23 papers · ranked by Valyu relevance
Nicolaas Weideman, Sima Arasteh, Mukund Raghothaman, Jelena Mirković + 1 more
—Data-flow analysis is a critical component of security research. Theoretically, accurate data-flow analysis in binary executables is an undecidable problem, due to complexities of binary code. Practically, many binary analysis engines offer some data-flow analysis capability, but we lack understanding of the accuracy…
Marcos Lordello Chaim, Kesina Baral, Jeff Offutt
—Data flow testing creates test requirements as definition-use (DU) associations, where a definition is a program location that assigns a value to a variable and a use is a location where that value is accessed. Data flow testing is expensive, largely because of the number of test requirements. Luckily , many…
Nicolas Boltz, Sebastian Hahner, Christopher Gerking, Robert Heinrich
Information Security Authors: ['Nicolas Boltz' 'Sebastian Hahner' 'Christopher Gerking' 'Robert Heinrich'] Abstract. The growing interconnection between software systems increases the need for security already at design time. Security-related properties like confidentiality are often analyzed based on data flow…
Rohan Padhye, Uday P. Khedker
We describe a general-purpose interprocedural analysis framework for Soot using data flow values for context-sensitivity. This framework is not restricted to problems with distributive flow functions, although the lattice must be finite. It combines the key ideas of the tabulation method of the functional approach and…
Wilhelm Hasselbring, Maik Wojcieszak, Schahram Dustdar
When we consider the application layer [1] of networked infrastructures, data and control flow are important concerns in distributed systems integration. Modularity is a fundamental principle in software design [2], in particular for distributed system architectures. Modularity emphasizes high cohesion of individual…
Mohammed K. S. Alwaheidi, Shareeful Islam, Lei Shu
Cloud computing offers many benefits including business flexibility, scalability and cost savings but despite these benefits, there exist threats that require adequate attention for secure service delivery. Threats in a cloud-based system need to be considered from a holistic perspective that accounts for data…
Charlotte Capitanchik, Sam Ireland, Alex Harston, Chris Cheshire + 13 more
Ever-increasing volumes of sequencing data offer potential for large-scale meta-analyses to address significant biological questions. However, challenges such as insufficient data processing information, data quality concerns, and issues related to accessibility and curation often present obstacles. Additionally, most…
Chengyu Zhang, Ting Su, Yichen Yan, Ke Wu + 1 more
Dataflow coverage, one of the white-box testing criteria, focuses on the relations between variable definitions and their uses. Several empirical studies have proved data-flow testing is more effective than control-flow testing. However, data-flow testing still cannot find its adoption in practice, due to the lack of…
Ramanathan Ramu, Ganesha Upadhyaya, Hoan Anh Nguyen, Hridesh Rajan
Many data-driven software engineering tasks such as discovering programming patterns, mining API specifications, etc., perform source code analysis over control flow graphs (CFGs) at scale. Analyzing millions of CFGs can be expensive and performance of the analysis heavily depends on the underlying CFG traversal…
Jiazhen Zhao, Kailong Zhu, Canju Lu, Jun Zhao + 2 more
PHP is the most widely used server-side programming language, but it remains highly susceptible to diverse classes of vulnerabilities. Static Application Security Testing (SAST) tools are commonly adopted for vulnerability detection; however, their evaluation lacks systematic criteria capable of quantifying information…
Hui He, Dongyan Zhang, Min Liu, Weizhe Zhang + 1 more
Software security defects have a serious impact on the software quality and reliability. It is a major hidden danger for the operation of a system that a software system has some security flaws. When the scale of the software increases, its vulnerability has becoming much more difficult to find out. Once these…
Kejun Chen, Xiaolong Guo, Qingxu Deng, Yier Jin + 1 more
Dynamic information flow tracking (DIFT) has been proven an effective technique to track data usage; prevent control data attacks and non-control data attacks at runtime; and analyze program performance. Therefore, a series of DIFT techniques have been developed recently. In this paper, we summarize the current DIFT…
Gaurav Kaushik, Sinisa Ivkovic, Janko Simonovic, Nebojsa Tijanic + 2 more
As biomedical data becomes increasingly easy to generate in large quantities, the methods used to analyze it have proliferated rapidly. However, for the insights gained from these analyses to be meaningful, the analysis methods themselves must be transparent and reproducible. To address this issue, numerous groups have…
Hannah den Braanker, Margot Bongenaar, Erik Lubberts
Spectral flow cytometry is an upcoming technique that allows for extensive multicolor panels, enabling simultaneous investigation of a large number of cellular parameters in a single experiment. To fully explore the resulting high-dimensional single cell datasets, high-dimensional analysis is needed, as opposed to the…
Taylor Reiter, Phillip T. Brooks, Luiz Irber, Shannon E.K. Joslin + 4 more
As the scale of biological data generation has increased, the bottleneck of research has shifted from data generation to analysis. Researchers commonly need to build computational workflows that include multiple analytic tools and require incremental development as experimental insights demand tool and parameter…
Nawsher Khan, Ibrar Yaqoob, Ibrahim Abaker Targio Hashem, Zakira Inayat + 4 more
'Zakira Inayat' 'Waleed Kamaleldin Mahmoud Ali' 'Muhammad Alam' 'Muhammad Shiraz' 'Abdullah Gani'] Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Aleksandar Jagličić, Torben Gädt, Matthias Hofmann
Isothermal heat flow calorimetry is a powerful method for studying chemical processes. In cement research, it has become indispensable for quantifying the heat release during cement hydration. It is used to study the reactivity of cementitious binders and the effect of admixture chemistry and dosage. Most isothermal…
Michael Statt, Kristopher Brown, Santosh Suram, Linda Hung + 3 more
In this work, we present DBgen, a Python library that provides a framework for defining extract-transform-load (ETL) pipelines to create and populate SQL databases. DBgen is most useful when the underlying data has complex relationships, requires multi-step analysis, is large-scale, and the type of data being collected…
Samuel Lampa, Martin Dahlö, Jonathan Alvarsson, Ola Spjuth
The complex nature of biological data has driven the development of specialized software tools. Scientific workflow management systems simplify the assembly of such tools into pipelines and assist with job automation and aids reproducibility of analyses. Many contemporary workflow tools are specialized and not designed…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Authors not listed
ElyteOS is a graphical user interface written in Python 3.8.3 which enables the automation of the processes of electrolyte preparation, measurement, data storage, and data visualization. It provides a user-friendly interface and acts as a framework for automating lab equipment with different commands as well as…
Mahnoor Zulfiqar, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck + 2 more
Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for…