Science of Computer Programming最新文献_第9页

Actionable code smell identification with fusion learning of metrics and semantics 通过度量标准和语义的融合学习识别可操作的代码气味

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-03-27 DOI: 10.1016/j.scico.2024.103110

Dongjin Yu, Quanxin Yang, Xin Chen, Jie Chen, Sixuan Wang, Yihang Xu

{"title":"Actionable code smell identification with fusion learning of metrics and semantics","authors":"Dongjin Yu, Quanxin Yang, Xin Chen, Jie Chen, Sixuan Wang, Yihang Xu","doi":"10.1016/j.scico.2024.103110","DOIUrl":"https://doi.org/10.1016/j.scico.2024.103110","url":null,"abstract":"<div><p>Code smell detection is one of the essential tasks in the field of software engineering. Identifying whether a code snippet has a code smell is subjective and varies by programming language, developer, and development method. Moreover, developers tend to focus on code smells that have a real impact on development and ignore insignificant ones. However, existing static code analysis tools and code smell detection approaches exhibit a high false positive rate in detecting code smells, which makes insignificant smells drown out those smells that developers value. Therefore, accurately reporting those actionable code smells that developers tend to spend energy on refactoring can prevent developers from getting lost in the sea of smells and improve refactoring efficiency. In this paper, we aim to detect actionable code smells that developers tend to refactor. Specifically, we first collect actionable and non-actionable code smells from projects with numerous historical versions to construct our datasets. Then, we propose a dual-stream model for fusion learning of code metrics and code semantics to detect actionable code smells. On the one hand, code metrics quantify the code's structure and even some rules or patterns, providing fundamental information for detecting code smells. On the other hand, code semantics encompass information about developers' refactoring tendencies, which prove valuable in detecting actionable code smells. Extensive experiments show that our approach can detect actionable code smells more accurately compared to existing approaches.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"236 ","pages":"Article 103110"},"PeriodicalIF":1.3,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140344782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Implementing an environment for hybrid software evaluation 实施混合软件评估环境

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-03-24 DOI: 10.1016/j.scico.2024.103109

Ana Díaz-Muñoz , Moisés Rodríguez , Mario Piattini

{"title":"Implementing an environment for hybrid software evaluation","authors":"Ana Díaz-Muñoz , Moisés Rodríguez , Mario Piattini","doi":"10.1016/j.scico.2024.103109","DOIUrl":"https://doi.org/10.1016/j.scico.2024.103109","url":null,"abstract":"<div><p>Quantum computing is a revolutionary paradigm in computer science based on the principles of quantum mechanics. It has the potential to solve problems that are currently unsolvable for classical computing. Applications of quantum computing already span a variety of sectors.</p><p>Ongoing enhancements to the integrated programming and development environment simplify the creation and optimization of quantum algorithms. Ultimately, the focus on supporting tools represents the starting point towards achieving quantum computing maturity, facilitating its transition from an experimental domain to a practical industry.</p><p>As quantum software gains ground and relevance in various domains, it is essential to address the evaluation of hybrid systems that combine classical and quantum elements to ensure diverse quality characteristics. However, in the realm of quantum software, models, metrics, and tools are still to be established.</p><p>The primary contribution of this paper is to present the first technological environment for measuring and evaluating the analyzability of hybrid software.</p><p>Real-world examples of hybrid software are provided to showcase the functionality of the different tools in the environment, yielding readable and representative results for the evaluator.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"236 ","pages":"Article 103109"},"PeriodicalIF":1.3,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140350570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

“Will I be replaced?” Assessing ChatGPT's effect on software development and programmer perceptions of AI tools "我会被取代吗？评估 ChatGPT 对软件开发的影响以及程序员对人工智能工具的看法

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-03-22 DOI: 10.1016/j.scico.2024.103111

Mohammad Amin Kuhail , Sujith Samuel Mathew , Ashraf Khalil , Jose Berengueres , Syed Jawad Hussain Shah

{"title":"“Will I be replaced?” Assessing ChatGPT's effect on software development and programmer perceptions of AI tools","authors":"Mohammad Amin Kuhail , Sujith Samuel Mathew , Ashraf Khalil , Jose Berengueres , Syed Jawad Hussain Shah","doi":"10.1016/j.scico.2024.103111","DOIUrl":"https://doi.org/10.1016/j.scico.2024.103111","url":null,"abstract":"<div><p>ChatGPT is a language model with artificial intelligence (AI) capabilities that has found utility across various sectors. Given its impact, we conducted two empirical studies to assess the potential and limitations of ChatGPT and other AI tools in software development. In the first study, we evaluated ChatGPT 3.5′s effectiveness in generating code for 180 coding problems from LeetCode, an online coding interview preparation platform. Our findings suggest that ChatGPT 3.5 is more effective in solving easy and medium coding problems but less reliable for harder problems. Further, ChatGPT 3.5 is somewhat more effective at coding problems with higher popularity scores. In the second study, we administered a questionnaire (<em>N</em> = 99) to programmers to gain insights into their views on ChatGPT and other AI tools. Our findings indicate that programmers use AI tools for various tasks, such as generating boilerplate code, explaining complex code, and conducting research. AI tools also help programmers to become more productive by creating better-performing, shorter, and more readable code, among other benefits. However, AI tools can sometimes misunderstand requirements and generate erroneous code. While most programmers are not currently concerned about AI tools replacing them, they are apprehensive about what the future may hold. Our research has also revealed associations between AI tool usage, trust, perceived productivity, and job security threats caused by the tools.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"235 ","pages":"Article 103111"},"PeriodicalIF":1.3,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140327665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

PX-MBT: A framework for model-based player experience testing PX-MBT：基于模型的玩家体验测试框架

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-03-20 DOI: 10.1016/j.scico.2024.103108

Saba Gholizadeh Ansari , I.S.W.B. Prasetya , Mehdi Dastani , Gabriele Keller , Davide Prandi , Fitsum Meshesha Kifetew , Frank Dignum

{"title":"PX-MBT: A framework for model-based player experience testing","authors":"Saba Gholizadeh Ansari , I.S.W.B. Prasetya , Mehdi Dastani , Gabriele Keller , Davide Prandi , Fitsum Meshesha Kifetew , Frank Dignum","doi":"10.1016/j.scico.2024.103108","DOIUrl":"10.1016/j.scico.2024.103108","url":null,"abstract":"<div><p>As video games become more complex and widespread, player experience (PX) testing becomes crucial in the game industry. Attracting and retaining players are key elements to guarantee the success of a game in the highly competitive market. Although a number of techniques have been introduced to measure the emotional aspect of the experience, automated testing of player experience still needs to be explored. This paper presents <span>PX-MBT</span>, a framework for automated player experience testing with emotion pattern verification. <span>PX-MBT</span> (1) utilizes a model-based testing approach for test suite generation, (2) employs a computational model of emotions developed based on a psychological theory of emotions to model players' emotions during game-plays with an intelligent agent, and (3) verifies emotion patterns given by game designers on executed test suites to identify PX-issues. We explain <span>PX-MBT</span> architecture and provide an example along with its result in emotion pattern verification, which asserts the evolution of emotions over time, and heat-maps to showcase the spatial distribution of emotions on the game map.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"236 ","pages":"Article 103108"},"PeriodicalIF":1.3,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167642324000315/pdfft?md5=3feb08ed6c236db63ae3355a5f46a72f&pid=1-s2.0-S0167642324000315-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140280471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A method to identify overfitting program repair patches based on expression tree 基于表达树识别过度拟合程序修复补丁的方法

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-03-05 DOI: 10.1016/j.scico.2024.103105

Yukun Dong, Xiaotong Cheng, Yufei Yang, Lulu Zhang, Shuqi Wang, Lingjie Kong

{"title":"A method to identify overfitting program repair patches based on expression tree","authors":"Yukun Dong, Xiaotong Cheng, Yufei Yang, Lulu Zhang, Shuqi Wang, Lingjie Kong","doi":"10.1016/j.scico.2024.103105","DOIUrl":"10.1016/j.scico.2024.103105","url":null,"abstract":"<div><p>The primary aim of Automatic Program Repair (APR) is to automatically repair defective programs, with the intention of reducing the amount of effort required by developers. However, APR techniques may produce overfitting patches that do not truly repair the program, allowing the program to pass all test cases. This paper provides a comprehensive review of the overfitting problem and adds to the existing research on overfitting in conditional statements. Our proposed method, ETPAT (Expression Tree-based Patch Assessment Technique), implements expression trees and targeted coverage criteria to identify differences between the original and the patched program. We utilize ETPAT to verify test case adequacy. In parallel, ETPAT also guides the generation of corresponding test cases via equivalence class information, which may be added to the original test suite, making it more robust while also preventing the repair technique from generating comparable overfitting patches. With reference to the patch set in the BuggyJavaJML benchmark, ETPAT recognized 77/82 (93.9%) overfitting patches out of 120 patches related to conditional constraints, displaying superior accuracy rates and fewer test cases required than the original repair tool.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"235 ","pages":"Article 103105"},"PeriodicalIF":1.3,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140053861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Diagnosis of package installation incompatibility via knowledge base 通过知识库诊断软件包安装的不兼容性

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-03-01 DOI: 10.1016/j.scico.2024.103098

Yulu Cao , Zhifei Chen , Xiaowei Zhang , Yanhui Li , Lin Chen , Linzhang Wang

{"title":"Diagnosis of package installation incompatibility via knowledge base","authors":"Yulu Cao , Zhifei Chen , Xiaowei Zhang , Yanhui Li , Lin Chen , Linzhang Wang","doi":"10.1016/j.scico.2024.103098","DOIUrl":"https://doi.org/10.1016/j.scico.2024.103098","url":null,"abstract":"<div><p>Python package installation is far from trivial. Users encounter a variety of errors when installing Python libraries, including dependency conflicts and incompatibilities. Existing solutions focus on parsing third-party dependencies but ignore the impact of local settings and user requirements. In this paper, we propose a novel approach, HELP, to help Python users tackle installation errors. We first establish a local knowledge base by extracting the PyPI database and dependency analysis. When the user provides the installation requirements, HELP extracts multiple constraints including user requirements, Python version constraints, and dependency constraints, and models them into SMT expressions. Then HELP solves the installation problem by using the SMT solver.</p><p>To understand the status of Python version compatibility, we conduct an empirical study on Python version compatibility on 8,502 libraries. The study reveals that 80% of Python libraries do not declare Python version constraints in most versions. We also find that installation errors are strongly related to Python versions. To evaluate HELP, we conduct the experiment on 495 sampled installation failures. The results show that HELP can effectively resolve 263 installation failures, 42% more than the baseline approach. Especially, HELP provides a more comprehensive diagnosis when encountering configuration-related installation failures. Besides, HELP is more efficient than pip at predicting installation failures (30X speedups), which may save much effort if the installation cannot succeed.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"235 ","pages":"Article 103098"},"PeriodicalIF":1.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140042827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Sibilla: A tool for reasoning about collective systems Sibilla：集体系统推理工具

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-02-28 DOI: 10.1016/j.scico.2024.103095

Nicola Del Giudice, Lorenzo Matteucci, Michela Quadrini, Aniqa Rehman, Michele Loreti

引用次数: 0

Narrowing and heuristic search for symbolic reachability analysis of concurrent object-oriented systems 面向对象并发系统符号可达性分析的缩小和启发式搜索

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-02-23 DOI: 10.1016/j.scico.2024.103097

Byeongjee Kang , Kyungmin Bae

引用次数: 0

Preface for the special issue on tool papers of the 17th International Federated Conference on Distributed Computing Techniques, DisCoTec 2022 第 17 届分布式计算技术国际联盟会议（DisCoTec 2022）工具论文特刊序言

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-02-23 DOI: 10.1016/j.scico.2024.103096

Ferruccio Damiani, David Eyers, Anna Philippou

引用次数: 0

Neighborhood contrastive learning-based graph neural network for bug triaging 基于邻域对比学习的图神经网络用于错误分拣

IF 1.3 4区计算机科学

Science of Computer Programming Pub Date : 2024-02-20 DOI: 10.1016/j.scico.2024.103093

Haozhen Dong, Hongmin Ren, Jialiang Shi, Yichen Xie, Xudong Hu

{"title":"Neighborhood contrastive learning-based graph neural network for bug triaging","authors":"Haozhen Dong, Hongmin Ren, Jialiang Shi, Yichen Xie, Xudong Hu","doi":"10.1016/j.scico.2024.103093","DOIUrl":"10.1016/j.scico.2024.103093","url":null,"abstract":"<div><p>Researchers have been developing automatic bug triaging techniques by leveraging bug information sourced from bug tracking systems. Recent studies have modeled the bug-developer relationship as a graph, introducing graph neural networks for bug triaging. Despite achieving positive outcomes, these methods overlook issues related to data sparsity and fail to fully exploit implicit relationships within the graph. In addressing these challenges, we present the Neighborhood Contrastive Learning-based Graph Neural Network Bug Triaging framework, abbreviated as NCGBT. Our approach models the relationship between bugs and developers as a bipartite graph. We utilize a pre-trained language model to acquire the initial representation of bug nodes. Employing a basic graph neural network framework, we learn the representation of all nodes and leverage these representations to predict developers for a given bug. Our proposed strategy involves neighborhood contrastive learning applied to the basic graph neural network approach. We take into account the neighbors of nodes from both structural and semantic perspectives, utilizing them as contrastive objects. Extensive experiments conducted on three public datasets demonstrate the effectiveness of the NCGBT framework.</p></div>","PeriodicalId":49561,"journal":{"name":"Science of Computer Programming","volume":"235 ","pages":"Article 103093"},"PeriodicalIF":1.3,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139919482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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