the office. To find a balance benefiting all, companies need to find new ways to connect and communicate. This paper explores how hybrid work impacts the sense of belonging in agile software development. We conducted interviews (N = 38) and a workshop (N = 15) with professionals from three case organizations. Our thematic analysis identifies key factors influencing belonging at the individual, team, and organizational levels. Our findings underline that continuous, conscious, and visible actions are needed at all levels to foster a sense of belonging. As hybrid work reduces spontaneous and random encounters, maintaining a sense of belonging requires planned efforts to recreate the informal interactions that once happened naturally.

The success of agile work heavily depends on people and their approach to challenges, with the agile mindset emerging as a pivotal driver. Despite its importance, Information Systems (IS) research lacks a systematic overview of the contexts where the agile mindset is relevant and the research gaps that remain. This study addresses this gap by systematically examining the factors influencing and resulting from the agile mindset in IS contexts and, for the first time, demonstrating its broad relevance across diverse IS domains.

We conducted a systematic literature review, analyzing 62 relevant papers from IS research. Our findings show that the agile mindset plays a central role in four key areas: (1) implementing agile methods or scaled agile frameworks during agile transformations, (2) applying digital tools and driving digital transformation, (3) supporting coaching, training, and education, and (4) leadership and management. This study’s originality lies in highlighting the agile mindset’s wide-ranging applicability, offering practitioners actionable insights for designing processes and mechanisms to enhance the success of agile work in IS. Additionally, researchers are provided with a roadmap of open questions and future research opportunities to deepen our understanding of this critical concept in IS contexts.

Agile software development relies on self-organized teams, underlining the importance of individual responsibility. How developers take responsibility and build ownership are influenced by external factors such as architecture and development methods. This position paper examines the existing literature on ownership in software engineering and in psychology, and argues that a more comprehensive view of ownership in software engineering has a great potential in improving software team’s work. Initial positions on the issue are offered for discussion and to lay foundations for further research.

Due to their benefits regarding resilience to change and adaptability, agile methods are widely adopted in the software development industry. Despite being intended for small co-located teams, organizations have started to scale agile methods, e.g., applying them in multi-team projects. Consequently, effective and efficient knowledge sharing and coordination become more complex, and agile intra-team practices are not sufficient anymore. While several case studies investigate knowledge sharing and coordination in the scaled agile context, an overview across multiple organizations is missing. To fill this gap, we combined the results of a literature review of 69 studies and an interview study to gain an overview of how coordination and knowledge sharing are conducted in scaled agile organizations and what factors hinder or facilitate their effectiveness and efficiency. Our findings show that organizations implement various mechanisms, including roles (e.g., Product Owners), meetings (e.g., ad-hoc exchange), tools and artifacts (e.g., chats), and other structures (e.g., Communities of Practice). Organizations struggle particularly with misalignment among teams and units, insufficient communication, and distribution across different working locations. Key enabling factors are documentation efforts, as well as both formal and informal exchanges. Context is crucial and should be regularly reassessed as needs evolve. Also, strong organizational support is needed to facilitate coordination and knowledge sharing.

User involvement is critical in large-scale agile software development. User representatives bridge access gaps and align development teams with user expectations. However, research primarily focuses on development-side user representatives like product owners or user experience designers, overlooking user-side representatives who bring practical expertise and bridge communication between users and development teams. This highlights a gap in understanding user-side representatives’ roles in large-scale agile software development for fostering effective collaboration. In this paper, we ask the following research question: What are the roles, responsibilities, and challenges of user-side representatives in large-scale agile software development? We conducted an exploratory case study within a large public organization using interviews, focus groups, and document analysis to answer this. We investigated two established user-side representative roles: implementation coordinators and change agents. In our distributed case organization, implementation coordinators serve as county-level contact points, overseeing planning, coordination, training, and follow-up of software release implementation. Based in local offices, change agents facilitate requirements elicitation, test software quality, train users, share knowledge, and handle user requests. These roles enhance communication of user needs, support alignment between development and user requirements, and complement development-side user representatives. These findings contribute to a deeper understanding of user involvement in large-scale, distributed agile software development.

New Work and agile methodologies share a common foundation in their aim to foster autonomy, collaboration, and adaptability. Their benefits make both concepts highly relevant for organizations as they support agility, innovation, and attractiveness to existing and potential employees. Still, implementing these concepts within large, established companies remains challenging. Therefore, this case study investigates a Community of Practice that promotes New Work principles within a large software organization aiming to be agile and innovative. Our study explores the establishment and functioning of this community and its effectiveness in advancing New Work practices within the case company. The community has been growing and has achieved its first success in promoting New Work, but there remains potential for improvement. In particular, a clearer mandate from the upper management is needed.

Agility embraces changes in the functional and non-functional requirements. When the latter happens, the architecture needs to evolve, putting architectural refactoring in evidence. Microservices is an architectural style that enables more agility in a system’s architecture, as it favors the evolution of the system by adding new operations. But it also has its liabilities: the number of services can explode, with similar ones being created. Ultimately, that harms the system’s evolution and maintenance. This work addresses these challenges by proposing a catalog of architecture refactorings to promote reusability in Microservices. These refactorings target patterns that embrace data heterogeneity in the APIs and employ metadata to enhance messages and guide processing. We evaluated the catalog with case studies of three real-world applications and conducted change impact analysis in two scenarios: adding a new data provider, and adding a new processing algorithm. The results showed that embracing heterogeneous data in the API enables a more seamless addition of new data providers, and using metadata can strongly decouple the processing algorithms from the data they use. Furthermore, the results point to other improvements in observability, scalability, and infrastructure.

Generative AI has been rapidly adopted by the software development industry in various ways, offering innovative approaches to transforming requirements into working software. Combining Generative AI with Test-Driven Development (TDD) presents a creative method to accelerate this transformation. However, questions remain about ChatGPT’s readiness for this challenge, including the techniques and best practices required for success and the scenarios where this approach can consistently deliver results. To explore these questions, we designed a study where a group of master’s students performed programming assignments using TDD, first independently and then with the support of ChatGPT. The three assignments represent distinct scenarios: mathematical calculations (function), text processing (class), and system integration (class with dependencies). We performed a qualitative analysis of the submitted code and reports identifying key strategies that significantly influence success rates, such as providing contextual information, separating instructions in prompts following an iterative process, and assisting AI in fixing errors. Among the scenarios, the integration task achieved the highest performance. This study highlights the potential of leveraging Generative AI in TDD for software development and presents a list of effective strategies to maximize its impact. By applying these positive strategies and avoiding identified pitfalls, this research marks a step toward establishing best practices for integrating Generative AI with TDD in software engineering.

Exploratory Testing (ET) is a dynamic software testing approach that emphasises creativity, real-time learning, and defect discovery. The integration of ET into structured frameworks like Scrum remains insufficiently explored and presents distinct challenges. This qualitative study investigates how ET is implemented in Scrum workflows and identifies key factors enabling its effective application.

Interviews with 20 industry professionals highlight ET’s role in enhancing test coverage, uncovering usability issues, and addressing edge cases often missed by automated or scripted tests. The results demonstrated that the critical enablers of effective ET are the tester’s eagerness to learn about the system under test and the ability to adopt a user-centric perspective. Other key factors include testers’ curiosity, creativity, domain knowledge, and organisational support. Participants noted that ET complements Scrum’s iterative cycles, enabling teams to identify defects dynamically and improve software quality.

Despite its advantages, ET faces challenges within Scrum, including time constraints and the need for traceability. Lightweight documentation practices, such as annotated mind maps and screen recordings, emerged as effective strategies to bridge these gaps. This study underscores ET’s potential to enhance Scrum workflows, providing actionable insights for optimising testing strategies in Agile environments.

Previous research has identified mutation testing as a promising technique for detecting unintended changes in test behavior during test code refactorings. Despite its theoretical support, the practical adoption of this approach has been hindered by a lack of corresponding tools. Consequently, these studies have been unable to fully validate the effectiveness of mutation testing as a guardrail to ensure the consistency of the refactored test behavior, leaving an in-depth empirical validation open for future research. To address this gap, this study examines MeteoR, a tool developed as a reference implementation to support test refactoring by using mutation testing. We leverage MeteoR to validate the practical applicability of the mutation testing approach across diverse test refactoring scenarios. This evaluation uses a catalog of common test refactorings that reflect real-world practices. The results indicate that MeteoR effectively detects changes in test behavior in most cases, demonstrating the efficacy of mutation testing to identify problems during test code refactoring. However, the study also identifies limitations, particularly the occurrence of false negatives when refactorings modify the way tests handle dependencies. These findings highlight the potential of the approach and contribute to the state-of-the-art by identifying limitations that can be addressed in future studies.

Visualization is a promising technique in TD management, but with various tools offering visualization, the question arise: is it being used effectively by practitioners? Through an analysis of survey data from 417 participants across seven international companies, we examine the current use of visualization and its perceived potential to improve TD management. Our findings reveal that while visualization tools are not widely used, there is a clear desire for enhanced visualization capabilities.

Accurate effort estimation in the software development industry remains a significant challenge due to requirements’ complexities, technology variability, and insufficient skilled members. To provide up-to-date insights on the state of effort estimation practices in Sri Lanka, we surveyed agile practitioners to identify the effort estimation techniques, types of metrics employed, levels of accuracy, and reasons for inaccuracies in estimates. Our analysis of 93 valid responses reveals that Planning Poker was the most popular estimation technique at 50.5%, while story points were the most widely used metric utilized by 61.3% of participants. Expert estimation was employed by 30% of respondents, and man-hours were used by 23.7%. The combination of Planning Poker and story points was most used, with a prevalence of 70.2%. Regarding the accuracy of estimations, respondents who used a combination of Planning Poker (61.7%) and expert estimation (25.5%) could complete their work within the estimated time without any extra effort. The top three categories of inaccurate estimates were quality-related, project management, and team-related issues.

Experimentation programs are vital for enabling data-driven decision-making within product development. However, evaluating their overarching success remains a significant challenge. Current metrics, such as conversion rates, primarily focus on individual experiments, leaving a gap in assessing broader program efficiency and impact. This paper addresses this gap by presenting a structured overview and analysis of 18 program-level metrics, categorized into six domains: Volume, Outcome-Based, Quality, Engagement, Process Efficiency and Strategic Alignment. Metrics such as experimentation throughput, time-to-decision and experimentation coverage are examined for their implications on operational efficiency, cultural adoption, and strategic alignment. Based on interviews with 48 experimentation practitioners, this work provides a description of these metrics and discusses their benefits and challenges. The results offer actionable insights for advancing experimentation practices and aligning them with organizational goals.

Companies adopt agile methodologies for various reasons, primarily due to their adaptability to change and evolving business demands. In this context, addressing non-functional requirements (NFRs) may not always be a priority and can present challenges for agile teams. The focus on User Stories present in agile methods and tools often does not offer explicit alternatives for documenting NFRs. In this research, we perform a survey to explore five different strategies for documenting NFRs, to identify which fits better for different types of quality attributes and to understand the strengths and drawbacks of each one. As a result, the participants considered certain strategies as being more or less suitable for specifying different types of quality attributes. For instance, while Story Labeling was rarely recommended for security requirements, using Story Sub-sections or Verification Rules were highly recommended for this kind of quality attribute. Our results also evaluated the strategies considering several factors, such as the level of detail and requirement duplication. As a practical implication, the results of this work can provide guidance to agile development teams in choosing the most suitable alternative for each NFR documentation.

Continuously delivering valuable software is a core principle of agile software development (ASD). In practice, value delivery is often impeded by several key issues, including low customer involvement, volatile requirements, technical debt, delivery pressure, excessive rework, or meeting overhead, which affect the product or the process. Despite their negative influence, the different consequences for the delivered value remain to be better understood. In addition, a collection of measures to help practitioners adapt to these issues is missing, as previous work only offers limited guidance on how to mitigate them. To address this situation, we conducted 19 semi-structured expert interviews to identify the consequences of key issues for value delivery and empirically derive measures to adapt to these issues. We find 34 value-reducing consequences, which primarily affect product quality and capabilities, delivery timeliness, and process efficiency. We also develop a collection of 48 measures to address the issues, including procedural changes, process artifacts and roles, technical means, and different ways to approach customers. With our work, we provide practitioners with actionable measures to adapt to issues encountered in daily practice and avoid their value-reducing consequences, thereby facilitating continuous value delivery. For research, we extend knowledge on the dark side of ASD by illustrating how key issues affect the delivered value, which was less regarded in related studies. In addition, we encourage future investigations into how micro-tailoring fosters sustained value delivery, along with examinations of resilience engineering in the context of ASD to improve the performance of software development processes.