Ownership-based Alias Analysis for Securing Unsafe Rust Programs. This project aims to develop an ownership-based alias analysis as a complement to Rust's ownership type system for improving Rust's memory safety. This project, therefore, expects to deliver an alias analysis foundation that can provide stronger memory safety guarantees than the state-of-the-art in detecting memory-safety violations and security vulnerabilities in real-world Rust programs that use unsafe language features. The exp ....Ownership-based Alias Analysis for Securing Unsafe Rust Programs. This project aims to develop an ownership-based alias analysis as a complement to Rust's ownership type system for improving Rust's memory safety. This project, therefore, expects to deliver an alias analysis foundation that can provide stronger memory safety guarantees than the state-of-the-art in detecting memory-safety violations and security vulnerabilities in real-world Rust programs that use unsafe language features. The expected outcomes are a deployable ownership-based alias analysis in the Rust compiler and an industrial-strength open-source framework. These outcomes are expected to provide significant benefits in improving software quality and security in Rust, an emerging language that offers both performance and safety.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100473
Funder
Australian Research Council
Funding Amount
$410,154.00
Summary
Effective integration of human and automated analyses for security testing. This DECRA project aims to significantly improve the performance of current state-of-the-art automated security testing approaches, enabling them to discover more security bugs in strict time constraints. The key innovation of the project is its novel way to embrace human element to leverage the ingenuity of the developers. This project will help companies improve the security and reliability of their products, thwarting ....Effective integration of human and automated analyses for security testing. This DECRA project aims to significantly improve the performance of current state-of-the-art automated security testing approaches, enabling them to discover more security bugs in strict time constraints. The key innovation of the project is its novel way to embrace human element to leverage the ingenuity of the developers. This project will help companies improve the security and reliability of their products, thwarting cyberattacks that cost Australian business $29 billion each year. The knowledge from this project will be transferred and integrated into higher education subjects to train the next generations of software developers, who are responsible to build security-critical systems that we all rely on now and in the future.Read moreRead less
Domain-specific visual languages for big data analytics applications. This project aims to invent domain-specific visual languages and support model-driven engineering based infrastructure so domain experts can specify, generate and apply complex data analytics and visualisation techniques. Many domains, including intelligent transport, business intelligence, and population health, need more effective “big data” analytics and visualisation. A challenge is to combine detailed domain knowledge – w ....Domain-specific visual languages for big data analytics applications. This project aims to invent domain-specific visual languages and support model-driven engineering based infrastructure so domain experts can specify, generate and apply complex data analytics and visualisation techniques. Many domains, including intelligent transport, business intelligence, and population health, need more effective “big data” analytics and visualisation. A challenge is to combine detailed domain knowledge – what the data means and what it can be used for – with sophisticated, scalable computational techniques to mine and present information from the huge volumes of raw data. This project is expected to improve productivity and quality of big data analytics and visualisation in critical domains.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100040
Funder
Australian Research Council
Funding Amount
$442,302.00
Summary
Quality Assurance of Mobile Applications by Effective Testing and Repair. This project aims to create advanced techniques that will enable software engineers to effectively develop quality assured and robust software systems. This project expects to generate new and innovative approaches that automate software testing and repair. The expected outcomes of this project include new knowledge of software engineering, development of an automated and cost-effective testing system with improved coverag ....Quality Assurance of Mobile Applications by Effective Testing and Repair. This project aims to create advanced techniques that will enable software engineers to effectively develop quality assured and robust software systems. This project expects to generate new and innovative approaches that automate software testing and repair. The expected outcomes of this project include new knowledge of software engineering, development of an automated and cost-effective testing system with improved coverage, greater bug detection and repair, and faster testing protocols. This should provide significant benefits to software users by providing reliable and user-friendly systems and to software companies to position Australia as a global leader in software development and technological advancement.Read moreRead less
Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100035
Funder
Australian Research Council
Funding Amount
$3,009,457.00
Summary
Human-centric Model-driven Software Engineering. This project aims to find fundamentally new ways to capture and use human-centric software requirements during model-driven software engineering and verifying that systems meet these requirements. There are major issues with misaligned software applications in terms of accessibility, usability, emotions, personality, age, gender, and culture. This project aims to address these through new conceptual foundations and modelling techniques for their s ....Human-centric Model-driven Software Engineering. This project aims to find fundamentally new ways to capture and use human-centric software requirements during model-driven software engineering and verifying that systems meet these requirements. There are major issues with misaligned software applications in terms of accessibility, usability, emotions, personality, age, gender, and culture. This project aims to address these through new conceptual foundations and modelling techniques for their support during software engineering. The intended outcomes are enhanced theory, models, tools and capability for next-generation software engineering with these critical elements. Significant benefits are expected to include greatly improved software quality, developer productivity and cost savings.Read moreRead less
Scalable Stream Processing in Hybrid Edge-Cloud Infrastructures. This project aims to develop a new computational paradigm to ensure low-latency services for streaming applications across heterogeneous Edge devices while satisfying high-throughput and scalability requirements. This project is of high significance for generating new knowledge in the area of real-time streaming using innovative algorithms that overcome the limitations of remote Cloud and distributed Edge computing. Expected outcom ....Scalable Stream Processing in Hybrid Edge-Cloud Infrastructures. This project aims to develop a new computational paradigm to ensure low-latency services for streaming applications across heterogeneous Edge devices while satisfying high-throughput and scalability requirements. This project is of high significance for generating new knowledge in the area of real-time streaming using innovative algorithms that overcome the limitations of remote Cloud and distributed Edge computing. Expected outcomes include novel programming abstractions, performance models, and control mechanisms to address complex problems for incremental and iterative computations in hybrid Edge-Cloud infrastructures. This should provide significant benefits, one of which is the optimised utilisation of limited computing resources.Read moreRead less
Values-oriented Defect Fixing for Mobile Software Applications. This project aims to address critical problems with mobile applications that exhibit human values-based defects, by advancing our understanding, detection and fixing of such defects. Many mobile apps do not operate according to the essential values of their human users - e.g. inclusivity, accessibility, privacy, ethical behaviour, due care, emotions, etc - making them ineffective, underused, unfit for purpose or even dangerous. Exp ....Values-oriented Defect Fixing for Mobile Software Applications. This project aims to address critical problems with mobile applications that exhibit human values-based defects, by advancing our understanding, detection and fixing of such defects. Many mobile apps do not operate according to the essential values of their human users - e.g. inclusivity, accessibility, privacy, ethical behaviour, due care, emotions, etc - making them ineffective, underused, unfit for purpose or even dangerous. Expected outcomes include new theories, techniques and prototype tools for developers and end users to detect and help fix values-based defects in mobile apps. Benefits include better, safer mobile apps for people and organisations and improved app developer productivity and competitiveness.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101057
Funder
Australian Research Council
Funding Amount
$424,140.00
Summary
Practical Automated Software Bug Fixing via Syntactic and Semantic Analyses. This proposal aims to advance the practical adoption of automated software bug repair, which has recently been adopted by industry, e.g., Facebook. It will produce novel methods that use mining software repositories, program analysis, and human-guided search to help automated repair to scale and be accurate. Expected outcomes include a publicly available automated bug repair framework. This project will help the softwar ....Practical Automated Software Bug Fixing via Syntactic and Semantic Analyses. This proposal aims to advance the practical adoption of automated software bug repair, which has recently been adopted by industry, e.g., Facebook. It will produce novel methods that use mining software repositories, program analysis, and human-guided search to help automated repair to scale and be accurate. Expected outcomes include a publicly available automated bug repair framework. This project will help the software industry deliver to users high quality software with improved reliability and safety, and increase education quality for students learning to code via automated feedback generation.Read moreRead less
Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramat ....Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramatically benefit Australian people and government, especially for the Australian ICT industry for commercializing the research outputs. Read moreRead less