標(biāo)題: Titlebook: Recommendation Systems in Software Engineering; Martin P. Robillard,Walid Maalej,Thomas Zimmermann Book 2014 Springer-Verlag Berlin Heidel [打印本頁] 作者: 哪能仁慈 時間: 2025-3-21 19:18
書目名稱Recommendation Systems in Software Engineering影響因子(影響力)
書目名稱Recommendation Systems in Software Engineering影響因子(影響力)學(xué)科排名
書目名稱Recommendation Systems in Software Engineering網(wǎng)絡(luò)公開度
書目名稱Recommendation Systems in Software Engineering網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Recommendation Systems in Software Engineering被引頻次
書目名稱Recommendation Systems in Software Engineering被引頻次學(xué)科排名
書目名稱Recommendation Systems in Software Engineering年度引用
書目名稱Recommendation Systems in Software Engineering年度引用學(xué)科排名
書目名稱Recommendation Systems in Software Engineering讀者反饋
書目名稱Recommendation Systems in Software Engineering讀者反饋學(xué)科排名
作者: 殺死 時間: 2025-3-21 22:39
Simulationpplied in practice. From these examples, we extract some general strengths and weaknesses of the use of simulation to evaluate RSSEs. We also explore prospects for making more extensive use of simulation in the future.作者: Vulnerable 時間: 2025-3-22 02:49
Recommending Program Transformations this chapter describes two concrete example-based program transformation approaches in detail, Sydit and Lase. These two approaches are selected for an in-depth discussion, because they handle the issue of both recommending change locations and applying transformations, and they are specifically de作者: neoplasm 時間: 2025-3-22 05:02
Book 2014ibes needs, issues and solution concepts involved in entire recommendation systems for specific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materia作者: Anthrp 時間: 2025-3-22 09:38
ot in terms of a local or global explanation. The current approach for XAI for RL is Policy summarization?[.], typically by visual, gradient based methods. Policy summarization characterizes a path a policy would take or feature effects on a policy through a path. Visual explanations consist of feat作者: 哀求 時間: 2025-3-22 12:54 作者: 創(chuàng)作 時間: 2025-3-22 18:44 作者: garrulous 時間: 2025-3-23 00:43 作者: Intervention 時間: 2025-3-23 05:00 作者: A保存的 時間: 2025-3-23 08:49 作者: 議程 時間: 2025-3-23 13:15 作者: 精致 時間: 2025-3-23 17:42
Kim Herzig,Andreas Zellert evaluation metrics. Specifically, the ResNet-50 was trained to classify CT scans of lungs acquired with and without contrast agents, in which clinically relevant anatomical areas were manually determined by experts as segmentation masks in the images. Three evaluation metrics were used to quantify作者: dyspareunia 時間: 2025-3-23 21:26
Walid Maalej,Thomas Fritz,Romain Robbes is to underestimate the context dependency and subjectivity of the explanations’ understanding, interpretation, and relevance. Moreover, even a plausible (and possibly expected) explanation can lead to an imprecise or incorrect outcome or its understanding. This can lead to unbalanced and unfair ci作者: 傲慢人 時間: 2025-3-24 01:10
Annie T. T. Ying,Martin P. Robillards and Contextual Importance and Utility (CIU) for localizing the disease areas based on prediction. The user interface is developed as an IOS mobile app, allowing farmers to capture a photo of the infected grape leaves. The system has been evaluated using various performance metrics such as classifi作者: 含沙射影 時間: 2025-3-24 06:21
Emerson Murphy-Hill,Gail C. Murphys and Contextual Importance and Utility (CIU) for localizing the disease areas based on prediction. The user interface is developed as an IOS mobile app, allowing farmers to capture a photo of the infected grape leaves. The system has been evaluated using various performance metrics such as classifi作者: NEEDY 時間: 2025-3-24 06:57
al confusion. We propose ReCCoVER, an algorithm which detects causal confusion in an agent’s reasoning before deployment, by executing its policy in alternative environments where certain correlations between features do not hold. We demonstrate our approach in the taxi and grid world environments, 作者: 可觸知 時間: 2025-3-24 12:16
Iman Avazpour,Teerat Pitakrat,Lars Grunske,John Grundychanges and analyze theoretically the rationality of this approach. Specifically, we extend PMRL-OM based on an analysis of the PMRL-OM approach. Our experiments evaluated the performance of the proposed method for a navigation task in a maze-type environment undergoing cyclic environmental change, 作者: 農(nóng)學(xué) 時間: 2025-3-24 16:11 作者: THE 時間: 2025-3-24 19:05
Robert J. Walker,Reid Holmeschanges and analyze theoretically the rationality of this approach. Specifically, we extend PMRL-OM based on an analysis of the PMRL-OM approach. Our experiments evaluated the performance of the proposed method for a navigation task in a maze-type environment undergoing cyclic environmental change, 作者: 合適 時間: 2025-3-25 01:48
Ay?e Tosun M?s?rl?,Ay?e Bener,Bora ?a?layan,Gül ?al?kl?,Burak Turhanver, this paper argues that how the provided explanations and their content can exacerbate the deceptive dynamics or even manipulate the end user. Therefore, in order to avoid similar consequences, this analysis suggests legal principles to which the explanation must conform to mitigate the side eff作者: dandruff 時間: 2025-3-25 03:46 作者: 職業(yè)拳擊手 時間: 2025-3-25 07:45 作者: Gyrate 時間: 2025-3-25 14:09 作者: sterilization 時間: 2025-3-25 19:17
Miryung Kim,Na Menggly, we investigate research areas including: . reasoning and automatic theorem proving to synthesize novel knowledge via inference; . automatic planning and simulation, used to speculate over alternative courses of action; . machine learning and data mining, exploited to induce new knowledge from e作者: 混合,攙雜 時間: 2025-3-25 19:58
cific software engineering tasks, focusing on the engineering insights required to make effective recommendations. The book is complemented by the webpage rsse.org/book, which includes free supplemental materia978-3-662-52404-6978-3-642-45135-5作者: FADE 時間: 2025-3-26 00:27
Developer Profiles for Recommendation Systemsnal information, and communication networks. In recommendation systems in software engineering, developer profiles can be used for personalizing recommendations and for recommending developers who can assist with a task. This chapter describes techniques for capturing, representing, storing, and using developer profiles.作者: FLIC 時間: 2025-3-26 06:44
http://image.papertrans.cn/r/image/824115.jpg作者: 捕鯨魚叉 時間: 2025-3-26 08:57 作者: narcotic 時間: 2025-3-26 14:54 作者: 禍害隱伏 時間: 2025-3-26 20:41 作者: 厭煩 時間: 2025-3-26 21:34
978-3-662-52404-6Springer-Verlag Berlin Heidelberg 2014作者: contrast-medium 時間: 2025-3-27 03:28
Recommendation Systems in-the-Smallby a RITS through the use of heuristics. Several examples drawn from the literature illustrate the applications and designs of RITSs. We provide an introduction to the development of the heuristics typically needed by a RITS. We discuss the general limitations of RITSs.作者: conscribe 時間: 2025-3-27 06:05
Mining Bug Dataers, success, and finally profit. This chapter serves as a hand-on tutorial on how to mine bug reports, relate them to source code, and use the knowledge of bug fix locations to model, estimate, or even predict source code quality. This chapter also discusses risks that should be addressed before one can achieve reliable recommendation systems.作者: 卜聞 時間: 2025-3-27 11:18 作者: 帶來墨水 時間: 2025-3-27 13:45 作者: 露天歷史劇 時間: 2025-3-27 21:31 作者: 尾巴 時間: 2025-3-28 00:41
Book 2014 specifically address the unique challenges of navigating and interpreting software engineering data..This book collects, structures and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and作者: 不能妥協(xié) 時間: 2025-3-28 06:03
An Introduction to Recommendation Systems in Software Engineering,g include the source code and change history of the software, discussion lists and forums, issue databases, component technologies and their learning resources, and the development environment. The technical nature, size, and dynamicity of these information spaces motivate the development of a speci作者: Cholecystokinin 時間: 2025-3-28 09:37
Basic Approaches in Recommendation Systemsent-based filtering, and knowledge-based recommendation. We first discuss principles of the underlying algorithms based on a running example. Thereafter, we provide an overview of hybrid recommendation approaches which combine basic variants. We conclude this chapter with a discussion of newer algor作者: Isometric 時間: 2025-3-28 13:31
Recommendation Systems in-the-Smallr the infrastructure needed to support and to maintain an RSSE; moreover, it can be computationally expensive. This chapter examines recommendation systems in-the-small (RITSs), which do not rely on data mining. Instead, they take small amounts of data from the developer’s local context as input and作者: Synovial-Fluid 時間: 2025-3-28 16:43
Source Code-Based Recommendation Systemse most reliable data source. It provides a rich and structured source of information upon which recommendation systems can rely to provide useful recommendations to software developers. Source code-based recommendation systems provide support for tasks such as how to use a given API or framework, pr作者: 考古學(xué) 時間: 2025-3-28 20:28 作者: 要塞 時間: 2025-3-28 23:11 作者: etiquette 時間: 2025-3-29 03:25 作者: PRO 時間: 2025-3-29 09:53
Recommendation Deliverybe delivered with a user interface that allows the user to become aware that recommendations are available, to determine if any of the recommendations have value for them and to be able to act upon a recommendation. By synthesizing previous results from general recommendation system research and sof作者: 割公牛膨脹 時間: 2025-3-29 13:59
Dimensions and Metrics for Evaluating Recommendation Systemscovery tasks, and approximate computation, among others. They have recently become popular and have attracted a wide variety of application scenarios ranging from business process modeling to source code manipulation. Due to this wide variety of application domains, different approaches and metrics 作者: Intersect 時間: 2025-3-29 19:28 作者: 細(xì)查 時間: 2025-3-29 23:46 作者: 表狀態(tài) 時間: 2025-3-30 01:04 作者: optional 時間: 2025-3-30 06:19
Reuse-Oriented Code Recommendation Systemsommendation systems that have the ability to unobtrusively suggest immediately applicable reuse opportunities can become a crucial step toward realizing this goal and making reuse more practical. This chapter focuses on tools that support reuse through the recommendation of source code—. (ROCR). The作者: SPASM 時間: 2025-3-30 08:57
Recommending Refactoring Operations in Large Software Systems original design, often reducing its quality. In such cases, . techniques can be applied to improve the readability and reducing the complexity of source code, to improve the architecture and provide for better software extensibility. Despite its advantages, performing refactoring in large and nontr作者: Conspiracy 時間: 2025-3-30 14:03
Recommending Program Transformationsding all relevant locations and making the correct edits is a tedious and error-prone process. This chapter presents several state-of-the art approaches to recommending . in order to automate repetitive software changes. First, it discusses . (PBD) approaches that automate repetitive tasks by inferr作者: 易碎 時間: 2025-3-30 17:13
An Introduction to Recommendation Systems in Software Engineering,nformation spaces in software engineering, describe the unique aspects of RSSEs, present an overview of the issues and considerations involved in creating, evaluating, and using RSSEs, and present a general outlook on the current state of research and development in the field of recommendation systems for highly technical domains.作者: 拋射物 時間: 2025-3-30 22:09 作者: 致敬 時間: 2025-3-31 04:02 作者: 嬉耍 時間: 2025-3-31 08:10 作者: 磨坊 時間: 2025-3-31 10:51 作者: 事與愿違 時間: 2025-3-31 14:30 作者: 大看臺 時間: 2025-3-31 19:51
