Zobrazeno 1 - 10
of 377
pro vyhledávání: '"Mesbah, Ali"'
End-to-end web testing is challenging due to the need to explore diverse web application functionalities. Current state-of-the-art methods, such as WebCanvas, are not designed for broad functionality exploration; they rely on specific, detailed task
Externí odkaz:
http://arxiv.org/abs/2409.10741
Deep neural networks are increasingly used as an effective way to represent control policies in a wide-range of learning-based control methods. For continuous-time optimal control problems (OCPs), which are central to many decision-making tasks, cont
Externí odkaz:
http://arxiv.org/abs/2409.00393
Autor:
Gu, Sijia, Mesbah, Ali
The Multi-Criteria Test Suite Minimization (MCTSM) problem aims to refine test suites by removing redundant test cases, guided by adequacy criteria such as code coverage or fault detection capability. However, current techniques either exhibit a high
Externí odkaz:
http://arxiv.org/abs/2408.13517
Dockerfile flakiness, characterized by inconsistent build behavior without Dockerfile or project source code changes, poses significant challenges in Continuous Integration and Delivery (CI/CD) pipelines. This issue can lead to unreliable deployments
Externí odkaz:
http://arxiv.org/abs/2408.05379
End-to-end (E2E) testing is essential for ensuring web application quality. However, manual test creation is time-consuming and current test generation techniques produce random tests. In this paper, we present AUTOE2E, a novel approach that leverage
Externí odkaz:
http://arxiv.org/abs/2408.01894
Large language models have made substantial progress in addressing diverse code-related tasks. However, their adoption is hindered by inconsistencies in generating output due to the lack of real-world, domain-specific information, such as for intra-r
Externí odkaz:
http://arxiv.org/abs/2405.04600
Industrial applications of plasma have significantly increased beyond semiconductor manufacturing in recent years. This necessitates training a skilled workforce in plasma science and technology. However, an essential challenge to this end stems from
Externí odkaz:
http://arxiv.org/abs/2405.02510
Designing predictive controllers towards optimal closed-loop performance while maintaining safety and stability is challenging. This work explores closed-loop learning for predictive control parameters under imperfect information while considering cl
Externí odkaz:
http://arxiv.org/abs/2404.12187
Autor:
Gu, Sijia, Mesbah, Ali
For large software applications, running the whole test suite after each code change is time- and resource-intensive. Regression test selection techniques aim at reducing test execution time by selecting only the tests that are affected by code chang
Externí odkaz:
http://arxiv.org/abs/2403.16001
Automated test generation for web forms has been a longstanding challenge, exacerbated by the intrinsic human-centric design of forms and their complex, device-agnostic structures. We introduce an innovative approach, called FormNexus, for automated
Externí odkaz:
http://arxiv.org/abs/2402.00950