Abstract. Model-Driven Engineering (MDE) has been promoted as a solution to handle the complexity of software development by raising the abstraction level and automating labor-intensive and error-prone tasks. However, few efforts have been made at collecting evidence to evaluate its benefits and limitations, which is the subject of this review. We searched several publication channels in the period 2000 to June 2007 for empirical studies on applying MDE in industry, which produced 25 papers for the review. Our findings include industry motivations for investigating MDE and the different domains it has been applied to. In most cases the maturity of third-party tool environments is still perceived as unsatisfactory for large-scale industrial adoption. We found reports of improvements in software quality and of both productivity gains and losses, but these reports were mainly from small-scale studies. There are a few reports on advantages of applying MDE in larger projects, however, more empirical studies and detailed data are needed to strengthen the evidence. We conclude that there is too little evidence to allow generalization of the results at this stage.
Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected. We argue that Model-Driven Development can be helpful in this context as it would allow developers to design software systems in a cloud-agnostic way and to be supported by model transformation techniques into the process of instantiating the system into specific, possibly, multiple Clouds. The MODA-CLOUDS (MOdel-Driven Approach for the design and execution of applications on multiple Clouds) approach we present here is based on these principles and aims at supporting system developers and operators in exploiting multiple Clouds for the same system and in migrating (part of) their systems from Cloud to Cloud as needed. MODACLOUDS offers a qualitydriven design, development and operation method and features a Decision Support System to enable risk analysis for the selection of Cloud providers and for the evaluation of the Cloud adoption impact on internal business processes. Furthermore, MODACLOUDS offers a run-time environment for observing the system under execution and for enabling a feedback loop with the design environment. This allows system developers to react to performance fluctuations and to redeploy applications on different Clouds on the long term.
Abstract. Systematic software reuse is proposed to increase productivity and software quality and lead to economic benefits. Reports of successful software reuse programs in industry have been published. However, there has been little effort to organize the evidence systematically and appraise it. This review aims to assess the effects of software reuse in industrial contexts. Journals and major conferences between 1994 and 2005 were searched to find observational studies and experiments conducted in industry, returning eleven papers of observational type. Systematic software reuse is significantly related to lower problem (defect, fault or error) density in five studies and to decreased effort spent on correcting problems in three studies. The review found evidence for significant gains in apparent productivity in three studies. Other significant benefits of software reuse were reported in single studies or the results were inconsistent. Evidence from industry is sparse and combining results was done by votecounting. Researchers should pay more attention to using comparable metrics, performing longitudinal studies, and explaining the results and impact on industry.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.