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evaluating software maintainability using fuzzy entropy theory

Evaluating software maintainability using fuzzy entropy theo...

IEEE/International Association for computer and Information Science International Conference on computer and Information Science

作者： Cai, Lizhi Liu, Zhenyu Zhang, Juan Tong, Weiqin Yang, Genxing Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai 201112 China Shanghai Key Laboratory of Computer Software Evaluating and Testing China School of Computer Engineering and Science Shanghai University China

ISBN: (纸本)9780769541471

With the development of information technology, a large number of software products enter the maintenance phase. The maintainability of software products continues to attract people's attention. This paper proposes a new synthetic maintainability evaluation model basing on fuzzy entropy theory. In the model, the weight of different indexes is calculated by combining the entropy weight and expert weight. The entropy weight can be obtained through measuring the difference of membership degree of the index which reflects the consistency of the expert opinion. The evaluation result is more objective and reasonable. It provides a guideline to design a software product with high maintainability. © 2010 IEEE.

关键词： Entropy

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A business process testing sequence generation approach based on test cases composition

A business process testing sequence generation approach base...

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International Association for computer and Information Science/JNU International Conference on computers, Networks, Systems and Industrial Engineering

作者： Cai, Lizhi Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai 201112 China

ISBN: (纸本)9780769544175

This paper proposes a business process testing scenario generation based on test cases composition. Just like path oriented testing technique in structure testing area, this testing method focuses on finding the logical error in the process implementation according to the formal business process presentation. The test cases against a node of process designed by the techniques such as boundary value analysis , equivalence partitioning and so on, may not easily find the errors in the special business process tends. These test cases are modeled as TCN (Test Cases Nets) with a CPN (Colored Petri Nets) in this paper. The BPSN (Business Process Scenario Net) is built by composing the existing TCN. The generation technique of the test scenario for basis path testing for a business process according to the BPSN is discussed. We exemplify our approach in an ATM system that has a rich set of interactions with its users. © 2011 IEEE.

关键词： testing

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Community Smell Occurrence Prediction on Multi-Granularity by Developer-Oriented Features and Process Metrics

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Journal of computer Science & Technology 2022年第1期37卷 182-206页

作者： Zi-Jie Huang Zhi-Qing Shao Gui-Sheng Fan Hui-Qun Yu Xing-Guang Yang Kang Yang Department of Computer Science and Engineering East China University of Science and TechnologyShanghai 200237China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai 200237China Shanghai Engineering Research Center of Smart Energy Shanghai 200237China

Community smells are sub-optimal developer community structures that hinder *** studies performed smell prediction and provided refactoring guidelines from a top-down aspect to help community ***,refactoring smells also requires bottom-up effort from every ***,supportive measures and guidelines for them are not available at a fine-grained *** recent work revealed developers'personalities and working states could influence community smells'emergence and variation,we build prediction models with experience,sentiment,and development process features of developers considering three smells including Organizational Silo,Lone Wolf,and Bottleneck,as well as two related classes including smelly developer and smelly *** predict the five classes in the individual granularity,and we also generate forecasts for the number of smelly developers in the community *** proposed models achieve F-measures ranging from 0.73 to 0.92 in individual-wide within-project,time-wise,and cross-project prediction,and mean R2 performance of 0.68 in community-wide Smelly Developer *** also exploit SHAP(SHapley Additive exPlanations)to assess feature importance to explain our *** conclusion,we suggest developers with heavy workload should foster more frequent communication in a straightforward and polite way to build healthier communities,and we recommend community shepherds to use the forecasting model for refactoring planning.

关键词： community smell developer sentiment socio-technical analysis empirical software engineering

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Research on Measuring Method of Function Size of Information System 26

Research on Measuring Method of Function Size of Information...

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26th ACIS International Winter Conference on software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD-Winter 2023

作者： Chunye, Du Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Software Testing &evaluating Shanghai China

ISBN: (纸本)9798350345865

With the rapid development of software industry, a variety of new technologies are produced. Research and development in cloud computing, big data, artificial intelligence, the Internet of Things, blockchain, and other related fields continue to prosper. The increasing lines of code, function points, escalating scale of software systems, and the rising complexity of software development collectively complicate software cost estimation. This article studies how to estimate the size, workload, and cost of an information system using functional scale measurement methods. © 2023 IEEE.

关键词： Information systems

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Automated Functionality and Security Evaluation of Large Language Models 9

Automated Functionality and Security Evaluation of Large Lan...

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9th IEEE International Conference on Smart Cloud, SmartCloud 2024

作者： Ding, Minjie Shen, Ying Chen, Mingang Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (纸本)9798350389500

Natural language processing (NLP) is rapidly developing. A series of Large Language Models (LLMs) have emerged, represented by ChatGPT, which have made significant breakthroughs in natural language understanding and generation, enabling fluent dialogue with humans, understanding human intentions, and completing complex tasks. However, in addition to the fairness and toxicity of traditional language models, some new problems, including hallucination, have also emerged in LLMs, making them hard to use. evaluating LLMs manually is challenging due to subjectivity and inefficiency. In this paper, we focused on the fuzzy matching, toxicity detection, and hallucination detection in the evaluation of LLMs automatically, and fine-tune the Mixtral-8x7B Model, which can be deployed in private cloud environment, and prove the effectiveness of our method through experiments. © 2024 IEEE.

关键词： Toxicity

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Scheduling Real-Time Embedded Systems Based on TCPNIA

Journal of Software

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Journal of software 2011年第3期6卷 340-348页

作者： Yang, Nianhua Yu, Huiqun Sun, Hua Qian, Zhilin Department of Computer Science and Engineering East China University of Science and Technology Shanghai 200237 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai 201112 China

TCPNIA (Timed Colored Petri Nets with Inhibitor Arcs, TCPNIA) is a model for specifying real-time embedded systems. It integrates features of colored Petri nets, timed Petri nets and inhibitor arcs. The methods for modeling modules of systems using TCPNIA are proposed. A depth-first scheduling algorithm for TCPNIA is proposed. The system level resource's influence to schedulable path is considered. Different data in tokens will change an execution path and call different data operational functions. The influence from data operational functions is considered in the scheduling algorithm. The time requirement upper bound of a schedulable path can be calculated in the algorithm. Tasks' parallel executions have been considered when the time upper bound of the path is calculated. The soundness of the algorithm is proved. The time and space complexities of the algorithm are also analyzed. The compositional conditions and method for composing schedulable path are given. A case study shows the applicability and feasibility of the method. © 2011 ACADEMY PUBLISHER.

关键词： Petri nets

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Research on stream processing engine and benchmarking framework 19

Research on stream processing engine and benchmarking framew...

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19th IEEE International Conference on Networking, Sensing and Control, ICNSC 2022

作者： Le, Qionghua Chen, Mingang Chen, Wenjie Shanghai Development Center of Computer Software Technology Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai China

ISBN: (纸本)9781665472432

Stream computing engine is an important part of big data system, and benchmarking is one of the main means to measure the engine's performance. In this paper, we compare the differences between two engines, Spark Streaming and Flink, in stream processing technologies. Then the open source benchmarking frameworks supporting stream processing and their respective characteristics are studied, and the HiBench testing framework is selected to test the two stream processing engines. The test results show that Flink is better than Spark Streaming in terms of performance in shuffle, stateful computation and windowed computation. © 2022 IEEE.

关键词： Benchmarking

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Detection and Segmentation of Graphical Elements on GUIs for Mobile Apps Based on Deep Learning 11th

Detection and Segmentation of Graphical Elements on GUIs for...

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11th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2020

作者： Hu, Rui Chen, Mingang Cai, Lizhi Chen, Wenjie Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China

ISBN: (纸本)9783030642136

Recently, mobile devices are more popular than computers. However, mobile apps are not as thoroughly tested as desktop ones, especially for graphical user interface (GUI). In this paper, we study the detection and segmentation of graphical elements on GUIs for mobile apps based on deep learning. It is the preliminary work of GUI testing for mobile apps based on artificial intelligence. We create a dataset, which consists of 2,100 GUI screenshots (or pages) labeled with 42,156 graphic elements in 8 classes. Based on our dataset, we adopt Mask R-CNN to train the detection and segmentation of graphic elements on GUI screenshots. The experimental results show that the mAP value achieves 98%. © 2020, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Graphical user interfaces

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An Evaluation System for Large Language Models based on Open-Ended Questions 11

An Evaluation System for Large Language Models based on Open...

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11th IEEE International Conference on Cyber Security and Cloud Computing, CSCloud 2024

作者： Cao, Zhiyuan Ma, Zeyu Chen, Mingang Computer and Information Engineering College Shanghai Polytechnic University Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer Software Technology Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Mathematical and Science College Shanghai Normal University Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai Development Center of Computer software Technology Shanghai China

ISBN: (纸本)9798350376982

We designed a large language model evaluation system based on open-ended questions. The system accomplished multidimensional evaluation of LLMs using open-ended questions, and it presented evaluation results with evaluation reports. Currently, the evaluation of large-scale language models often exists with two prominent limitations: (1) The evaluation methods are often single-minded, resulting in less credible results. (2) Most evaluations are based on datasets with closed-ended questions, treating generative large language models as discriminative models, which fails to adequately reflect the high output flexibility characteristic of these models. For these two limitations, we proposed an evaluation system for LLMs based on open-ended questions. Our experiments on the adapted open-source datasets demonstrated the effectiveness of this system. © 2024 IEEE.

关键词： Natural language processing systems

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Research on GUI-based automation test technology driven by separated definition data

International Journal of Control and Automation

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International Journal of Control and Automation 2014年第6期7卷 421-432页

作者： Liu, Zhenyu Chen, Qiang Cai, Lizhi Shanghai Key Laboratory of Computer Software Testing and Evaluation China

GUI-based software is often developed a complicated test script with existing traditional automation software testing tools. The software automated test development technology consequently carried out some study of existing automated testing with current automated testing tools to simplify the script. The paper proposed a novel test automation technology with separated definition data, which replaced by script development or modification. The definition data are depicted for script driven, page description and test data separately. The test automation technology provided completed function and interface between this method and actual test tool. The test engineers is not need to write the any test script, but modify the definition files for test developing to some extent. The automation functional test technology has support the typical test tool and proved effective in the specific cases. © 2014 SERSC.

关键词： Graphical user interfaces

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