VLDB 2026 Research / reviewers in the wild / expert
Askar Yeltayuly Khamit
dblp:351/6853
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Automated Program Repair from Fuzzing PerspectiveabstractIn this work, we present a novel approach that connects two closely-related topics: fuzzing and automated program repair (APR). The paper is divided into two parts. In the first part, we describe the similarities between fuzzing and APR both of which can be viewed as a search problem. In the second part, we introduce a new patch-scheduling algorithm called Casino, which is designed from a fuzzing perspective to enhance search efficiency. Our experiments demonstrate that Casino outperforms existing algorithms. We also promote open science by sharing SimAPR, a simulation tool that can be used to evaluate new patch-scheduling algorithms. Seungheon Han, Askar Yeltayuly Khamit, Jooyong Yi |
ISSTA | 3 |
| 2023 | Leakpair: Proactive Repairing of Memory Leaks in Single Page Web ApplicationsabstractModern web applications often resort to application development frameworks such as React, Vue.js, and Angular. While the frameworks facilitate the development of web applications with several useful components, they are inevitably vulnerable to unmanaged memory consumption since the frameworks often produce Single Page Applications (SPAs). Web applications can be alive for hours and days with behavior loops, in such cases, even a single memory leak in a SPA app can cause performance degradation on the client side. However, recent debugging techniques for web applications still focus on memory leak detection, which requires manual tasks and produces imprecise results. We propose Leakpair,a technique to repair memory leaks in single page applications. Given the insight that memory leaks are mostly non-functional bugs and fixing them might not change the behavior of an application, the technique is designed to proactively generate patches to fix memory leaks, without leak detection, which is often heavy and tedious. To generate effective patches, Leakpairfollows the idea of pattern-based program repair since the automated repair strategy shows successful results in many recent studies. We evaluate the technique on more than 20 open-source projects without using explicit leak detection. The patches generated by our technique are also submitted to the projects as pull requests. The results show that Leakpaircan generate effective patches to reduce memory consumption that are acceptable to developers. In addition, we execute the test suites given by the projects after applying the patches, and it turns out that the patches do not cause any functionality breakage; this might imply that Leakpaircan generate non-intrusive patches for memory leaks. Arooba Shahoor, Askar Yeltayuly Khamit, Jooyong Yi, Dongsun Kim 0001 |
ASE | 2 |