A Systematic Mapping of Factors Affecting Accuracy of Software Development Effort Estimation

Software projects often do not meet their scheduling and budgeting targets. Inaccurate estimates are often responsible for this mismatch. This study investigates extant research on factors that affect accuracy of software development effort estimation. The purpose is to synthesize existing knowledge, propose directions for future research, and improve estimation accuracy in practice. A systematic mapping study (a comprehensive review of existing research) is conducted to identify such factors and their impact on estimation accuracy. Thirty-two factors assigned to four categories (estimation process, estimator’s characteristics, project to be estimated, and external context) are identified in a variety of research studies. Although the significant impact of several factors has been shown, results are limited by the lack of insight into the extent of these impacts. Our results imply a shift in research focus and design to gather more in-depth insights. Moreover, our results emphasize the need to argue for specific design decisions to enable a better understanding of possible influences of the study design on the credibility of the results. For software developers, our results provide a useful map to check the assumptions that undergird their estimates, to build comprehensive experience databases, and to adequately staff design projects

Development of an Internet-Based Chronic Disease Self-Management System

Patient self-management programs and information systems that support them can improve the quality of healthcare. Flaws in user experience reduce the willingness of patients to adopt such systems. To explore how emerging technology such as rich Internet applications can be used to address the usability issues of personal health information systems, we developed a health self-management application that is based on an open-source framework. In this work we present the architecture of the system, discuss the issues we faced and lessons we learned while developing it. This work can help researchers and practitioners in evaluating approaches towards developing new generation of personal health solutions. Furthermore, this work serves as a basis for implementing a feature-rich system that can improve chronic disease self-management

A design theory for transparency of information privacy practices

The rising diffusion of information systems (IS) throughout society poses an increasingly serious threat to privacy as a social value. One approach to alleviating this threat is to establish transparency of i nformation privacy practices (TIPP) so that consumers can better understand how their information is processed. However, the design of transparency artifacts (eg, privacy notices) has clearly not followed this approach, given the ever-increasing volume of information processing. Hence, consumers face a situation where they cannot see the ‘forest for the trees’ when aiming to ascertain whether information processing meets their privacy expectations. A key problem is that overly comprehensive information presentation results in information overload and is thus counterproductive for establishing TIPP. We depart from the extant design logic of transparency artifacts and develop a theoretical foundation (TIPP theory) for transparency artifact designs useful for establishing TIPP from the perspective of privacy as a social value. We present TIPP theory in two parts to capture the sociotechnical interplay. The first part translates abstract knowledge on the IS artifact and privacy into a description of social subsystems of transparency artifacts, and the second part conveys prescriptive design knowledge in form of a corresponding IS design theory. TIPP theory establishes a bridge from the complexity of the privacy concept to a metadesign for transparency artifacts that is useful to establish TIPP in any IS. In essence, transparency artifacts must accomplish more than offering comprehensive information; they must also be adaptive to the current information needs of consumers

Design Principles for Systematic Search Systems: A Holistic Synthesis of a Rigorous Multi-cycle Design Science Research Journey

Rigorous systematic literature searches are often described as complex, error-prone and time-consuming because of a prevailing lack of adequate technological assistance. Nonetheless, one of the first steps when conducting a rigorous literature review is finding an appropriate literature sample. The quality of this literature sample is an important factor for the overall quality of the literature review. This article investigates how to design innovative IT systems that effectively facilitate systematic literature searches. Applying the design science research paradigm, the research method consists of multiple design cycles of artifact development, evaluation, and refinement. In doing so, six design principles are derived that intend to increase the comprehensiveness, precision, and reproducibility of systematic literature searches. The results could be helpful for research and practice. The derived design knowledge builds a foundation for future research on systematic search systems and enables new methodological contributions. The results could also guide the development of innovative search systems and features that, eventually, increase the quality and efficiency of information accumulation in different contexts

Influential Factors on IS Project Quality: A Total Quality Management Perspective

Successful accomplishment of information system (IS) projects is a crucial challenge for researchers and practitioners. Agreement on influential factors, that is, success and failure factors, and on what constitutes success is lacking. Considering process and product quality an integral part of IS project success, we examine how project success and failure factors influence IS project quality. We conducted semi-structured interviews with 19 practitioners involved in IS projects and strategic decision making. This research-in-progress is based on total quality management (TQM), which facilitates continuous improvement of IS project quality. By applying an influential factor framework, we allow for a more detailed examination of success and failure factors not addressed in TQM. Our results suggest quality-specific themes, while acknowledging their context-dependency. By examining IS project quality and applying the influential factor framework, we expect to equip researchers and practitioners with an approach to examine specific dimensions of IS project success in detail

Architecture Matters: Investigating the Influence of Differential Privacy on Neural Network Design

One barrier to more widespread adoption of differentially private neural networks is the entailed accuracy loss. To address this issue, the relationship between neural network architectures and model accuracy under differential privacy constraints needs to be better understood. As a first step, we test whether extant knowledge on architecture design also holds in the differentially private setting. Our findings show that it does not; architectures that perform well without differential privacy, do not necessarily do so with differential privacy. Consequently, extant knowledge on neural network architecture design cannot be seamlessly translated into the differential privacy context. Future research is required to better understand the relationship between neural network architectures and model accuracy to enable better architecture design choices under differential privacy constraints

Trustworthy artificial intelligence

Artificial intelligence (AI) brings forth many opportunities to contribute to the wellbeing of individuals and the advancement of economies and societies, but also a variety of novel ethical, legal, social, and technological challenges. Trustworthy AI (TAI) bases on the idea that trust builds the foundation of societies, economies, and sustainable development, and that individuals, organizations, and societies will therefore only ever be able to realize the full potential of AI, if trust can be established in its development, deployment, and use. With this article we aim to introduce the concept of TAI and its five foundational principles (1) beneficence, (2) non-maleficence, (3) autonomy, (4) justice, and (5) explicability. We further draw on these five principles to develop a data-driven research framework for TAI and demonstrate its utility by delineating fruitful avenues for future research, particularly with regard to the distributed ledger technology-based realization of TAI