arXiv subjects

Elisa Yumi Nakagawa

Publications and source records attributed to Elisa Yumi Nakagawa.

17 recordsLinked to original sources

arXiv2026

Teaching Business Process Modeling to Leverage Soft Skills of Computing Students

Background and Context: Organizations have highly depended on software systems to realize their business processes and achieve strategic business goals and competitive advantage; hence, computing professionals who can understand these processes could more effectively build such systems. At the same time, while Artificial Intelligence (AI) has increased the productivity in developing these and other systems, professionals should be better prepared due to the competitiveness of the job market; thus, soft skills could be an important factor to ensure their position in this market. Objective: This paper aims to analyze and present the impact of teaching business process modeling to leverage key soft skills of future computing professionals. Method and Findings: Our method involved an industry-driven, project-based approach with 53 computing students who actively interacted with stakeholders and modeled the organization's business process. We systematically collected the students' feedback, including the soft skills practiced and demonstrating that professionalism, initiative, motivation, communication, and teamwork can be leveraged. Implications: The main implication of this work for the Computer Science Education research community is to provide evidence that teaching business process modeling subjects is particularly beneficial for future professionals, as it could contribute to preparing them regarding their soft skills for the era of AI-assisted software development.

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arXiv2026

TagDebt: A Bot to Support Technical Debt Management

Context: Technical debt (TD) is a widely studied metaphor that helps to explain how sub-optimal decisions that can harm software maintainability over time. Although incurring TD is not intrinsically bad, tracking and managing TD are crucial to avoid its negative effects. Hence, researchers and practitioners have proposed and developed diverse approaches and tools for managing TD. However, we are still lacking specialized tools for technical debt management (TDM), specifically ones that can be easily integrated into existing development workflows. Objective: We present and evaluate TagDebt, a bot that can be integrated within GitHub repositories and automatically assign labels to issues (i.e., SATD or non-SATD). TagDebt helps in the identification of TD (i.e., by looking for self-admitted technical debt (SATD)), leading to more efficient TDM. Methods: We carried out a Design Science Research study to design and implement TagDebt. For its evaluation, we executed a Technology Acceptance Model (TAM) study through interviews with 16 practitioners, to check the bot's usefulness, ease of use, and contextual factors that might impact the bot's usage (such as team size and practitioners' roles). Results: Overall, practitioners found that TagDebt is useful, especially for organizing issues and reducing manual work. Furthermore, they pointed out that the bot is overall easy to use, and its documentation is clear. The analysis also revealed that contextual factors, such as team and codebase size, impact the decision to adopt TagDebt. Finally, several improvements were suggested, such as including features to check and update the source code. Conclusion: TagDebt is a proof-of-concept for the development and usage of more specialized tools for TDM. It helps to make TD visible without disrupting existing workflows and help practitioners avoid the risks of unmanaged TD.

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arXiv2026

Investigating CI/CD-based Technical Debt Management in Open-source Projects

Managing technical debt (TD) is critical to ensure the sustainability of long-term software projects. However, the time and cost involved in technical debt management (TDM) often discourage practitioners from performing this activity consistently. Continuous Integration and Continuous Delivery (CI/CD) pipelines offer an opportunity to support TDM by embedding automated practices directly into the development workflow. Despite this potential, it remains unclear how TDM tools could be integrated into CI/CD pipelines, and we still lack established best practices for this process. To address this problem, the objective of this study is to understand how TDM tools have been used in CI/CD pipelines and also identify potential configuration anti-patterns. To this end, we conducted a large-scale mining software repository (MSR) study on GitHub. In total, we collected around 600,000 Travis CI configuration files and 50,000 supporting scripts, and identified 3,684 pipelines that contain at least one TDM tool. We applied descriptive statistics to analyze the prevalence of tools and anti-patterns, and our findings show that most tools are executed and integrated using an external script; in addition, \textit{Absent Feedback} is the most common configuration anti-pattern. We believe that researchers and practitioners can use the evidence of this study to further investigate how to improve both the tools that are integrated in CI/CD and the integration practices.

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arXiv2026

Open Educational Resources: Barriers and Open Issues

Open Educational Resources (OER) are freely available teaching and learning materials, such as textbooks, videos, and interactive games, that can be used, reused, adapted, and shared. OER can leverage access, collaboration, and innovation in education; however, their adoption and long-term use remain limited. Motivated by this issue, this manuscript examined the literature and identified 26 social, economic, and technical barriers that hinder teachers, students, and institutions from creating, using, and maintaining OER. These barriers were evaluated through semi-structured interviews with experts to ensure their understandability, correctness, completeness, and relevance. We adopted a four-step research method: (1) a tertiary study that identified barriers from 26 secondary studies; (2) analysis and classification of the barriers according to social, economic, and technical dimensions and the OER lifecycle activities they affect; (3) design of the conceptual model to represent relationships among OER elements, barriers, and mitigation actions; and (4) evaluation through expert interviews. These barriers are also illustrated using a real-world OER. The findings provide insights for the education community, supporting inclusive strategies, institutional actions, and public policies to reduce social, economic, and technical barriers to OER. By addressing factors that affect accessibility, sustainability, and equitable participation, this manuscript advances universal access to educational resources and fosters more inclusive educational ecosystems.

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arXiv2025

Automating Technical Debt Management: Insights from Practitioner Discussions in Stack Exchange

Managing technical debt (TD) is essential for maintaining long-term software projects. Nonetheless, the time and cost involved in technical debt management (TDM) are often high, which may lead practitioners to omit TDM tasks. The adoption of tools, and particularly the usage of automated solutions, can potentially reduce the time, cost, and effort involved. However, the adoption of tools remains low, indicating the need for further research on TDM automation. To address this problem, this study aims at understanding which TDM activities practitioners are discussing with respect to automation in TDM, what tools they report for automating TDM, and the challenges they face that require automation solutions. To this end, we conducted a mining software repositories (MSR) study on three websites of Stack Exchange (Stack Overflow, Project Management, and Software Engineering) and collected 216 discussions, which were analyzed using both thematic synthesis and descriptive statistics. We found that identification and measurement are the most cited activities. Furthermore, 51 tools were reported as potential alternatives for TDM automation. Finally, a set of nine main challenges were identified and clustered into two main categories: challenges driving TDM automation and challenges related to tool usage. These findings highlight that tools for automating TDM are being discussed and used; however, several significant barriers persist, such as tool errors and poor explainability, hindering the adoption of these tools. Moreover, further research is needed to investigate the automation of other TDM activities such as TD prioritization.

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arXiv2025

Towards a Maturity Model for Systematic Literature Review Process

Systematic literature reviews (SLR) have been increasingly conducted in software engineering and they provide significant benefits in terms of summarizing the state of the research. The process of conducting SLR is complex, involving several activities and consuming considerable effort and time from researchers. Researchers often skip or poorly conduct essential activities, which introduce threats to validity, resulting in lower-quality SLR. But researchers are often unaware of what they could do to mature their SLR process, thus improving the SLR quality. The main goal of this paper is to introduce a maturity model for the SLR process named MM4SLR. To this end, we were inspired by well-known models like CMMI (Capability Maturity Model Integration). We first identified 39 key practices for SLR from the literature and grouped them into nine goals that were further grouped into five process areas. We then organized the process areas into five maturity levels which compose our model. Our proof of concept, applying the MM4SLR to four published SLR showed that the MM4SLR is suitable for appraising SLR and can identify important flaws in SLR quality. MM4SLR can therefore support researchers in creating their SLR processes and selecting practices that could be adopted to mature their processes.

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arXiv2025

Leveraging Sustainable Systematic Literature Reviews

Systematic Literature Reviews (SLRs) are a widely employed research method in software engineering. However, there are several problems with SLRs, including the enormous time and effort to conduct them and the lack of obvious impacts of SLR results on software engineering practices and industry projects. To address these problems, the concepts of \textit{sustainability} and \textit{sustainable SLR} have been proposed, aiming to raise awareness among researchers about the importance of dealing with SLR problems in a consistent way; however, practical and concrete actions are still lacking. This paper presents concrete directions towards sustainable SLRs. We first identified 18 ``green drivers'' (GD) that could directly impact SLR sustainability, and we distilled 25 sustainability indicators (SI) associated with the GD to assess SLRs regarding their sustainability. A preliminary evaluation was conducted on the ten top-cited SLRs in software engineering published over the last decade. From this analysis, we synthesized our insights into 12 leverage points for sustainability. Our results indicate that even in high-quality reviews, there are threats to sustainability, such as: flaws in the search process, lack of essential details in the documentation, weak collaboration with stakeholders, poor knowledge management, lack of use of supporting tools, and a dearth of practical insights for software engineering practitioners. The good news is that moving towards sustainable SLRs only requires some simple actions, which can pave the way for a profound change in the software engineering community's mindset about how to create and sustain SLRs.

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arXiv2024

Self-adaptive, Requirements-driven Autoscaling of Microservices

Microservices architecture offers various benefits, including granularity, flexibility, and scalability. A crucial feature of this architecture is the ability to autoscale microservices, i.e., adjust the number of replicas and/or manage resources. Several autoscaling solutions already exist. Nonetheless, when employed for diverse microservices compositions, current solutions may exhibit suboptimal resource allocations, either exceeding the actual requirements or falling short. This can in turn lead to unbalanced environments, downtime, and undesirable infrastructure costs. We propose MS-RA, a self-adaptive, requirements-driven solution for microservices autoscaling. MS-RA utilizes service-level objectives (SLOs) for real-time decision making. Our solution, which is customizable to specific needs and costs, facilitates a more efficient allocation of resources by precisely using the right amount to meet the defined requirements. We have developed MS-RA based on the MAPE-K self-adaptive loop, and have evaluated it using an open-source microservice-based application. Our results indicate that MS-RA considerably outperforms the horizontal pod autoscaler (HPA), the industry-standard Kubernetes autoscaling mechanism. It achieves this by using fewer resources while still ensuring the satisfaction of the SLOs of interest. Specifically, MS-RA meets the SLO requirements of our case-study system, requiring at least 50% less CPU time, 87% less memory, and 90% fewer replicas compared to the HPA.

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arXiv2023

Technical Debt Management Automation: State of the Art and Future Perspectives

Technical Debt (TD) refers to non-optimal decisions made in software projects that may lead to short-term benefits, but potentially harm the system's maintenance in the long-term. Technical debt management (TDM) refers to a set of activities that are performed to handle TD, e.g., identification. These activities can entail tasks such as code and architectural analysis, which can be time-consuming if done manually. Thus, substantial research work has focused on automating TDM tasks (e.g., automatic identification of code smells). However, there is a lack of studies that summarize current approaches in TDM automation. This can hinder practitioners in selecting optimal automation strategies to efficiently manage TD. It can also prevent researchers from understanding the research landscape and addressing the research problems that matter the most. Thus, the main objective of this study is to provide an overview of the state of the art in TDM automation, analyzing the available tools, their use, and the challenges in automating TDM. For this, we conducted a systematic mapping study (SMS), and from an initial set of 1086 primary studies, 178 were selected to answer three research questions covering different facets of TDM automation. We found 121 automation artifacts, which were classified in 4 different types (i.e., tools, plugins, scripts, and bots); the inputs/outputs and interfaces were also collected and reported. Finally, a conceptual model is proposed that synthesizes the results and allows to discuss the current state of TDM automation and related challenges. The results show that the research community has investigated to a large extent how to perform various TDM activities automatically, considering the number of studies and automation artifacts we identified. More research is needed towards fully automated TDM, specially concerning the integration of the automation artifacts.

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arXiv2022

Evolving Reference Architecture Description: Guidelines based on ISO/IEC/IEEE 42010

The architectural design of software systems is not a trivial task, requiring sometimes large experience and knowledge accumulated for years. Reference architectures have been increasingly adopted as a means to support such task, also contributing to the standardization and evolution of these systems. Although considerable time and effort are devoted to design these architectures, an outdated description is still found in several of them and, as a consequence, resulting in their non-continuation. This article presents guidelines to evolve the description of reference architectures, considering different types of stakeholders and required tasks. To complement our statement that the guidelines are correct by construction as they were grounded in widely known international standard ISO/IEC/IEEE 42010 and literature, we also briefly present a qualitative analysis comparing the guidelines with an ad hoc way (commonly occurred in reference architectures). We believe solutions like these guidelines are necessary and could further contribute to the sustainability and longevity of reference architectures.

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arXiv2022

Can Existing Approaches Manage Dynamic and Large Business Processes enacted through Systems-of-Systems?

In the era of joint ventures (JV) and mergers & acquisitions (M&A), dynamic and large business processes can emerge to achieve broader business goals and are often formed from business processes of distinct organizations. Software systems of such distinct organizations should support these larger processes and, for this, they need to communicate among them forming the so called Systems-of-Systems (SoS). However, the management of these larger processes and the correspondent SoS has been currently a complicated challenge for the alliances of organizations. In this scenario, the main contribution of this paper is to discover what has been proposed in the literature to manage these processes. We analyzed possibly all existing approaches and the findings point out that many of them cannot provide understanding of the whole large processes and, more importantly, they do not address completely the SoS inherent characteristics. We also highlight the next research directions to make possible the management of these dynamic, complex, interconnected business processes that have increasingly crossed several critical domains.

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arXiv2022

Establishing a Search String to Detect Secondary Studies in Software Engineering

Context: A tertiary study can be performed to identify related reviews on a topic of interest. However, the elaboration of an appropriate and effective search string to detect secondary studies is challenging for Software Engineering (SE) researchers. Objective: The main goal of this study is to propose a suitable search string to detect secondary studies in SE, addressing issues such as the quantity of applied terms, relevance, recall and precision. Method: We analyzed seven tertiary studies under two perspectives: (1) structure -- strings' terms to detect secondary studies; and (2) field: where searching -- titles alone or abstracts alone or titles and abstracts together, among others. We validate our string by performing a two-step validation process. Firstly, we evaluated the capability to retrieve secondary studies over a set of 1537 secondary studies included in 24 tertiary studies in SE. Secondly, we evaluated the general capacity of retrieving secondary studies over an automated search using the Scopus digital library. Results: Our string was capable to retrieve an optimum value of over 90\% of the included secondary studies (recall) with a high general precision of almost 60\%. Conclusion: The suitable search string for finding secondary studies in SE contains the terms "systematic review", "literature review", "systematic mapping", "mapping study" and "systematic map".

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arXiv2022

Benefits and Drawbacks of a Graduate Course: An Experience Teaching Systematic Literature Review

Graduate courses can provide specialized knowledge for Ph.D. and Master's students and contribute to develop their hard and soft skills. At the same time, Systematic Literature Review (SLR) has been increasingly adopted in the computing area as a valuable technique to synthesize the state of the art of a given research topic. However, there is still a poor understanding of the real benefits and drawbacks of offering the SLR course for graduate students. This paper reports an experience that examines such benefits and drawbacks, the difficulties for professors (i.e., educators), and the essential SLR topics to be taught as well as a way to better teach them. We also surveyed computer science graduate students who attended the SLR course, which we have offered for almost ten years for Ph.D. and Master's students in our institution. We found the attendance to the SLR course is a valuable opportunity for graduate students to conduct the required deep literature review of their research topic, improve their research skills, and increase their formation. Hence, we recommend that Ph.D. and Masters' programs offer the SLR course to contribute to their academic achievement.

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arXiv2021

Towards Sustainability of Systematic Literature Reviews

Background: The software engineering community has increasingly conducted systematic literature reviews (SLR) as a means to summarize evidence from different studies and bring to light the state of the art of a given research topic. While SLR provide many benefits, they also present several problems with punctual solutions for some of them. However, two main problems still remain: the high time-/effort-consumption nature of SLR and the lack of an effective impact of SLR results in the industry, as initially expected for SLR. Aims: The main goal of this paper is to introduce a new view - which we name Sustainability of SLR - on how to deal with SLR aiming at reducing those problems. Method: We analyzed six reference studies published in the last decade to identify, group, and analyze the SLR problems and their interconnections. Based on such analysis, we proposed the view of Sustainability of SLR that intends to address these problems. Results: The proposed view encompasses three dimensions (social, economic, and technical) that could become SLR more sustainable in the sense that the four major problems and 31 barriers (i.e., possible causes for those problems) that we identified could be mitigated. Conclusions: The view of Sustainability of SLR intends to change the researchers' mindset to mitigate the inherent SLR problems and, as a consequence, achieve sustainable SLR, i.e., those that consume less time/effort to be conducted and updated with useful results for the industry.

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arXiv2021

Expanding Frontiers: Settling an Understanding of Systems-of-Information Systems

System-of-Systems (SoS) has consolidated itself as a special type of software-intensive systems. As such, subtypes of SoS have also emerged, such as Cyber-Physical SoS (CPSoS) that are formed essentially of cyber-physical constituent systems and Systems-of-Information Systems (SoIS) that contain information systems as their constituents. In contrast to CPSoS that have been investigated and covered in the specialized literature, SoIS still lack critical discussion about their fundamentals. The main contribution of this paper is to present those fundamentals to set an understanding of SoIS. By offering a discussion and examining literature cases, we draw an essential settlement on SoIS definition, basics, and practical implications. The discussion herein presented results from research conducted on SoIS over the past years in interinstitutional and multinational research collaborations. The knowledge gathered in this paper arises from several scientific discussion meetings among the authors. As a result, we aim to contribute to the state of the art of SoIS besides paving the research avenues for the forthcoming years.

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arXiv2021

A Visual Analysis Approach to Update Systematic Reviews

Context: In order to preserve the value of Systematic Reviews (SRs), they should be frequently updated considering new evidence that has been produced since the completion of the previous version of the reviews. However, the update of an SR is a time consuming, manual task. Thus, many SRs have not been updated as they should be and, therefore, they are currently outdated. Objective: The main contribution of this paper is to support the update of SRs. Method: We propose USR-VTM, an approach based on Visual Text Mining (VTM) techniques, to support selection of new evidence in the form of primary studies. We then present a tool, named Revis, which supports our approach. Finally, we evaluate our approach through a comparison of outcomes achieved using USR-VTM versus the traditional (manual) approach. Results: Our results show that USR-VTM increases the number of studies correctly included compared to the traditional approach. Conclusions: USR-VTM effectively supports the update of SRs.

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arXiv2018

Toward Architectural Knowledge Sustainability. New Opportunities to Extend the Longevity of Systems

Complex software systems must be maintained for years or decades, and the effort and cost to maintain them are often high, involving continuous refactoring to ensure their longevity in the face of changing requirements. In this article, we introduce the notion of architectural knowledge (AK) sustainability as a new concept to support architects dealing with the evolution of long-lived systems. Architecture sustainability refers to the ability of the architecture to endure over time with the minimum number of refactoring cycles possible. We suggest that sustainability of the AK is a function of how stable the decisions are, and we discuss a set of sustainability criteria and metrics useful to estimate the sustainability of this AK.

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