Software: Practice and Experience最新文献_第10页

Grammar‐based fuzzing of data integration parsers in computational materials science 计算材料科学中基于语法的数据集成解析器模糊化

Software: Practice and Experience Pub Date : 2023-09-19 DOI: 10.1002/spe.3266

Sebastian Müller, Jan Arne Sparka, Martin Kuban, Claudia Draxl, Lars Grunske

{"title":"Grammar‐based fuzzing of data integration parsers in computational materials science","authors":"Sebastian Müller, Jan Arne Sparka, Martin Kuban, Claudia Draxl, Lars Grunske","doi":"10.1002/spe.3266","DOIUrl":"https://doi.org/10.1002/spe.3266","url":null,"abstract":"Computational materials science (CMS) focuses on in silico experiments to compute the properties of known and novel materials, where many software packages are used in the community. The NOMAD Laboratory (Draxl C, Scheffler) offers to store the input and output files in its FAIR data repository. Since the file formats of these software packages are non‐standardized, parsers are used to provide the results in a normalized format.The main goal of this article is to report experience and findings of using grammar‐based fuzzing on these parsers.We have constructed an input grammar for four common software packages in the CMS domain and performed an experimental evaluation on the capabilities of grammar‐based fuzzing to detect failures in the Novel Materials Discovery (NOMAD) parsers.With our approach, we were able to identify three unique critical bugs concerning service availability, as well as several additional syntactic, semantic, logical, and downstream bugs in the investigated NOMAD parsers. We reported all issues to the developer team prior to publication.Based on the experience gained, we can recommend grammar‐based fuzzing also for other research software packages to improve the trust level in the correctness of the produced results.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135013975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High‐performance extended actors 高性能扩展演员

Software: Practice and Experience Pub Date : 2023-09-16 DOI: 10.1002/spe.3262

Peter A. Buhr, Colby A. Parsons, Thierry Delisle, He Nan Li

引用次数: 0

Practice of Alibaba cloud on elastic resource provisioning for large‐scale microservices cluster 阿里云在大规模微服务集群弹性资源配置上的实践

Software: Practice and Experience Pub Date : 2023-09-16 DOI: 10.1002/spe.3271

Minxian Xu, Lei Yang, Yang Wang, Chengxi Gao, Linfeng Wen, Guoyao Xu, Liping Zhang, Kejiang Ye, Chengzhong Xu

{"title":"Practice of Alibaba cloud on elastic resource provisioning for large‐scale microservices cluster","authors":"Minxian Xu, Lei Yang, Yang Wang, Chengxi Gao, Linfeng Wen, Guoyao Xu, Liping Zhang, Kejiang Ye, Chengzhong Xu","doi":"10.1002/spe.3271","DOIUrl":"https://doi.org/10.1002/spe.3271","url":null,"abstract":"Summary Cloud‐native architecture is becoming increasingly crucial for today's cloud computing environments due to the need for speed and flexibility in developing applications. It utilizes microservice technology to break down traditional monolithic applications into light‐weight and self‐contained microservice components. However, as microservices grow in scale and have dynamic inter‐dependencies, they also pose new challenges in resource provisioning that cannot be fully addressed by traditional resource scheduling approaches. The various microservices with different resource demands and latency requirements can create complex calling chains, making it difficult to provide fine‐grained and accurate resource allocation to each component while maintaining the overall quality of service in the chain. Alibaba Cloud has fully embraced cloud‐native and microservice technologies to drive its key business and scenarios, including Double 11 Shopping Festival. In this work, we aim to address the research problem on how to efficiently provision resources for the growing scale of microservice platform and ensure the performance of latency‐critical microservices. To address the problem, we present in‐depth analyses of Alibaba's microservice cluster and propose optimized resource provisioning algorithms to enhance resource utilization while ensuring the latency requirement. First, we analyze the distinct features of microservices in Alibaba's cluster compared to traditional applications. Then we present Alibaba's resource capacity provisioning workflow and framework to address challenges in resource provisioning for large‐scale and latency‐critical microservice clusters. Finally, we propose enhanced resource provisioning algorithms over Alibaba's current practice by making both proactive and reactive scheduling decisions based on different workloads patterns, which can improve resource usage by 10%–15% in Alibaba's clusters, while maintaining the necessary latency for microservices.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135307141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A probabilistic modeling and evolutionary optimization approach for serverless workflow configuration 无服务器工作流配置的概率建模和进化优化方法

Software: Practice and Experience Pub Date : 2023-09-15 DOI: 10.1002/spe.3268

Weiguo Wang, Quanwang Wu, Zhiyong Zhang, Jie Zeng, Xiang Zhang, Mingqiang Zhou

{"title":"A probabilistic modeling and evolutionary optimization approach for serverless workflow configuration","authors":"Weiguo Wang, Quanwang Wu, Zhiyong Zhang, Jie Zeng, Xiang Zhang, Mingqiang Zhou","doi":"10.1002/spe.3268","DOIUrl":"https://doi.org/10.1002/spe.3268","url":null,"abstract":"Abstract Serverless computing has nowadays become a mainstream paradigm to develop cloud‐native applications owing to its high scalability, ease of usage and cost‐effectiveness. Nevertheless, because of its poor infrastructure transparency, two main challenges emerge when users migrate their applications to a serverless platform: the lack of an effective analytical model for performance and billing, and the trade‐off problem between them. In this paper, we formally define a serverless workflow and introduce the concept of execution instances. Based on them, a probabilistic performance and cost evaluation model is built to obtain their expected values for an input serverless workflow. Then, we design a tailored evolutionary optimization algorithm called EASW to tackle budget‐constrained performance optimization and performance‐constrained cost optimization problems. Extensive experiments were carried out to test the proposed model and optimization algorithm on AWS Lambda. Results reveal that our model can achieve an accuracy over 98% and EASW can yield a better memory configuration solution than existing methods for constrained optimization.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135396547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DevOps project management success factors: A decision‐making framework DevOps项目管理成功因素:决策制定框架

Software: Practice and Experience Pub Date : 2023-09-13 DOI: 10.1002/spe.3269

Muhammad Azeem Akbar, Arif Ali Khan, Najmul Islam, Sajjad Mahmood

{"title":"<scp>DevOps</scp> project management success factors: A decision‐making framework","authors":"Muhammad Azeem Akbar, Arif Ali Khan, Najmul Islam, Sajjad Mahmood","doi":"10.1002/spe.3269","DOIUrl":"https://doi.org/10.1002/spe.3269","url":null,"abstract":"Abstract Development and operations (DevOps) refer to the collaboration and multidisciplinary organizational effort to automate continuous delivery of information systems (IS) development project with an aim to improve the quality of the IS. The flexibility and quality production of software projects motivated the organizations to adopt DevOps paradigm. Organizations face several complexities while management of DevOps process. This study aims to explore and analyze the factors that could positively impact the management of DevOps process. Firstly, literature review was performed and identified 36 success factors that are related to 10 knowledge areas of DevOps project management. Secondly, a questionnaire survey study was conducted to get the insight of industry experts concerning the success factors of DevOps project. Finally, the fuzzy‐AHP was applied for ranking the success factors and examining the relationship between 10 knowledge areas of identified success factors. The results of this study will serve as a body of knowledge for researchers and practitioners to consider the highest priority success factors and develop the effective policies for the successful execution of DevOps project management.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135784329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transcoding unicode characters with AVX‐512 instructions 用AVX‐512指令转码unicode字符

Software: Practice and Experience Pub Date : 2023-09-12 DOI: 10.1002/spe.3261

Robert Clausecker, Daniel Lemire

引用次数: 0

Security‐based code smell definition, detection, and impact quantification in Android Android中基于安全的代码气味定义、检测和影响量化

Software: Practice and Experience Pub Date : 2023-09-09 DOI: 10.1002/spe.3257

Yi Zhong, Mengyu Shi, Jiawei He, Chunrong Fang, Zhenyu Chen

{"title":"Security‐based code smell definition, detection, and impact quantification in Android","authors":"Yi Zhong, Mengyu Shi, Jiawei He, Chunrong Fang, Zhenyu Chen","doi":"10.1002/spe.3257","DOIUrl":"https://doi.org/10.1002/spe.3257","url":null,"abstract":"Abstract Android's high market share and extensive functionality make its security a significant concern. Research reveals that many security issues are caused by insecure coding practices. As a poor design indicator, code smell threatens the safety and quality assurance of Android applications (apps). Although previous works revealed specific problems associated with code smells, the field still lacks research reflecting Android features. Moreover, the cost and time limit developers to repairing numerous smells timely. We conducted a study, including Def inition, D etection, and I mpact Q uantification for Android code smell (DefDIQ): (1) define 15 novel code smells in Android from a security programming perspective and provide suggestions on how to eliminate or mitigate them; (2) implement DACS (Detect Android Code Smell) to automatically detect the custom code smells based on ASTs; (3) investigate the correlation between individual smells with DACS detection results, select suitable code smells to construct fault counting models, then quantify their impact on quality, and thereby generating code smell repair priorities. We conducted experiments on 4575 open‐source apps, and the findings are: (i) Lin's CCC between DACS and manual detection results reaches 0.9994, verifying the validity; (ii) the fault counting model constructed by zero‐inflated negative binomial is superior to negative binomial (AIC = 517.32, BIC = 522.12); some smells do indicate fault‐proneness, and we identify such avoidable poor designs; (iii) different code smells have different levels of importance and the repair priorities constructed provide a practical guideline for researchers and inexperienced developers.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantum machine learning‐based framework to detect heart failures in Healthcare 4.0 医疗4.0中基于量子机器学习的心力衰竭检测框架

Software: Practice and Experience Pub Date : 2023-09-05 DOI: 10.1002/spe.3264

Manushi Munshi, Rajesh Gupta, N. Jadav, Zdzislaw Polkowski, S. Tanwar, Fayez Alqahtani, Wael Said

引用次数: 0

Python meets JIT compilers: A simple implementation and a comparative evaluation Python满足JIT编译器:一个简单的实现和比较计算

Software: Practice and Experience Pub Date : 2023-09-05 DOI: 10.1002/spe.3267

Q. Zhang, Lei Xu, Baowen Xu

{"title":"Python meets JIT compilers: A simple implementation and a comparative evaluation","authors":"Q. Zhang, Lei Xu, Baowen Xu","doi":"10.1002/spe.3267","DOIUrl":"https://doi.org/10.1002/spe.3267","url":null,"abstract":"Developing a just‐in‐time (JIT) compiler can be a daunting task, especially for a language as flexible as Python. While PyPy, powered with JIT compilation, can often outperform the official pure interpreter, CPython, by a noteworthy margin, its popularity remains far from comparable to that of CPython due to some issues. Given that an easier‐to‐deploy and better‐compatible JIT compiler would benefit more Python users, we have developed comPyler, a simple JIT compiler functioning as a CPython extension and intended to convert frequently interpreted CPython bytecode into equivalent machine code. Designed with good compatibility in mind, it does not alter CPython's internal data structures or external interfaces. Based on LLVM's mature infrastructure, it can be readily ported to almost all platforms. Compared with CPython, it achieved the highest speedup of 2.205, with an average of 1.093. Despite its relatively limited effect, comPyler incurs low development costs. As a baseline compiler, it also sheds light on the improvement attainable by optimizing solely the overhead of bytecode interpretation. Furthermore, as there is still a dearth of empirical research covering the multitude of JIT compilers available for Python, we have conducted a performance study that examines Jython, IronPython, PyPy, GraalPy, Pyston, Pyjion, and our comPyler. Our research takes into account not only the benchmark speed for various time windows but also the boot latency and memory footprint. Through this comprehensive study, our objective is to assist developers in gaining a better understanding of the effects of distinct JIT compilation techniques and to aid users in making informed decisions when choosing among different Python implementations.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74707308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FIDEL: Fog integrated federated learning framework to train neural networks Fog集成了联邦学习框架来训练神经网络

Software: Practice and Experience Pub Date : 2023-09-05 DOI: 10.1002/spe.3265

Aditya Kumar, S. Srirama

{"title":"FIDEL: Fog integrated federated learning framework to train neural networks","authors":"Aditya Kumar, S. Srirama","doi":"10.1002/spe.3265","DOIUrl":"https://doi.org/10.1002/spe.3265","url":null,"abstract":"Technological advancement in the digital era has continued to produce voluminous amounts of data through various devices. Even though data is produced distributively, it needs to be accumulated centrally for processing, analysis, and knowledge extraction that faces several challenges such as bandwidth, latency, congestion, privacy, and security. Fog computing paradigm addresses some of these issues, and can be used as a distributed data processing unit. Federated learning trains a shared model over distributed nodes. However, a fog node can not process continuously growing data due to computational limitations. In this paper, we propose FIDEL: a fog integrated federated learning framework for neural network training using resource‐constrained devices. The federation of resource‐constrained Internet of Things (IoT) devices creates a shared global model trained on local data, which is generalized on the unseen dataset for prediction/inferences. We have also designed an online training scheme to process continuous data with limited compute resources. The FIDEL supports both synchronous and asynchronous federate learning that empowers resource‐constrained devices to train machine learning models. To test the learning capabilities of the FIDEL, we have trained three neural networks (i) Shallow network; (ii) Deep Network; (iii) Convolutional Neural Network (CNN) models for human position detection in industrial IoT setup on rapidly changing datasets. The experimental results show that the framework can learn input–output relationships with significantly high accuracy. The overall system efficiency of the framework is reasonable in terms of latency and memory usage for resource‐constrained devices.","PeriodicalId":21899,"journal":{"name":"Software: Practice and Experience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87540487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0