No abstract
Abstract-Modern software systems often make use of thirdparty components to speed-up development and reduce maintenance costs. In return, developers need to update to new releases of these dependencies to avoid, for example, security and compatibility risks. In practice, prioritizing these updates is difficult because the use of outdated dependencies is often opaque. In this paper we aim to make this concept more transparent by introducing metrics to quantify the use of recent versions of dependencies, i.e. the system's "dependency freshness".We propose and investigate a system-level metric based on an industry benchmark. We validate the usefulness of the metric using interviews, analyze the variance of the metric through time, and investigate the relationship between outdated dependencies and security vulnerabilities. The results show that the measurements are considered useful, and that systems using outdated dependencies four times as likely to have security issues as opposed to systems that are up-to-date.
Novel therapeutic agents combined with innovative modes of delivery and non-invasive imaging of drug delivery, pharmacokinetics and efficacy are crucial in developing effective clinical anti-cancer therapies. In this study, we have created and characterized multiple novel variants of anti-angiogenic protein thrombospondin (aaTSP-1) that were comprised of unique regions of 3 type-I-repeats of TSP-1 and employed engineered human neural stem cells (hNSC) to provide sustained on-site delivery of secretable aaTSP-1 to tumor-vasculature. We show that hNSC-aaTSP-1 has anti-angiogenic effect on human brain and dermal microvascular endothelial cells co-cultured with established glioma cells and CD133+ glioma-initiating-cells. Using human glioma cells and hNSC engineered with different combinations of fluorescent and bioluminescent marker proteins and employing bioluminescence imaging and intravital-scanning microscopy, we show that aaTSP-1 targets the vascular-component of gliomas and a single administration of hNSC-aaTSP-1 markedly reduces tumor vessel-density that results in inhibition of tumor-progression and increased survival in mice bearing highly malignant human gliomas. We also show that therapeutic hNSC do not proliferate and remain in an un-differentiated state in the brains of glioma bearing mice. This study provides a platform for accelerated development of future cell based therapies for cancer.
Abstract.Clean is an experimental language for specifying functional computations in terms of graph rewriting. It is based on an extension of Term Rewriting Systems (TRS) in which the terms are replaced by graphs. Such a Graph Rewriting System (GRS) consists of a, possibly cyclic, directed graph, called the data graph and graph rewrite rules which specify how this data graph may be rewr~en. Clean is designed to provide a firm base for functional programming. In particular, Clean is suitable as an intermediate language between functional languages and (parallel) target machine architectures. A sequential implementation of Clean on a conventional machine is described and its performance is compared with other systems. The results show that Clean can be efficiently implemented.
Certification of software artifacts offers organizations more certainty and confidence about software. Certification of software helps software sales, acquisition, and can be used to certify legislative compliance or to achieve acceptable deliverables in outsourcing. In this article, we present a software product certification model. This model has evolved from a maturity model for product quality to a more general model with which the conformance of software product artifacts to certain properties can be assessed. Such a conformance assessment we call a 'software product certificate'. The practical application of the model is demonstrated in concrete software certificates for two software product areas that are on different ends of the software product spectrum (ranging from a requirements definition to an executable). For each certificate, a concrete case study has been performed. We evaluate the use of the model for these certificates. It will be shown that the model can be used satisfactorily for quite different kinds of certificates.
A b str a c t. We present a size-aware type system for first-order shapely function definitions. Here, a function definition is called shapely when the size of the result is determined exactly by a polynomial in the sizes of the arguments. Examples of shapely function definitions may be matrix multiplication and the Cartesian product of two lists. The type checking problem for the type system is shown to be undecidable in general. We define a natural syntactic restriction such that the type checking becomes decidable, even though size polynomials are not necessarily linear or monotonic. Furthermore, a method that infers poly nomial size dependencies for a non-trivial class of function definitions is suggested.1
In this paper we p r esent a t ype system f o r g r aph rewrite systems: uniqueness typing. It employs u s a ge information to deduce whether an o b j e c t i s u n i q u e ' a t a certain moment, i.e. is only locally accessible. In a type of a function it can bespeci ed that the function requires a unique argument o b j e c t. The correctness of type assignment guarantees that no external a ccess on t h e o r iginal o bject will take place in the future. The presented t ype system is proven to be correct. We illustrate the power of the system by de ning an elegant q u i c ksort a l g orithm that performs the sorting in situ on the data structure.
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.