Journal of Systems and Software最新文献

{"title":"Empirical pathways to developer experience: A facet-based synthesis of empirical designs and guidelines","authors":"Abdul Razzaq ,&nbsp;Goetz Botterweck ,&nbsp;Qin Lai ,&nbsp;Jim Buckley","doi":"10.1016/j.jss.2025.112648","DOIUrl":"10.1016/j.jss.2025.112648","url":null,"abstract":"<div><h3>Context:</h3><div>Developer eXperience (Dev-X) focuses on ensuring a better experience for software developers, while still achieving development goals. Indeed, several existing studies suggest that improved Dev-X may actually result in improved development productivity. But a comprehensive understanding of how to empirically assess Dev-X remains limited.</div></div><div><h3>Aims and Method:</h3><div>This paper determines the empirical coverage of Dev-X facets to date by analyzing employed empirical designs and identifying quality issues or guidelines for assessing Dev-X. To this end, it presents a mapping study of 231 articles that employed empirical methods to explore the Dev-X landscape.</div></div><div><h3>Results:</h3><div>It identifies 16 facets of Dev-X—spanning emotions, values, and perceptions—and systematically maps the empirical methods, data types, and evaluation metrics used to assess these facets. The findings reveal gaps in facet coverage, highlight underutilized empirical designs, and stress the importance of quality assessment and methodological triangulation. This research offers a facet-wise synthesis of empirical designs and provides actionable guidelines to help researchers and practitioners empirically evaluate Dev-X.</div></div><div><h3>Conclusion:</h3><div>Based on SLR findings, this paper presents a Dev-X facet-based <em>synthesis</em> of empirical designs to guide selection of method, data, and metric combinations in future studies. By revealing design gaps (e.g., underexplored facets, overuse of surveys, weak corroboration) and highlighting dominant practices (e.g., survey-based ratings for emotions and values), our facet-wise schema offers an evidence-based guide for context-appropriate Dev-X evaluation strategies.</div><div><em>Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board</em>.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"233 ","pages":"Article 112648"},"PeriodicalIF":4.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated end-to-end testing for conversational agents","authors":"Juan de Lara ,&nbsp;Alejandro del Pozzo ,&nbsp;Esther Guerra ,&nbsp;Jesús Sánchez Cuadrado","doi":"10.1016/j.jss.2025.112685","DOIUrl":"10.1016/j.jss.2025.112685","url":null,"abstract":"<div><div>The advances in generative artificial intelligence, especially Large Language Models (LLMs), have prompted the proliferation of conversational agents (or chatbots). These can be general-purpose – like ChatGPT – or tailored to specific tasks – like buying tickets or obtaining customer support. Although chatbots play a significant role in today’s software ecosystem, they are hard to test: defining meaningful, thorough tests is time-consuming, and setting an oracle flexible to conversational variations is challenging. This is aggravated when testing LLM-based chatbots, as their conversation is natural but unpredictable.</div><div>To alleviate this problem, we present an end-to-end testing approach for conversational agents, comprising two components. First, a highly customisable user simulator that generates meaningful conversations with a chatbot under test, for the given goals (e.g., setting an appointment) and communication styles (e.g., long/short phrases, spelling mistakes). Second, a domain-specific language to specify and check correctness conditions (assertions and metamorphic relations) on the generated conversations. The conditions can assess functional correctness (e.g., booking more tickets costs more) and interaction styles (e.g., the chatbot responds in English and does not deviate from certain topics). This paper describes the approach, an implementation enabling chatbots’ testing independently of their technology, and an evaluation of its effectiveness in finding defects. We tested our tool on chatbots with artificially injected errors, and on third-party, real-world chatbots. Our tool detected between 81.25 % and 100 % of the injected errors, and identified actual functional issues in the real-world chatbots by applying manually defined correctness rules.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"233 ","pages":"Article 112685"},"PeriodicalIF":4.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial of the special issue in the journal of systems and software on managing technical debt in software-intensive products and services","authors":"Zadia Codabux ,&nbsp;Rodrigo Spinola ,&nbsp;Carolyn Seaman ,&nbsp;Matthias Galster","doi":"10.1016/j.jss.2025.112687","DOIUrl":"10.1016/j.jss.2025.112687","url":null,"abstract":"","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"233 ","pages":"Article 112687"},"PeriodicalIF":4.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Only less labeled: How to learn representations from multi-domain","authors":"Chunyong Zhang ,&nbsp;Liangwei Yao","doi":"10.1016/j.jss.2025.112713","DOIUrl":"10.1016/j.jss.2025.112713","url":null,"abstract":"<div><div>Software vulnerability detection is an essential part of cybersecurity. The basis of software vulnerability detection is source code detection. Under the assumption that there is sufficient labeled data for training, machine learning and deep learning can automatically and effectively find vulnerabilities. However, due to the lack of high-quality labeled data, the vulnerability detection performance of some deep learning-based methods is poor. Therefore, we propose a way to learn feature representations from multi-domain heterogeneous vulnerability data. It can form the basis of transferring knowledge and improve the vulnerability detection performance. First, we use real-world data Ffmqem and synthetic data SARD as data sources to learn feature extractors to represent the objective function. Next, we obtain the combined vector representation of the target code function for training the vulnerability classifier. Finally, we conducted extensive experiments on two open-source projects. The experimental results show that OLL has better vulnerability detection performance in scenarios with a small amount of labeled data. Compared with SDV, it improves 4.1 % and 3.1 % on the F1-Score metrics. It is demonstrated that learning combined vector representations from two heterogeneous data compensates for the small amount of labeled data. They facilitate the learning of representations of loophole functions.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"233 ","pages":"Article 112713"},"PeriodicalIF":4.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial of the special issue in the journal of systems and software on reliable and secure large language models for software engineering","authors":"Antonio Mastropaolo ,&nbsp;Pietro Liguori ,&nbsp;Gabriele Bavota","doi":"10.1016/j.jss.2025.112683","DOIUrl":"10.1016/j.jss.2025.112683","url":null,"abstract":"","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"233 ","pages":"Article 112683"},"PeriodicalIF":4.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From engineering models to digital twins: Generating AAS from SysML v2 models","authors":"Enxhi Ferko ,&nbsp;Luca Berardinelli ,&nbsp;Alessio Bucaioni ,&nbsp;Moris Behnam ,&nbsp;Manuel Wimmer","doi":"10.1016/j.jss.2025.112688","DOIUrl":"10.1016/j.jss.2025.112688","url":null,"abstract":"<div><div><strong>Context:</strong> Digital twins serve as virtual representations of systems, enabling capabilities such as intelligent monitoring, real-time control, decision-making, and predictive analytics. The Asset Administration Shell (AAS) is the pivotal Industry 4.0 standard for digital twin engineering. In parallel, the Systems Modeling Language (SysML) has emerged as a modeling standard for systems engineering, providing a formalized and semantically rich approach to system modeling. SysML v2 is its recent evolution. With its growing adoption, multiple models are expected to be widely available, each capturing different facets of the modeled system by leveraging diverse engineering capabilities offered by various tool ecosystems. <strong>Problem:</strong> Instead of manually re-creating models for digital twinning, existing system models should be leveraged to relieve repetitive modeling tasks. While SysML v2 and AAS are prominent standards in DT engineering, they lack direct integration, necessitating a dedicated approach for their seamless interoperability. <strong>Purpose:</strong> This paper presents a practical investigation into the conceptual alignment between the SysML v2 and AAS specifications, with a focus on their structural and behavioral modeling aspects. It proposes an implementable approach for mapping SysML v2 to AAS, enabling the automated generation of AAS models from SysML v2 models. <strong>Method:</strong> To realize this approach, we employ model-driven engineering techniques leveraging the Eclipse Modeling Framework (EMF) and model transformations based on the Query View Transformation (QVT) language. The proposed model transformation incorporates query mechanisms for extracting structured elements, preserving information and structural integrity, and ensuring static semantic consistency at design-time and seamless integration between the two investigated standards. We develop and validate the model transformation following an iterative test-driven development approach using an existing set of 24 SysML v2 examples, sourced from the official SysML v2 repository. <strong>Result:</strong> We deliver a QVT-based, EMF-compliant transformation that automatically generates AAS submodel templates from SysML v2 models, preserving structural hierarchies and behavioral semantics via dedicated AAS concepts and their extension. Through an iterative, test-driven development process, we validate metamodel conformance, information preservation, and structural integrity. The current mapping addresses design-time concepts, and the implementation supports forward transformation. All conceptual mappings, QVT scripts, and example artifacts are publicly available in a dedicated repository.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"233 ","pages":"Article 112688"},"PeriodicalIF":4.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Software product families from a phylogenetics perspective for video game content generation","authors":"Samuel Navarro ,&nbsp;Jorge Chueca ,&nbsp;Daniel Blasco ,&nbsp;Carlos Cetina ,&nbsp;Jaime Font","doi":"10.1016/j.jss.2025.112649","DOIUrl":"10.1016/j.jss.2025.112649","url":null,"abstract":"<div><div>A Software Product Family comprises similar products within a defined scope that share common characteristics, often due to reuse techniques applied during development. This paper introduces two approaches that apply biological insights to map the landscape of a software product family, identifying potential gaps within its scope, and identifying and extracting features from the family, respectively. Phylogenetics studies the gene similarity among groups of organisms to understand ancestry among species. Leveraging Phylogenetics in software, our approaches offer a structured view of a product family, aiding in the discovery of unexplored areas fitting the scope of the family. Our approaches create a phylogenetic tree that enables to easily identify latent products (ancestors) that did not exist in the original family. Those ancestors can then be reconstructed from existing products (descendants). Moreover, the phylogenetic tree can be exploited to identify and extract features from the family. Then, those features can be injected into other members of the family. The product family evaluated is a set of industry-scale video game non-playable characters. We assess these approaches through video game simulations and scope metrics to determine how closely the reconstructed and injected products align with the family’s scope. The results confirm that the content generated with our phylogenetics-based approaches aligns better with the family scope than the state-of-the-art procedural content generation techniques using evolutionary algorithms. Phylogenetics enhances content generation by providing a framework to understand and expand the product family with new content.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"232 ","pages":"Article 112649"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proactive self-adaptation and assurance of explainable Human–Machine Teaming","authors":"Livia Lestingi ,&nbsp;Marcello M. Bersani ,&nbsp;Matteo Camilli ,&nbsp;Raffaela Mirandola ,&nbsp;Matteo Rossi ,&nbsp;Patrizia Scandurra","doi":"10.1016/j.jss.2025.112657","DOIUrl":"10.1016/j.jss.2025.112657","url":null,"abstract":"<div><div>With the pervasiveness of software-intensive systems, autonomous agents are increasingly involved in missions entailing close cooperation with humans in critical domains. Human–Machine Teaming (HMT) requires agents to have a high degree of autonomy to make dependable decisions in safety-critical settings and quickly react to unexpected changes in the environment. We present AdaptEASE, a framework that leverages formal modeling and verification to model HMT missions offline and predict the mission outcome at runtime through Machine Learning (ML) models trained on Statistical Model Checking (SMC) results. The framework also exploits explainable AI techniques to inform stakeholders on what factors impact the predicted outcome positively or negatively. Building upon previous work, AdaptEASE enhances the controlled autonomous agents with the capability to self-adapt at runtime proactively. Specifically, if an unfavorable situation emerges during the HMT, AdaptEASE identifies an adaptation action that guarantees balance between the agents’ performance and the involved human subjects’ comfort levels. While runtime adaptation exploits ML predictors to preserve the timeliness of the HMT, the proposed adaptation action is asynchronously subject to formal verification to provide stakeholders with an assessment of the agents’ decisions and of the overall HMT trustworthiness. The validation testbed is a case study from the healthcare robot domain. The optimized versions of 1000 different mission configurations lead to a statistically significant estimated increase of HMT performance. The asynchronous SMC formal verification confirms that 75% of the optimized configurations increase the HMT performance.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"232 ","pages":"Article 112657"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimenting Architectural Patterns in Federated Learning Systems","authors":"Ivan Compagnucci ,&nbsp;Riccardo Pinciroli ,&nbsp;Catia Trubiani","doi":"10.1016/j.jss.2025.112655","DOIUrl":"10.1016/j.jss.2025.112655","url":null,"abstract":"<div><div>Federated Learning has emerged as a promising paradigm that enables collaborative model training while preserving data privacy, thus contributing to enhance user trust. However, the design of Federated Learning systems requires non-trivial architectural choices to address several challenges, such as system efficiency and learning accuracy. Architectural patterns for Federated Learning systems have been defined in the literature to handle these challenges, but their experimentation is limited. The objective of this paper is to empower software architects in their task of evaluating the design of FL systems while deciding which architectural alternatives are more beneficial in their context of adoption. Our methodology consists of a tool-based approach that embeds the implementation of six architectural patterns defined in the literature. The advantage is that software architects can select design alternatives either in isolation or in a combined fashion, and the subsequent analysis provides the evaluation of some metrics of interest. The experimental results indicate that architectural patterns can enhance system efficiency, although we found a combination of patterns that added overhead and turned to limit its benefit. By quantifying these trade-offs, we aim to support software architects in designing Federated Learning systems by evaluating the benefits and drawbacks of applying architectural patterns.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"232 ","pages":"Article 112655"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Web app performance testing in industrial contexts: Supporting workload generation with E2E-Loader++","authors":"Sergio Di Meglio ,&nbsp;Luigi Libero Lucio Starace ,&nbsp;Sergio Di Martino","doi":"10.1016/j.jss.2025.112684","DOIUrl":"10.1016/j.jss.2025.112684","url":null,"abstract":"<div><div>Performance testing is essential for ensuring that web applications remain responsive and reliable under varying workloads. Defining meaningful workloads remains a key challenge in performance testing, with existing solutions requiring deployed systems to collect real user behaviors, offering limited support for automated data dependency management, and lacking support for emerging protocols like WebSocket.</div><div>Our previous work introduced E2E-Loader, a novel approach that supports the definition of performance testing workloads by exploiting existing End-to-End functional test cases, enabling workload creation even before system deployment. While initial results demonstrated technical feasibility, the practical utility and industrial readiness of automated workload generation remained unvalidated in real-world software engineering contexts.</div><div>In this paper, we present E2E-Load-er++, an enhanced version of our original tool, with significant improvements to dependency detection capabilities, and provide the first rigorous industrial evaluation of our semi-automated performance testing workload generation approach. The comprehensive empirical assessment we conducted involved controlled experiments with professional software engineers working on proprietary industrial applications, aimed at measuring both technical effectiveness and practical impact of E2E-Loader++ on performance testing workflows.</div><div>Results demonstrate substantial productivity gains: compared to manual approaches, E2E-Loader++ achieved a 62 % reduction rate in workload creation time and a 37 % reduction rate in the number of required user interactions per minute, while preserving comparable workload quality.</div><div>Moreover, the tool received strong usability ratings and practitioner acceptance, confirming its potential for real-world adoption in industrial performance testing workflows.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"232 ","pages":"Article 112684"},"PeriodicalIF":4.1,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}