arXiv subjects

Qiao Huang

Publications and source records attributed to Qiao Huang.

22 records · Page 2Linked to original sources

arXiv2021

An Exploratory Study on the Introduction and Removal of Different Types of Technical Debt

To complete tasks faster, developers often have to sacrifice the quality of the software. Such compromised practice results in the increasing burden to developers in future development. The metaphor, technical debt, describes such practice. Prior research has illustrated the negative impact of technical debt, and many researchers investigated how developers deal with a certain type of technical debt. However, few studies focused on the removal of different types of technical debt in practice. To fill this gap, we use the introduction and removal of different types of self-admitted technical debt (i.e., SATD) in 7 deep learning frameworks as an example. This is because deep learning frameworks are some of the most important software systems today due to their prevalent use in life-impacting deep learning applications. Moreover, the field of the development of different deep learning frameworks is the same, which enables us to find common behaviors on the removal of different types of technical debt across projects. By mining the file history of these frameworks, we find that design debt is introduced the most along the development process. As for the removal of technical debt, we find that requirement debt is removed the most, and design debt is removed the fastest. Most of test debt, design debt, and requirement debt are removed by the developers who introduced them. Based on the introduction and removal of different types of technical debt, we discuss the evolution of the frequencies of different types of technical debt to depict the unresolved sub-optimal trade-offs or decisions that are confronted by developers along the development process. We also discuss the removal patterns of different types of technical debt, highlight future research directions, and provide recommendations for practitioners.

cs.SE↗

arXiv2020

Rolling with Random Slipping and Twisting: A Large Deviation Point of View

We study a rolling model from the perspective of probability. More precisely, we consider a Riemannian manifold rolling against Euclidean space, where the rolling is coupled with random slipping and twisting. The system is modelled by a stochastic differential equation of Stratonovich-type driven by semimartingales, on the orthonormal frame bundle. The stability of the system is examined via large deviations. We prove the large deviation principles for the projection curves on the base manifold and their horizontal lifts respectively, provided that the large deviation holds for the random Euclidean curves as semimartingales. The large deviation results for the case of compact manifolds and two special cases of noncompact manifolds are established.

math.PR↗

arXiv2020

Numerical analysis and applications of Fokker-Planck equations for stochastic dynamical systems with multiplicative $α$-stable noises

The Fokker-Planck equations (FPEs) for stochastic systems driven by additive symmetric $α$-stable noises may not adequately describe the time evolution for the probability densities of solution paths in some practical applications, such as hydrodynamical systems, porous media, and composite materials. As a continuation of previous works on additive case, the FPEs for stochastic dynamical systems with multiplicative symmetric $α$-stable noises are derived by the adjoint operator method, which satisfy the nonlocal partial differential equations. A finite difference method for solving the nonlocal Fokker-Planck equation (FPE) is constructed, which is shown to satisfy the discrete maximum principle and to be convergent. Moreover, an example is given to illustrate this method. For asymmetric case, general finite difference schemes are proposed, and some analyses of the corresponding numerical schemes are given. Furthermore, the corresponding result is successfully applied to the nonlinear filtering problem.

math.DS↗

arXiv2018

Maximum principles for nonlocal parabolic Waldenfels operators

As a class of Lévy type Markov generators, nonlocal Waldenfels operators appear naturally in the context of investigating stochastic dynamics under Lévy fluctuations and constructing Markov processes with boundary conditions (in particular the construction with jumps). This work is devoted to prove the weak and strong maximum principles for `parabolic' equations with nonlocal Waldenfels operators. Applications in stochastic differential equations with $α$-stable Lévy processes are presented to illustrate the maximum principles.

math.AP↗