Software Quality Journal最新文献_第3页

LLM-BRC: A large language model-based bug report classification framework LLM-BRC：基于大型语言模型的错误报告分类框架

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-24 DOI: 10.1007/s11219-024-09675-3

Xiaoting Du, Zhihao Liu, Chenglong Li, Xiangyue Ma, Yingzhuo Li, Xinyu Wang

引用次数: 0

A source model simplification method to assist model transformation debugging 辅助模型转换调试的源模型简化方法

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-24 DOI: 10.1007/s11219-024-09676-2

Junpeng Jiang, Mingyue Jiang, Liming Nie, Zuohua Ding

引用次数: 0

Enhancing human-machine pair inspection with risk number and code inspection diagram 利用风险编号和代码检查图加强人机对检查

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-23 DOI: 10.1007/s11219-024-09674-4

Yujun Dai, Shaoying Liu, Guangquan Xu

引用次数: 0

An effective parallel convolutional anomaly multi-classification model for fault diagnosis in microservice system 用于微服务系统故障诊断的有效并行卷积异常多分类模型

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-21 DOI: 10.1007/s11219-024-09672-6

Xi Li, Peian Wen, Peng Chen, Juan Chen, Xuming Wen, Yunni Xia

引用次数: 0

Automated SC-MCC test case generation using coverage-guided fuzzing 利用覆盖引导模糊自动生成 SC-MCC 测试用例

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-14 DOI: 10.1007/s11219-024-09667-3

Monika Rani Golla, Sangharatna Godboley

{"title":"Automated SC-MCC test case generation using coverage-guided fuzzing","authors":"Monika Rani Golla, Sangharatna Godboley","doi":"10.1007/s11219-024-09667-3","DOIUrl":"https://doi.org/10.1007/s11219-024-09667-3","url":null,"abstract":"One of the main objectives of testing is to achieve adequate code coverage. Modern code coverage standards suggest MC/DC (Modified Condition/Decision Coverage) instead of MCC (Multiple Condition Coverage) due to its ability to generate a feasible number of test cases. In contrast to the MC/DC, which only takes independent pairs into consideration, the MCC often considers each and every test case. In our work, we suggest SC-MCC, i.e., MCC with Short-Circuit. The key aspect of this paper is to demonstrate the effectiveness of SC-MCC-based test cases compared to MC/DC using Coverage-Guided Fuzzing (CGF) technique. In this work, we have considered American Fuzzy Lop (AFL) tool to generate both the SC-MCC and MC/DC test cases for 54 RERS benchmark programs. As part of this paper, we propose unique goal constraint generation and fuzz-instrumentation techniques that help in mitigating the masking problem of AFL. Subsequently, we performed mutation testing by employing the GCOV tool and computed the mutation score in order to evaluate the quality of the generated test cases. Finally, based on our observations, SC-MCC has performed better for over 85% of the programs taken into consideration.","PeriodicalId":21827,"journal":{"name":"Software Quality Journal","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CLOUD-QM: a quality model for benchmarking cloud-based enterprise information systems CLOUD-QM：基于云的企业信息系统基准质量模型

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-14 DOI: 10.1007/s11219-024-09669-1

Umut Şener, Ebru Gökalp, P. Erhan Eren

{"title":"CLOUD-QM: a quality model for benchmarking cloud-based enterprise information systems","authors":"Umut Şener, Ebru Gökalp, P. Erhan Eren","doi":"10.1007/s11219-024-09669-1","DOIUrl":"https://doi.org/10.1007/s11219-024-09669-1","url":null,"abstract":"Organizations are increasingly migrating from on-premise enterprise information systems (EIS) to cloud products due to cloud computing benefits, such as flexibility, elasticity, and on-demand service. However, identifying the most suitable option becomes challenging with the proliferation of Cloud-EIS solutions in the market. To address this challenge, this study introduces a novel quality model named Cloud-QM, based on ISO/IEC 250nn standards. It diagnoses the quality of Cloud-EIS products, benchmarks available options, and identifies the most suitable choice for the organization. Cloud-QM comprises 10 main dimensions, 33 sub-dimensions, and corresponding metrics for a systematic quality assessment. Furthermore, the practical use of Cloud-QM is illustrated through a case study that evaluates two substitute Cloud-EIS products. The results from the case study highlight the effectiveness of Cloud-QM in enabling decision-makers to delve into the quality dimensions and facilitate the selection of the most suitable product for their organizations. The main contributions are as follows: (1) proposing a comprehensive and hierarchically structured quality model for Cloud-EIS products; (2) offering a quantifiable and standardized assessment approach through a set of metrics for quality evaluation; and (3) demonstrating applicability and usability of Cloud-QM by benchmarking Cloud-EIS products.","PeriodicalId":21827,"journal":{"name":"Software Quality Journal","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

KAD: a knowledge formalization-based anomaly detection approach for distributed systems KAD：基于知识形式化的分布式系统异常检测方法

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-05-10 DOI: 10.1007/s11219-024-09670-8

Xinjie Wei, Chang-ai Sun, Xiao-Yi Zhang

{"title":"KAD: a knowledge formalization-based anomaly detection approach for distributed systems","authors":"Xinjie Wei, Chang-ai Sun, Xiao-Yi Zhang","doi":"10.1007/s11219-024-09670-8","DOIUrl":"https://doi.org/10.1007/s11219-024-09670-8","url":null,"abstract":"Large-scale distributed systems are becoming key engines of the IT industry due to their scalability and extensibility. A distributed system often involves numerous complex interactions among components, suffering anomalies such as data inconsistencies between components and unanticipated delays in response times. Existing anomaly detection techniques, which extract knowledge from system logs using either statistical or machine learning techniques, exhibit limitations. Statistical techniques often miss implicit anomalies that are related to complex interactions manifested by logs, whereas machine learning techniques lack explainability and they are usually sensitive to log variations. In this paper, we propose KAD, a knowledge formalization-based anomaly detection approach for distributed systems. KAD includes a general knowledge description language (KDL), leveraging the general structure of system logs and extended Backus-Naur form (EBNF) for complex knowledge extraction. Particularly, the semantic set is constructed based on the bidirectional encoder representation from the transformer (BERT) model to improve the expressive capabilities of KDL in knowledge description. In addition, KAD incorporates distributed scheduling computation module to improve the efficiency of anomaly detection processes. Experimental results based on two widely used benchmarks show that KAD can accurately describe the knowledge associated with anomalies, with a high F1-score in detecting various anomaly types.","PeriodicalId":21827,"journal":{"name":"Software Quality Journal","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140939196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantitative evaluation of molecular generation performance of graph-based GANs 定量评估基于图的 GAN 的分子生成性能

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-04-25 DOI: 10.1007/s11219-024-09671-7

Jinli Zhang, Zhenbo Wang, Zongli Jiang, Man Wu, Chen Li, Yoshihiro Yamanishi

引用次数: 0

Differential testing solidity compiler through deep contract manipulation and mutation 通过深度合约操作和突变对 solidity 编译器进行差异测试

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-04-23 DOI: 10.1007/s11219-024-09673-5

Zhenzhou Tian, Fanfan Wang, Yanping Chen, Lingwei Chen

引用次数: 0

Exploring API behaviours through generated examples 通过生成的示例探索应用程序接口行为

IF 1.9 3区计算机科学

Software Quality Journal Pub Date : 2024-04-22 DOI: 10.1007/s11219-024-09668-2

Stefan Karlsson, John Hughes, Robbert Jongeling, Adnan Čaušević, Daniel Sundmark

引用次数: 0