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Field of Research : Software Engineering
Scheme : Discovery Early Career Researcher Award
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  • Researchers (13)
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  • Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200100016

    Funder
    Australian Research Council
    Funding Amount
    $351,798.00
    Summary
    Enabling Compatible and Secure Mobile Apps via Automated Program Repair. This project aims to ensure everyone in Australia and the world can reliably utilise compatible and secure mobile apps on their smart devices, by inventing a novel approach to automatically fix compatibility and security issues during app development and installation. The project expects to generate new knowledge, tools and methods to support efficient mobile app fix through mining the best practices from the mobile ecosyst .... Enabling Compatible and Secure Mobile Apps via Automated Program Repair. This project aims to ensure everyone in Australia and the world can reliably utilise compatible and secure mobile apps on their smart devices, by inventing a novel approach to automatically fix compatibility and security issues during app development and installation. The project expects to generate new knowledge, tools and methods to support efficient mobile app fix through mining the best practices from the mobile ecosystem. Expected outcomes include better support for app developers to build mobile apps that will maximise the potential of the mobile ecosystem for Australian businesses. This should provide significant benefits, such as enhanced productivity for the software industry and better mobile app experience and safety for users.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE160100850

    Funder
    Australian Research Council
    Funding Amount
    $330,000.00
    Summary
    Dynamic adaptive software configuration. The aim of this project is to use computational intelligence in software engineering processes to achieve self-optimising products. Many mobile device users bemoan inadequate battery life, and device size is largely determined by the battery. In addition, information and communications technology uses six per cent of the global electricity production. The expected outputs of this project will be packages of optimisation components that software engineers .... Dynamic adaptive software configuration. The aim of this project is to use computational intelligence in software engineering processes to achieve self-optimising products. Many mobile device users bemoan inadequate battery life, and device size is largely determined by the battery. In addition, information and communications technology uses six per cent of the global electricity production. The expected outputs of this project will be packages of optimisation components that software engineers can incorporate into next generation products: the products analyse their collected usage data, perform what-if analyses, and optimise their configurations accordingly for the next usage period. Hence, the products may respond faster, be more reliable, and consume less energy.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE180100153

    Funder
    Australian Research Council
    Funding Amount
    $361,446.00
    Summary
    Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to impr .... Automatically summarising and measuring software development activity. This project aims to create technologies for automatically repackaging, interpreting, and aggregating software development activity. The project will devise new natural-language summarisation approaches and productivity metrics that use all data available in a software repository. This is likely to lead to knowledge and tools that allow organisations to quickly integrate new developers into existing software projects, to improve project awareness, and to increase productivity goals. The outcomes would include a comprehensive decision and awareness support system for software projects, based on automating the creation and continual updating of developer activity summaries and measures.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE170101081

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t .... Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200100941

    Funder
    Australian Research Council
    Funding Amount
    $392,778.00
    Summary
    Practical and Explainable Analytics to Prevent Future Software Defects. This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects bef .... Practical and Explainable Analytics to Prevent Future Software Defects. This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects before they impact end users. This should provide significant benefits including accelerating the productivity of the software industry while preventing software defects in many critical domains including smart city and e-health applications.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE200100021

    Funder
    Australian Research Council
    Funding Amount
    $413,665.00
    Summary
    An Intelligent Programmer’s Assistant Using Data Mining. This project aims to advance the important practice of pair programming in software engineering via software repository mining and create automated support tools. This project expects to use innovative techniques combining artificial intelligence, programming analysis and software analytics, to help software developers review code, fix bugs and implement new features. Expected outcomes of this project include an intelligent programmer’s as .... An Intelligent Programmer’s Assistant Using Data Mining. This project aims to advance the important practice of pair programming in software engineering via software repository mining and create automated support tools. This project expects to use innovative techniques combining artificial intelligence, programming analysis and software analytics, to help software developers review code, fix bugs and implement new features. Expected outcomes of this project include an intelligent programmer’s assistant, consisting of a set of automated tools, covering software development, testing and maintenance. This should provide significant benefits to the Australian software development industry by improving developers’ productivity and reduce overall project costs.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE140100017

    Funder
    Australian Research Council
    Funding Amount
    $394,800.00
    Summary
    Adaptive Optimisation of Complex Combinatorial Problems. One of the most common problems faced by planners, whether in industry or government, is optimisation, finding the optimal solution to a problem. Even a one per cent improvement in a solution can make a difference of millions of dollars in some cases. Traditionally optimisation problems are solved by analytic means or exact optimisation methods. Today, however, many optimisation problems involve complex combinatorial systems that make such .... Adaptive Optimisation of Complex Combinatorial Problems. One of the most common problems faced by planners, whether in industry or government, is optimisation, finding the optimal solution to a problem. Even a one per cent improvement in a solution can make a difference of millions of dollars in some cases. Traditionally optimisation problems are solved by analytic means or exact optimisation methods. Today, however, many optimisation problems involve complex combinatorial systems that make such traditional approaches unsuitable or intractable. This project aims to assist researchers and practitioners in solving complex combinatorial optimisation problems by adapting the optimisation strategy to the problem being solved, based on problem features such as search space difficulty.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE190100046

    Funder
    Australian Research Council
    Funding Amount
    $387,000.00
    Summary
    Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established .... Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established statistical framework utilised in ecology research to provide fundamental insights to boosting the efficiency of software vulnerability discovery, and on the trade-off between investing more resources and gaining better cyber security guarantees. As our reliance on new technologies is ever growing, this project equips Australia to curb cyber crime cost-effectively.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE180100245

    Funder
    Australian Research Council
    Funding Amount
    $386,500.00
    Summary
    Achieving millimetre geodesy with space tie satellites. This project aims to implement the completely new concept of observing artificial satellites with radio telescopes, realising a so-called space tie. Understanding Earth’s changing shape requires measurements with a stability of 0.1 mm per year. Today, geodetic earth observations are used to realise reference points with a precision of five to ten times larger. Using the unique Australian ground infrastructure, current observational and oper .... Achieving millimetre geodesy with space tie satellites. This project aims to implement the completely new concept of observing artificial satellites with radio telescopes, realising a so-called space tie. Understanding Earth’s changing shape requires measurements with a stability of 0.1 mm per year. Today, geodetic earth observations are used to realise reference points with a precision of five to ten times larger. Using the unique Australian ground infrastructure, current observational and operational problems shall be overcome. The intended outcome is to improve the coordinate system of the Earth, which is the basis for a better understanding of Earth serving to fulfil scientific as well as societal demands.
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    Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE210101091

    Funder
    Australian Research Council
    Funding Amount
    $402,160.00
    Summary
    Data-Driven Code Reviews for Cost-Effective Software Quality Assurance. This DECRA project aims to create advanced techniques that will enable software engineers to effectively assure the highest quality of software systems with minimal cost through data-driven recommendations. The current standard practices in software quality assurance involve the manual and tedious process of code review, which can lead to high costs and cause severe delays in software development. The expected outcomes of th .... Data-Driven Code Reviews for Cost-Effective Software Quality Assurance. This DECRA project aims to create advanced techniques that will enable software engineers to effectively assure the highest quality of software systems with minimal cost through data-driven recommendations. The current standard practices in software quality assurance involve the manual and tedious process of code review, which can lead to high costs and cause severe delays in software development. The expected outcomes of this project include new theories, techniques, and an automated system that provides insightful feedback, suitable reviewer recommendations, and fine-grained effort prioritisation. Significant benefits are expected to improve the production of Australia's software and the quality of safety-critical software systems.
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