Open source framework usage : an investigation of the user's intention to continue using a framework

viii, 129 leaves : ill. ; 29 cmTo increase productivity, application developers are using tools that allow them to create higher quality applications faster. One such set of tools, open-source frameworks, allows application developers to reuse software artifacts and should increase application quality. However, given the vast number of open-source frameworks available, users must be able to differentiate among frameworks and select the one best suited for them. In this study, we expand the taxonomy of open-source frameworks and analyze the impact of the framework's characteristics, technical quality, and social pressure on perceived usefulness and continued framework usage intention. Our findings suggest that understandability and flexibility have a significant impact on perceived ease of use, while perceived usefulness is mainly determined by flexibility and efficiency. Our research can be used to understand what influences developers to continue using frameworks and to improve framework development

The dynamics of digital platform innovation: unfolding the paradox of control and generativity in Apple's iOS

Mobile digital platforms provide an architectural basis for third party innovation of platform complements. Platform owners have property rights, enabling them to establish a boundary of permissible innovation demarcating the permitted from the prohibited. This allows for the curation of complements, which provides a means of controlling for value creation. Consequently, platform innovationthe innovation of platform complements is occasionally refused by platform owners. When this occurs tensions may arise between the two parties over where the boundary of permissible innovation should lie. Tussles may break out, embodied in complex interactions, as each party attempts to get its way. Eventually an outcome is achieved, and a platform innovation is either allowed or prohibited. A body of platform innovation literature is emerging from fields including information systems. Whilst this literature considers many aspects of platform innovation, the dynamics concerning the control of the innovation of platform innovation complements is overlooked. This research attempts to address that gap. Its relevance to information systems concerns the digitalisation of platforms as systemsdigital infrastructures, which affects their capacity for innovation and regulation. This research uses the method of narrative networks to analyse 45 examples of contested platform innovation. This approach, informed by empirical data sourced from over 4500 blog entries, identifies patterned sequences of actions across the examples. These sequences describe how tension builds, how control is asserted, and how control is then resisted. A theory of formal managerial control is used to explain how mechanisms of control are applied by platform owners as well as how developers respond to control. The principle contribution of this research is to theory. It develops and presents a theory to describe and explain the dynamics of contested innovation of complements on curated digital platforms. In doing so, iIt challenges the understanding that the platform owner alone controls platform design rules and concerning which platform complements are allowed, and which are notthe boundary of permissible innovation. Furthermore, tThe study indicates opens up the possibility that the forces of digitalisation provide third parties with the power to affect influence platform architecture, but at the cost of additional means of being controlled

BIM-based Generative Modular Housing Design and Implications for Post-Disaster Housing Recovery

The adverse social and financial impacts of catastrophic disasters are increasing as population centers grow. After disastrous events, the government agencies must respond to post-disaster housing issues quickly and efficiently and provide sufficient resources for the reconstruction of destroyed and damaged houses for full rehabilitation. However, post-disaster housing reconstruction is a highly complex process because of the large number of projects, shortage of resources, and heavy pressure for delivery of the projects after a disastrous event. This complexity and lack of an inconsistent, systematic approach for planning lead to an ad-hoc decision-making process and inefficient recovery. This research explored modular construction as a highly time-efficient approach to tackle the abovementioned challenges and facilitate the housing reconstruction process. Firstly, this research investigated the feasibility of using the modular construction method for rapid post-disaster housing reconstruction through a targeted literature review and survey of subject matter experts to broaden the understanding of modular construction-based post-disaster housing reconstruction, benefits, and barriers. Second, this research focused on improving the design and pre-planning phase of modular construction that can facilitate the successful implementation of modular construction in a post-disaster situation. To this end, a BIM-based generative modular housing design system was developed by using Generative Adversarial Networks (GANs) to automate the entire design process by incorporating manufacturing and construction constraints to fit the needs of the modular construction method. The framework was further extended by developing an optimization model to optimize the modularization strategy in the early design phase which was capable of reflecting the entire multi-stage process of modular construction (production, transportation, and assembly), and considering both individual project’s requirements and post-disaster housing reconstruction portfolio’s requirements. The outcomes of this study fit the MC industry that may be used by designers and modular housing companies looking to automate their design process. It is also expected to provide critical benchmarks for planners, decision-makers, and community developers to facilitate their decision-making process on considering modular construction as an efficient way for mass post-disaster housing reconstruction and addressing communities’ housing needs following a disastrous event

ICSEA 2021: the sixteenth international conference on software engineering advances

The Sixteenth International Conference on Software Engineering Advances (ICSEA 2021), held on October 3 - 7, 2021 in Barcelona, Spain, continued a series of events covering a broad spectrum of software-related topics. The conference covered fundamentals on designing, implementing, testing, validating and maintaining various kinds of software. The tracks treated the topics from theory to practice, in terms of methodologies, design, implementation, testing, use cases, tools, and lessons learnt. The conference topics covered classical and advanced methodologies, open source, agile software, as well as software deployment and software economics and education. The conference had the following tracks: Advances in fundamentals for software development Advanced mechanisms for software development Advanced design tools for developing software Software engineering for service computing (SOA and Cloud) Advanced facilities for accessing software Software performance Software security, privacy, safeness Advances in software testing Specialized software advanced applications Web Accessibility Open source software Agile and Lean approaches in software engineering Software deployment and maintenance Software engineering techniques, metrics, and formalisms Software economics, adoption, and education Business technology Improving productivity in research on software engineering Trends and achievements Similar to the previous edition, this event continued to be very competitive in its selection process and very well perceived by the international software engineering community. As such, it is attracting excellent contributions and active participation from all over the world. We were very pleased to receive a large amount of top quality contributions. We take here the opportunity to warmly thank all the members of the ICSEA 2021 technical program committee as well as the numerous reviewers. The creation of such a broad and high quality conference program would not have been possible without their involvement. We also kindly thank all the authors that dedicated much of their time and efforts to contribute to the ICSEA 2021. We truly believe that thanks to all these efforts, the final conference program consists of top quality contributions. This event could also not have been a reality without the support of many individuals, organizations and sponsors. We also gratefully thank the members of the ICSEA 2021 organizing committee for their help in handling the logistics and for their work that is making this professional meeting a success. We hope the ICSEA 2021 was a successful international forum for the exchange of ideas and results between academia and industry and to promote further progress in software engineering research

Exploring regression testing and software product line testing - research and state of practice

In large software organizations with a product line development approach a selective testing of product variants is necessary in order to keep pace with the decreased development time for new products, enabled by the systematic reuse. The close relationship between products in product line indicates an option to reduce the testing effort due to redundancy. In many cases test selection is performed manually, based on test leaders’ expertise. This makes the cost and quality of the testing highly dependent on the skills and experience of the test leaders. There is a need in industry for systematic approaches to test selection. The goal of our research is to improve the control of the testing and reduce the amount of redundant testing in the product line context by applying regression test selection strategies. In this thesis, the state of art of regression testing and software product line testing are explored. Two extensive systematic reviews are conducted as well as an industrial survey of regression testing state of practice and an industrial evaluation of a pragmatic regression test selection strategy. Regression testing is not an isolated one-off activity, but rather an activity of varying scope and preconditions, strongly dependent on the context in which it is applied. Several techniques for regression test selection are proposed and evaluated empirically but in many cases the context is too specific for a technique to be easily applied directly by software developers. In order to improve the possibility for generalizing empirical results on regression test selection, guidelines for reporting the testing context are discussed in this thesis. Software product line testing is a relatively new research area. The understanding about challenges is well established but when looking for solutions to these challenges, we mostly find proposals, and empirical evaluations are sparse. Regression test selection strategies proposed in literature are not easily applicable in the product line context. Instead, control may be increased by increased visibility of the effects of testing and proper measurements of software quality. Focus of our future work will be on how to guide the planning and assessment of regression testing activities in large, complex reuse based systems, by visualizing the quality achieved in different parts of the system and evaluating the effects of different selection strategies when applied in various regression testing situations