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

Developing an educational framework for using mobile learning during the era of COVID-19

This paper focuses on the impact of fear emotion upon technology adoption by educators and students during Covid-19 pandemic. Mobile learning (m-learning) has been applied as the educational social platform within higher education institutes, public as well as private. The research hypotheses were associated with the Covid-19 influence on m-learning adoption with the rise of the coronavirus increasing types of fear. Such fears include fear caused by the education failure, family lockdown, and loss of social relationships. Teachers and students are mostly fearful of these aspects of the situation. An integrated model was established within the research, using theoretical models; the Planned Behavior theory, the Technology Acceptance Model, and the Expectation-Confirmation Model. The proposed integrated model (using PLS-SEM software) was analyzed using an online survey data, with 420 respondents from Zayed University, UAE. The findings indicated that attitude was the best predictor for using the m-learning system, followed by continuous intention, expectation confirmation, perceived usefulness, ease-of-use, perceived fear, behavioral control, and satisfaction. According to the research, during the coronavirus pandemic, if the m-learning system is adopted for educational reasons, the learning and teaching outcome proves quite promising. Yet there is a fear of the family being stressed, or of loss of friends, and also a fear of the results of future schooling. It is therefore necessary to assess the students efficiently during this pandemic so that the situation can be managed emotionally

Identifying Architectural Technical Debt: Moving Forward

In software-intensive systems, technical debt is a metaphor encompassing design and implementation constructs that are used as expedients in the short term, but that hinder future maintainability and evolvability. Architectural technical debt, in turn, adopts such concept by considering sub-optimal architectural design and implementation choices that bring short-term benefits to the cost of the long-term gradual deterioration of the quality of the software architecture. Architectural technical debt is an active field of research. Nevertheless, how to accurately identify and manage architectural technical debt is still an open question. Our research aims to fill this gap. In particular, our goal is to: (i) consolidate the existing knowledge of architectural technical debt identification and its management in practice, (ii) conceive novel identification and management approaches built upon the existing state of the art techniques and industrial needs, and (iii) provide empirical evidence of architectural technical debt phenomena and assess the viability of the conceived approaches. As a result, we envision a sound methodology aimed to support software architects in the identification and management of architectural technical debt throughout the software development process

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

The Influence of Cognitive Biases on Architectural Technical Debt

Cognitive biases exert a significant influence on human thinking and decision-making. In order to identify how they influence the occurrence of architectural technical debt, a series of semi-structured interviews with software architects was performed. The results show which classes of architectural technical debt originate from cognitive biases, and reveal the antecedents of technical debt items (classes) through biases. This way, we analysed how and when cognitive biases lead to the creation of technical debt. We also identified a set of debiasing techniques that can be used in order to prevent the negative influence of cognitive biases. The observations of the role of organisational culture in the avoidance of inadvertent technical debt throw a new light on that issue.Comment: Presented at 2021 IEEE 18th International Conference on Software Architecture (ICSA) 202

EXTENDING THE TECHNOLOGY ACCEPTANCE MODEL IN E-LEARNING DISCUSSION FORUM ADOPTION: UNIVERSITY OF TECHNOLOGY STUDENTS’ PERSPECTIVES

Published ThesisThe advancement of Information and Communication Technology and the Internet for educational purposes has been a staple discourse among researchers in recent years. However, preliminary investigations indicate that e-learning systems are underutilised due to the fact that some of their major features, like electronic discussion forums, remain inactive. Despite several scholars reporting on high levels of e-learning system implementation at Universities of Technology, it is unnerving that discussion forums within these platforms remain poorly utilised. The purpose of this study is to establish constructs that may promote the adoption and use of discussion forums. The Technology Acceptance Model forms the theoretical framework for this study and is extended by including digital inclusion, attention and perceived enjoyment. The research design adopted in this study was a mixed-method approach, focusing on both quantitative and qualitative data analysis. The target population for qualitative data collection was 210, however, only 182 agreed to participate in the study. Qualitative data was collected from thirty participants who were purposefully selected from a third year Information Technology class and interviewed with regards to the different constructs which make up the Technology Acceptance Model. Findings of this study suggest that perceived usefulness and ease, along with digital inclusion, may positively influence adoption and use of discussion forums at Universities of Technology. Both attention and perceived enjoyment were found to have a positive relationship on perceived usefulness and attitude. Furthermore, digital inclusion could be implemented to improve the perceived ease-of-use of the system, which ultimately leads to improved behavioural intention and usage. Improved usage of components within the Learning Management System leads to a healthy, functioning system used to its full potential, which benefits the learning experience for both student and academic. The study contributes to the board of knowledge by providing useful insights into the application of the Technology Acceptance Model. This is done by establishing additional constructs that may promote discussion forum usage