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| 2. |
- Laaber, C., et al.
(author)
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Applying test case prioritization to software microbenchmarks
- 2021
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In: Empirical Software Engineering. - : Springer Science and Business Media LLC. - 1382-3256 .- 1573-7616. ; 26:6
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Journal article (peer-reviewed)abstract
- Regression testing comprises techniques which are applied during software evolution to uncover faults effectively and efficiently. While regression testing is widely studied for functional tests, performance regression testing, e.g., with software microbenchmarks, is hardly investigated. Applying test case prioritization (TCP), a regression testing technique, to software microbenchmarks may help capturing large performance regressions sooner upon new versions. This may especially be beneficial for microbenchmark suites, because they take considerably longer to execute than unit test suites. However, it is unclear whether traditional unit testing TCP techniques work equally well for software microbenchmarks. In this paper, we empirically study coverage-based TCP techniques, employing total and additional greedy strategies, applied to software microbenchmarks along multiple parameterization dimensions, leading to 54 unique technique instantiations. We find that TCP techniques have a mean APFD-P (average percentage of fault-detection on performance) effectiveness between 0.54 and 0.71 and are able to capture the three largest performance changes after executing 29% to 66% of the whole microbenchmark suite. Our efficiency analysis reveals that the runtime overhead of TCP varies considerably depending on the exact parameterization. The most effective technique has an overhead of 11% of the total microbenchmark suite execution time, making TCP a viable option for performance regression testing. The results demonstrate that the total strategy is superior to the additional strategy. Finally, dynamic-coverage techniques should be favored over static-coverage techniques due to their acceptable analysis overhead; however, in settings where the time for prioritzation is limited, static-coverage techniques provide an attractive alternative.
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| 3. |
- Pir Muhammad, Amna, 1990
(author)
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Managing Human Factors and Requirements in Agile Development of Automated Vehicles: An Exploration
- 2022
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Licentiate thesis (other academic/artistic)abstract
- Context: Automated Vehicle (AV) technology has evolved significantly in complexity and impact; it is expected to ultimately change urban transporta- tion. However, research shows that vehicle automation can only live up to this expectation if it is defined with human capabilities and limitations in mind. Therefore, it is necessary to bring human factors knowledge to AV developers. Objective: This thesis aims to empirically study how we can effectively bring the required human factors knowledge into large-scale agile AV develop- ment. The research goals are 1) to explore requirements engineering and human factors in agile AV development, 2) to investigate the problems of requirements engineering, human factors, and agile way of working in AV development, and 3) to demonstrate initial solutions to existing problems in agile AV development. Method: We conducted this research in close collaboration with industry, using different empirical methodologies to collect data—including interviews, workshops, and document analysis. To gain in-depth insights, we did a qualita- tive exploratory study to investigate the problem and used a design science approach to develop initial solution in several iterations. Findings and Conclusions: We found that applying human factors knowledge effectively is one of the key problem areas that need to be solved in agile development of artificial intelligence (AI)-intense systems. This motivated us to do an in-depth interview study on how to manage human factors knowl- edge during AV development. From our data, we derived a working definition of human factors for AV development, discovered the relevant properties of agile and human factors, and defined implications for agile ways of working, managing human factors knowledge, and managing requirements. The design science approach allowed us to identify challenges related to agile requirements engineering in three case companies in iterations. Based on these three case studies, we developed a solution strategy to resolve the RE challenges in agile AV development. Moreover, we derived building blocks and described guide- lines for the creation of a requirements strategy, which should describe how requirements are structured, how work is organized, and how RE is integrated into the agile work and feature flow. Future Outlook: In future work, I plan to define a concrete requirement strategy for human factors knowledge in large-scale agile AV development. It could help establishing clear communication channels and practices for incorporating explicit human factors knowledge into AI-based large-scale agile AV development.
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| 4. |
- Blanch, Krister, 1991
(author)
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Beyond-application datasets and automated fair benchmarking
- 2023
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Licentiate thesis (other academic/artistic)abstract
- Beyond-application perception datasets are generalised datasets that emphasise the fundamental components of good machine perception data. When analysing the history of perception datatsets, notable trends suggest that design of the dataset typically aligns with an application goal. Instead of focusing on a specific application, beyond-application datasets instead look at capturing high-quality, high-volume data from a highly kinematic environment, for the purpose of aiding algorithm development and testing in general. Algorithm benchmarking is a cornerstone of autonomous systems development, and allows developers to demonstrate their results in a comparative manner. However, most benchmarking systems allow developers to use their own hardware or select favourable data. There is also little focus on run time performance and consistency, with benchmarking systems instead showcasing algorithm accuracy. By combining both beyond-application dataset generation and methods for fair benchmarking, there is also the dilemma of how to provide the dataset to developers for this benchmarking, as the result of a high-volume, high-quality dataset generation is a significant increase in dataset size when compared to traditional perception datasets. This thesis presents the first results of attempting the creation of such a dataset. The dataset was built using a maritime platform, selected due to the highly dynamic environment presented on water. The design and initial testing of this platform is detailed, as well as as methods of sensor validation. Continuing, the thesis then presents a method of fair benchmarking, by utilising remote containerisation in a way that allows developers to present their software to the dataset, instead of having to first locally store a copy. To test this dataset and automatic online benchmarking, a number of reference algorithms were required for initial results. Three algorithms were built, using the data from three different sensors captured on the maritime platform. Each algorithm calculates vessel odometry, and the automatic benchmarking system was utilised to show the accuracy and run-time performance of these algorithms. It was found that the containerised approach alleviated data management concerns, prevented inflated accuracy results, and demonstrated precisely how computationally intensive each algorithm was.
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| 5. |
- Lv, Zhihan, Dr. 1984-, et al.
(author)
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Deep Learning for Security in Digital Twins of Cooperative Intelligent Transportation Systems
- 2022
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In: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers (IEEE). - 1524-9050 .- 1558-0016. ; 23:9, s. 16666-16675
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Journal article (peer-reviewed)abstract
- The purpose is to solve the security problems of the Cooperative Intelligent Transportation System (CITS) Digital Twins (DTs) in the Deep Learning (DL) environment. The DL algorithm is improved; the Convolutional Neural Network (CNN) is combined with Support Vector Regression (SVR); the DTs technology is introduced. Eventually, a CITS DTs model is constructed based on CNN-SVR, whose security performance and effect are analyzed through simulation experiments. Compared with other algorithms, the security prediction accuracy of the proposed algorithm reaches 90.43%. Besides, the proposed algorithm outperforms other algorithms regarding Precision, Recall, and F1. The data transmission performances of the proposed algorithm and other algorithms are compared. The proposed algorithm can ensure that emergency messages can be responded to in time, with a delay of less than 1.8s. Meanwhile, it can better adapt to the road environment, maintain high data transmission speed, and provide reasonable path planning for vehicles so that vehicles can reach their destinations faster. The impacts of different factors on the transportation network are analyzed further. Results suggest that under path guidance, as the Market Penetration Rate (MPR), Following Rate (FR), and Congestion Level (CL) increase, the guidance strategy's effects become more apparent. When MPR ranges between 40% similar to 80% and the congestion is level III, the ATT decreases the fastest, and the improvement effect of the guidance strategy is more apparent. The proposed DL algorithm model can lower the data transmission delay of the system, increase the prediction accuracy, and reasonably changes the paths to suppress the sprawl of traffic congestions, providing an experimental reference for developing and improving urban transportation.
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| 7. |
- Ali, Muhaddisa Barat, 1986
(author)
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Deep Learning Methods for Classification of Gliomas and Their Molecular Subtypes, From Central Learning to Federated Learning
- 2023
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Doctoral thesis (other academic/artistic)abstract
- The most common type of brain cancer in adults are gliomas. Under the updated 2016 World Health Organization (WHO) tumor classification in central nervous system (CNS), identification of molecular subtypes of gliomas is important. For low grade gliomas (LGGs), prediction of molecular subtypes by observing magnetic resonance imaging (MRI) scans might be difficult without taking biopsy. With the development of machine learning (ML) methods such as deep learning (DL), molecular based classification methods have shown promising results from MRI scans that may assist clinicians for prognosis and deciding on a treatment strategy. However, DL requires large amount of training datasets with tumor class labels and tumor boundary annotations. Manual annotation of tumor boundary is a time consuming and expensive process. The thesis is based on the work developed in five papers on gliomas and their molecular subtypes. We propose novel methods that provide improved performance. The proposed methods consist of a multi-stream convolutional autoencoder (CAE)-based classifier, a deep convolutional generative adversarial network (DCGAN) to enlarge the training dataset, a CycleGAN to handle domain shift, a novel federated learning (FL) scheme to allow local client-based training with dataset protection, and employing bounding boxes to MRIs when tumor boundary annotations are not available. Experimental results showed that DCGAN generated MRIs have enlarged the original training dataset size and have improved the classification performance on test sets. CycleGAN showed good domain adaptation on multiple source datasets and improved the classification performance. The proposed FL scheme showed a slightly degraded performance as compare to that of central learning (CL) approach while protecting dataset privacy. Using tumor bounding boxes showed to be an alternative approach to tumor boundary annotation for tumor classification and segmentation, with a trade-off between a slight decrease in performance and saving time in manual marking by clinicians. The proposed methods may benefit the future research in bringing DL tools into clinical practice for assisting tumor diagnosis and help the decision making process.
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| 8. |
- Lv, Zhihan, Dr. 1984-, et al.
(author)
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5G for mobile augmented reality
- 2022
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In: International Journal of Communication Systems. - : John Wiley & Sons. - 1074-5351 .- 1099-1131. ; 35:5
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Journal article (other academic/artistic)
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| 9. |
- Lv, Zhihan, Dr. 1984-, et al.
(author)
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Editorial : 5G for Augmented Reality
- 2022
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In: Mobile Networks and Applications. - : Springer. - 1383-469X .- 1572-8153.
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Journal article (peer-reviewed)
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| 10. |
- Arshad, Hamed, 1987, et al.
(author)
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Attribute-based encryption with enforceable obligations
- 2023
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In: Journal of Cryptographic Engineering. - Heidelberg : Springer. - 2190-8508 .- 2190-8516. ; 13, s. 343-371
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Journal article (peer-reviewed)abstract
- Attribute-based encryption (ABE) is a cryptographic mechanism that provides fine-grained access control to encrypted data, which can thus be stored in, e.g., public clouds. However, ABE schemes lack the notion of obligations, which is common in attribute-based access control systems such as eXtensible Access Control Markup Language and Usage Control. Obligations are used to define and enforce extra constraints that happen before approving or denying an access request. In this paper, we propose OB-ABE, a system for extending any classical ABE with enforceable obligations. Our system architecture has as core component trusted hardware enclaves, implemented with SGX, used for enforcing obligations. We employ ProVerif to formally model OB-ABE and verify its main property called "enforceable obligations," i.e., if a message is encrypted along with an obligation, then the message can be decrypted only after enforcing the attached obligation. OB-ABE has two more properties: (i) OB-ABE is a "conservative extension" of the underlying ABE scheme, preserving its security properties; (ii) OB-ABE is "backward compatible" in the sense that any ciphertext produced by an ABE scheme can be decrypted by its extended OB-ABE version, and moreover, a ciphertext produced by an OB-ABE scheme can be decrypted by its underlying ABE scheme provided that the ciphertext does not have obligations attached. We also implement in C using Intel SGX a prototype of an OB-ABE extending the well-known ciphertext-policy ABE.
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