Architectural technical debt identification:The research landscape

Architectural Technical Debt (ATD) regards sub-optimal design decisions that bring short-term benefits to the cost of long-term gradual deterioration of the quality of the architecture of a software system. The identification of ATD strongly influences the technical and economic sustainability of software systems and is attracting growing interest in the scientific community. During the years several approaches for ATD identification have been conceived, each of them addressing ATD from different perspectives and with heterogeneous characteristics. In this paper we apply the systematic mapping study methodology for identifying, classifying, and evaluating the state of the art on ATD identification from the following three perspectives: publication trends, characteristics, and potential for industrial adoption. Specifically, starting from a set of 509 potentially relevant studies, we systematically selected 47 primary studies and analyzed them according to a rigorously-defined classification framework. The analysis of the obtained results supports both researchers and practitioners by providing (i) an assessment of current research trends and gaps in ATD identification, (ii) a solid foundation for understanding existing (and future) research on ATD identification, and (iii) a rigorous evaluation of its potential for industrial adoption

Guidelines for architecting android apps:A mixed-method empirical study

For surviving in the highly competitive market of Android apps, it is fundamental for app developers to deliver apps of high quality and with short release times. A well architected Android app is beneficial for developers, e.g. in terms of maintainability, testability, performance, and avoidance of resource leaks. However, how to properly architect Android apps is still debated and subject to conflicting opinions usually influenced by technological hypes rather than objective evidence. In this paper we present an empirical study on how developers architect Android apps, what architectural patterns and practices Android apps are based on, and their potential impact on quality. We apply a mixed-method empirical research design that combines (i) semi-structured interviews with Android practitioners in the field and (ii) a systematic analysis of both the grey (i.e., websites, on-line blogs) and white literature (i.e., academic studies) on the architecture of Android apps. Based on the analysis of the state of the art and practice about architecting Android apps, we systematically extract a set of 42 evidence based guidelines supporting developers when architecting their Android apps

Variability Features: Extending Sustainability Decision Maps via an Industrial Case Study

Over the years, various thinking frameworks have been developed to address sustainability as a quality property of software-intensive systems. Notwithstanding, which quality concerns should be selected in practice that have a significant impact on sustainability remains a challenge.In this experience report, we propose the notion of variability features, i.e., specific software features which are implemented in a number of possible alternative variants, each with a potentially different impact on sustainability. We extended sustainability decision maps to incorporate these variability features into an already existing thinking framework.Our findings were derived from a qualitative case study and evaluated in an industrial context. Data was collected by analysing a real-world application and conducting working sessions together with expert interviews.The variability features allowed us to identify and evaluate alternative usage scenarios of one real-world software-intensive system, enabling data-driven sustainability choices and suggestions for professional practices. By providing concrete measurements, we can support software architects at design time, and decision makers towards achieving sustainability goals

The future of sustainable digital infrastructures: A landscape of solutions, adoption factors, impediments, open problems, and scenarios

Background: Digital infrastructures, i.e., ICT systems, or system-of-systems, providing digital capabilities, such as storage and computational services, are experiencing an ever-growing demand for data consumption, which is only expected to increase in the future. This trend leads to a question we need to answer: How can we evolve digital infrastructures to keep up with the increasing data demand in a sustainable way?Objective: The goal of this study is to understand what is the future of sustainable digital infrastructures, in terms of: which solutions are, or will be, available to sustainably evolve digital infrastructures, and which are the related adoption factors, impediments, and open problems.Method: We carried out a 3-phase mixed-method qualitative empirical study, comprising semi-structured interviews, followed by focus groups, and a plenary session with parallel working groups. In total, we conducted 13 sessions involving 48 digital infrastructure practitioners and researchers.Results: From our investigation emerges a landscape for sustainable digital infrastructures, composed of 30 solutions, 5 adoption factors, 4 impediments, and 13 open problems. We further synthesized our results in 4 incremental scenarios, which outline the future evolution of sustainable digital infrastructures.Conclusions: From an initial shift from on-premise to the cloud, as time progresses, digital infrastructures are expected to become increasingly distributed, till it will be possible to dynamically allocate resources by following time, space, and energy. Numerous solutions will support this change, but digital infrastructures are envisaged to be able to evolve sustainably only by (i) gaining a wider awareness of digital sustainability, (ii) holding every party accountable for their sustainability throughout value chains, and (iii) establishing cross-domain collaborations

Building and evaluating a theory of architectural technical debt in software-intensive systems

Architectural technical debt in software-intensive systems is a metaphor used to describe the “big” design decisions (e.g., choices regarding structure, frameworks, technologies, languages, etc.) that, while being suitable or even optimal when made, significantly hinder progress in the future. While other types of debt, such as code-level technical debt, can be readily detected by static analyzers, and often be refactored with minimal or only incremental efforts, architectural debt is hard to be identified, of wide-ranging remediation cost, daunting, and often avoided. In this study, we aim at developing a better understanding of how software development organizations conceptualize architectural debt, and how they deal with it. In order to do so, in this investigation we apply a mixed empirical method, constituted by a grounded theory study followed by focus groups. With the grounded theory method we construct a theory on architectural technical debt by eliciting qualitative data from software architects and senior technical staff from a wide range of heterogeneous software development organizations. We applied the focus group method to evaluate the emerging theory and refine it according to the new data collected. The result of the study, i.e., a theory emerging from the gathered data, constitutes an encompassing conceptual model of architectural technical debt, identifying and relating concepts such as its symptoms, causes, consequences, management strategies, and communication problems. From the conducted focus groups, we assessed that the theory adheres to the four evaluation criteria of classic grounded theory, i.e., the theory fits its underlying data, is able to work, has relevance, and is modifiable as new data appears. By grounding the findings in empirical evidence, the theory provides researchers and practitioners with novel knowledge on the crucial factors of architectural technical debt experienced in industrial contexts

Empirical evaluation of an architectural technical debt index in the context of the Apache and ONAP ecosystems

Background. Architectural Technical Debt (ATD) in a software-intensive system denotes architectural design choices which, while being suitable or even optimal when adopted, lower the maintainability and evolvability of the system in the long term, hindering future development activities. Despite the growing research interest in ATD, how to gain an informative and encompassing viewpoint of the ATD present in a software-intensive system is still an open problem. Objective. In this study, we evaluate ATDx, a data-driven approach providing an overview of the ATD present in a software-intensive system. The approach, based on the analysis of a software portfolio, calculates severity levels of architectural rule violations via a clustering algorithm, and aggregates results into different ATD dimensions. Method. To evaluate ATDx, we implement an instance of the approach based on SonarQube, and run the analysis on the Apache and ONAP ecosystems. The analysis results are then shared with the portfolio contributors, who are invited to participate in an online survey designed to evaluate the representativeness and actionability of the approach. Results. The survey results confirm the representativeness of the ATDx, in terms of both the ATDx analysis results and the used architectural technical debt dimensions. Results also showed the actionability of the approach, although to a lower extent when compared to the ATDx representativeness, with usage scenarios including refactoring, code review, communication, and ATD evolution analysis. Conclusions. With ATDx, we strive for the establishment of a sound, comprehensive, and intuitive architectural view of the ATD identifiable via source code analysis. The collected results are promising, and display both the representativeness and actionability of the approach. As future work, we plan to consolidate the approach via further empirical experimentation, by considering other development contexts (e.g., proprietary portfolios and other source code analysis tools), and enhancing the ATDx report capabilities

Green IT and Green Software

Software and IT usage are continuously growing to keep our society active and manage our individual lives. But as they grow, their energy demand is exploding. By 2030, data centers alone will already consume some 10% of the global electricity.1 Including the Internet, telecommunications, and embedded devices, the energy consumption will be one-third of the global demand. Understanding that end users only consume what we offer, it is the community of software developers who must become active in ecologic behaviors. Green IT is the call of today. Each single line of code that we develop today may still be running years from now on zillions of processors, eating energy and contributing to global climate change

Exploring Technical Debt in Security Questions on Stack Overflow

Background: Software security is crucial to ensure that the users are protected from undesirable consequences such as malware attacks which can result in loss of data and, subsequently, financial loss. Technical Debt (TD) is a metaphor incurred by suboptimal decisions resulting in long-term consequences such as increased defects and vulnerabilities if not managed. Although previous studies have studied the relationship between security and TD, examining their intersection in developers' discussion on Stack Overflow (SO) is still unexplored. Aims: This study investigates the characteristics of security-related TD questions on SO. More specifically, we explore the prevalence of TD in security-related queries, identify the security tags most prone to TD, and investigate which user groups are more aware of TD. Method: We mined 117,233 security-related questions on SO and used a deep-learning approach to identify 45,078 security-related TD questions. Subsequently, we conducted quantitative and qualitative analyses of the collected security-related TD questions, including sentiment analysis. Results: Our analysis revealed that 38% of the security questions on SO are security-related TD questions. The most recurrent tags among the security-related TD questions emerged as "security" and "encryption." The latter typically have a neutral sentiment, are lengthier, and are posed by users with higher reputation scores. Conclusions: Our findings reveal that developers implicitly discuss TD, suggesting developers have a potential knowledge gap regarding the TD metaphor in the security domain. Moreover, we identified the most common security topics mentioned in TD-related posts, providing valuable insights for developers and researchers to assist developers in prioritizing security concerns in order to minimize TD and enhance software security.Comment: The 17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), 202