Search

There have been recent efforts that combine seemingly disparate methods, extremum seeking (ES) optimization and partial differential equation (PDE) backstepping, to address the problem of model-free optimization with PDE actuator dynamics. In contrast to prior PDE-compensating ES designs, which only guarantee local stability around the extremum, we introduce unbiased ES that compensates for delay and diffusion PDE dynamics while ensuring exponential and unbiased convergence to the optimum. Our method leverages exponentially decaying/growing signals within the modulation/demodulation stages and carefully selected design parameters. The stability analysis of our designs relies on a state transformation, infinite-dimensional averaging, local exponential stability of the averaged system, local stability of the transformed system, and local exponential stability of the original system. Numerical simulations are presented to demonstrate the efficacy of the developed designs., Comment: Submitted to the 63rd IEEE Conference on Decision and Control (CDC), 2024

Our recently developed "unbiased" extremum seeking (uES) algorithms ensure perfect convergence to the optimum at a user-assigned exponential rate or, more powerfully, within a user-prescribed time. Unlike classical approach, these algorithms use time-varying adaptation and controller gains, along with constant or time-varying probing frequencies (chirp signals). This paper advances our earlier uES designs from strongly convex maps with static optima to a broader class of convex cost functions with time-varying optima diverging at arbitrary rates, even in finite time. This advancement first motivates the use of Lie bracket averaging instead of classical averaging due to the average system system, which doesn't necessarily need to be exponentially convergent, and the existence of non-periodic time-varying parameters; second, it necessitates the formulation of non-trivial and key feasibility conditions for the choice of time-varying design parameters and their decay/growth rates in relation to the convexity of the map and the divergence rate of optima. These conditions indicate that, for constant-frequency probing, the user-defined asymptotic rate of unbiasing is limited by the convexity of the map. However, this rate can be made arbitrarily fast (including asymptotic, exponential, and prescribed time) using chirpy probing, which requires sufficiently rapid frequency and adaptation growth to enable tracking of faster-diverging optima. In addition to numerical simulations of the designs, we experimentally test the feasibility of exponential uES for tuning the angular velocity of a unicycle to seek a static light source., Comment: Submitted to Transactions on Automatic Control

This paper introduces extremum seeking (ES) algorithms designed to achieve perfect tracking of arbitrary time-varying extremum. In contrast to classical ES approaches that employ constant frequencies and controller gains, our algorithms leverage time-varying parameters, growing either asymptotically or exponentially, to achieve desired convergence behaviors. Our stability analysis involves state transformation, time-dilation transformation, and Lie bracket averaging. The state transformation is based on the multiplication of the input state by asymptotic or exponential growth functions. The time transformation enables tracking of the extremum as it gradually converges to a constant value when viewed in the dilated time domain. Finally, Lie bracket averaging is applied to the transformed system, ensuring practical uniform stability in the dilated time domain as well as asymptotic or exponential stability of the original system in the original time domain. We validate the feasibility of these designs through numerical simulations., Comment: Accepted to the 2024 American Control Conference (ACC)

We present multivariable extremum seeking (ES) designs that achieve unbiased convergence to the optimum. Two designs are introduced: one with exponential unbiased convergence (unbiased extremum seeker, uES) and the other with user-assignable prescribed-time unbiased convergence (unbiased PT extremum seeker, uPT-ES). In contrast to the conventional ES, which uses persistent sinusoids and results in steady-state oscillations around the optimum, the exponential uES employs an exponentially decaying amplitude in the perturbation signal (for achieving convergence) and an exponentially growing demodulation signal (for making the convergence unbiased). The achievement of unbiased convergence also entails employing an adaptation gain that is sufficiently large in relation to the decay rate of the perturbation amplitude. Stated concisely, the bias is eliminated by having the learning process outpace the waning of the perturbation. The other algorithm, uPT-ES, employs prescribed-time convergent/blow-up functions in place of constant amplitudes of sinusoids, and it also replaces constant-frequency sinusoids with chirp signals whose frequency grows over time. Among the convergence results in the ES literature, uPT-ES may be the strongest yet in terms of the convergence rate (prescribed-time) and accuracy (unbiased). To enhance the robustness of uES to a time-varying optimum, exponential functions are modified to keep oscillations at steady state. Stability analysis of the designs is based on a state transformation, averaging, local exponential/PT stability of the averaged system, local stability of the transformed system, and local exponential/PT stability of the original system. For numerical implementation of the developed ES schemes and comparison with previous ES designs, the problem of source seeking by a two-dimensional velocity-actuated point mass is considered., Comment: 16 pages, 7 figures

Timing attacks are considered one of the most damaging side-channel attacks. These attacks exploit timing fluctuations caused by certain operations to disclose confidential information to an attacker. For instance, in asymmetric encryption, operations such as multiplication and division can cause time-varying execution times that can be ill-treated to obtain an encryption key. Whilst several efforts have been devoted to exploring the various aspects of timing attacks, particularly in cryptography, little attention has been paid to empirically studying the timing attack-related vulnerabilities in non-cryptographic software. By inspecting these software vulnerabilities, this study aims to gain an evidence-based understanding of weaknesses in non-cryptographic software that may help timing attacks succeed. We used qualitative and quantitative research approaches to systematically study the timing attack-related vulnerabilities reported in the National Vulnerability Database (NVD) from March 2003 to December 2022. Our analysis was focused on the modifications made to the code for patching the identified vulnerabilities. We found that a majority of the timing attack-related vulnerabilities were introduced due to not following known secure coding practices. The findings of this study are expected to help the software security community gain evidence-based information about the nature and causes of the vulnerabilities related to timing attacks.

In previous work, we deployed IssueTAG, which uses the texts present in the one-line summary and the description fields of the issue reports to automatically assign them to the stakeholders, who are responsible for resolving the reported issues. Since its deployment on January 12, 2018 at Softtech, i.e., the software subsidiary of the largest private bank in Turkey, IssueTAG has made a total of 301,752 assignments (as of November 2021). One observation we make is that a large fraction of the issue reports submitted to Softtech has screenshot attachments and, in the presence of such attachments, the reports often convey less information in their one-line summary and the description fields, which tends to reduce the assignment accuracy. In this work, we use the screenshot attachments as an additional source of information to further improve the assignment accuracy, which (to the best of our knowledge) has not been studied before in this context. In particular, we develop a number of multi-source (using both the issue reports and the screenshot attachments) and single-source assignment models (using either the issue reports or the screenshot attachments) and empirically evaluate them on real issue reports. In the experiments, compared to the currently deployed single-source model in the field, the best multi-source model developed in this work, significantly (both in the practical and statistical sense) improved the assignment accuracy for the issue reports with screenshot attachments from 0.843 to 0.858 at acceptable overhead costs, a result strongly supporting our basic hypothesis., Comment: Preprint for EMSE journal

Softtech, being a subsidiary of the largest private bank in Turkey, called IsBank, receives an average of 350 issue reports from the field every day. Manually assigning the reported issues to the software development teams is costly and cumbersome. We automate the issue assignments using data mining approaches and share our experience gained by deploying the resulting system at Softtech/IsBank. Automated issue assignment has been studied in the literature. However, most of these works report the results obtained on open source projects and the remaining few, although they use commercial, closed source projects, carry out the assignments in a retrospective manner. We, on the other hand, deploy the proposed approach, which has been making all the assignments since Jan 12, 2018. This presents us with an unprecedented opportunity to observe the practical effects of automated issue assignment in the field and to carry out user studies, which have not been done before in this context. We observe that it is not just about deploying a system for automated issue assignment, but also about designing/changing the assignment process around the system; the accuracy of the assignments does not have to be higher than that of manual assignments in order for the system to be useful; deploying such a system requires the development of additional functionalities, such as detecting deteriorations in assignment accuracies in an online manner and creating human-readable explanations for the assignments; stakeholders do not necessarily resist change; and gradual transition can help stakeholders build confidence., Comment: Preprint for EMSE journal

Combinatorial interaction testing (CIT) is a useful testing technique to address the interaction of input parameters in software systems. In many applications, the technique has been used as a systematic sampling technique to sample the enormous possibilities of test cases. In the last decade, most of the research activities focused on the generation of CIT test suites as it is a computationally complex problem. Although promising, less effort has been paid for the application of CIT. In general, to apply the CIT, practitioners must identify the input parameters for the Software-under-test (SUT), feed these parameters to the CIT tool to generate the test suite, and then run those tests on the application with some pass and fail criteria for verification. Using this approach, CIT is used as a black-box testing technique without knowing the effect of the internal code. Although useful, practically, not all the parameters having the same impact on the SUT. This paper introduces a different approach to use the CIT as a gray-box testing technique by considering the internal code structure of the SUT to know the impact of each input parameter and thus use this impact in the test generation stage. We applied our approach to five reliable case studies. The results showed that this approach would help to detect new faults as compared to the equal impact parameter approach., Comment: 28 pages

We believe that we can exploit the benefits of combinatorial interaction testing (CIT) on many "non-traditional" combinatorial spaces using many "non-traditional" coverage criteria. However, this requires truly flexible CIT approaches. To this end, we introduce Unified Combinatorial Interaction Testing (U-CIT), which enables practitioners to define their own combinatorial spaces and coverage criteria for testing, and present a unified construction approach to compute specific instances of U-CIT objects. We, furthermore, argue that most (if not all) existing CIT objects are a special case of U-CIT and demonstrate the flexibility of U-CIT on a simple, yet realistic scenario., Comment: 5 pages, 1 algorithm, 1 figure