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关键词： Testing   Software systems   Computer science   Fault diagnosis   Open source software   Indexes   Software testing   combinatorial testing   covering array   failure-inducing interactions  

摘要： Combinatorial testing (CT) seeks to detect potential faults caused by various interactions of factors that can influence the software systems. When applying CT, it is a common practice to first generate a set of test cases to cover each possible interaction and then to identify the failure-inducing interaction after a failure is detected. Although this conventional procedure is simple and forthright, we conjecture that it is not the ideal choice in practice. This is because 1) testers desire to identify the root cause of failures before all the needed test cases are generated and executed 2) the early identified failure-inducing interactions can guide the remaining test case generation so that many unnecessary and invalid test cases can be avoided. For these reasons, we propose a novel CT framework that allows both generation and identification process to interact with each other. As a result, both generation and identification stages will be done more effectively and efficiently. We conducted a series of empirical studies on several open-source software, the results of which show that our framework can identify the failure-inducing interactions more quickly than traditional approaches while requiring fewer test cases.

关键词： C++程序设计   语法知识   编程   教学方法  

摘要： 掌握程序设计基本方法并解决实际问题,已成为理工科学生复合型人才的必要条件。C++程序设计课程具有抽象程度高、理论性和实践性强的特点;现有教学存在过多强调语法知识、轻视实践、与学生专业脱钩等问题。探索“非计算机”理工科专业C++程序设计课程教学改革,以提高学生编程能力、并使用程序设计解决本专业实践问题为目的,着重从教学内容、实践环节、编程习惯等角度进行探讨并提出具体改革措施。该教学改革有助于实现提升教学质量、为专业建设服务的目的。

关键词： capital punishment   corrections   court   courts/law   other   quantitative methods   race and crime/justice   violent behavior  

摘要： To understand how racial/ethnic disparities are formed and sustained within death penalty institutions, this study tracks homicide cases through multiple stages of Los Angeles County’s criminal justice system. Drawing upon cumulative disadvantage research, this study focuses on the accumulation of racial/ethnic biases across multiple decision-making points. Logistic regressions seek to answer the following questions: (1) does victim/defendant race/ethnicity influence prosecutorial decision-making? and (2) if so, do these racial/ethnic disparities accumulate across multiple stages of the criminal justice system? Results indicate that cases with minority victims are less likely to involve a death-eligible charge or death notice. Moreover, these racial/ethnic disparities increase as cases advance through the courts, producing a Whiter pool of victims at later stages in the process. Defendant race/ethnicity is not predictive of death penalty charging decisions but does moderate the influence of victim race/ethnicity such that cases with minority defendants and White victims are treated more punitively. © 2017 Georgia State University.

关键词： 疾病   鼠疫/黑死病   文化   文学  

摘要： 突发性传染性疾病往往对社会文化影响巨大,其间所形成的疾病文化现象也值得特别重视。因此,人们至今对发生在欧洲中世纪的鼠疫或黑死病这一典型的疾病性事件,以包括文学在内的不同方式持续进行着研究和呈现。人们以文学对疾病文化进行表征,其意义不仅是文学主题的扩容,而且可以使之发挥出历史文化功能,亦即读者通过此类阅读在获得审美性体验的同时,有利于提升必备的公共卫生意识。所以,作为揭示人的历史境遇、张扬生命文化的文学书写对于疾病文化的表征,可以使人们重拾对自然的敬畏感并间接地奠定社会文化发展所需的观念基础。这一点有必要在文学研究和文学教育中予以强化。

摘要： 第三届计算机信息科学与人工智能国际学术会议(CISAI 2020)定于2020年9月25-27日在中国呼伦贝尔隆重举行。会议旨在为从事"计算机科学""信息科学"与"人工智能"研究的专家学者、工程技术人员、技术研发人员提供一个共享科研成果和前沿技术,了解学术发展趋势,拓宽研究思路,加强学术研究和探讨,促进学术成果产业化合作的平台。大会诚邀国内外高校、科研机构专家、学者,企业界人士及其他相关人员参会交流。

关键词： Twitter   Predictive models   Bayes methods   Computer science   Probabilistic logic   Sun   Social influence   Poisson factorization   microblogging  

摘要： Social influence analysis in microblogging services has attracted much attention in recent years. However, most previous studies were focused on measuring users' (topical) influence. Little effort has been made to discern and quantify how a user is influenced. Specifically, the fact that user $i$i retweets a tweet from author $j$j could be either because $i$i is influenced by $j$j (i.e., $j$j is a topical authority), or simply because he is "influenced" by the content (interested in the content). To mine such influence patterns, we propose a novel Bayesian factorization model, dubbed Influence Beta-Poisson Factorization (IBPF). IBPF jointly factorizes the retweet data and tweet content to quantify latent topical factors of user preference, author influence and content influence. It generates every retweet record according to the sum of two causing terms: one representing author influence, and the other one derived from content influence. To control the impact of the two terms, for each user IBPF generates a probability for each latent topic by Beta distribution, indicating how strongly the user cares about the topical authority of the author. We develop an efficient variational inference algorithm for IBPF. We demonstrate the efficacy of IBPF on two public microblogging datasets.

关键词： Testing   Fault diagnosis   Flexible printed circuits   Software   Task analysis   Debugging   Computer science   Combinatorial testing   fault localization   debugging  

摘要： Combinatorial testing has been shown to be a very effective strategy for software testing. After a failure is detected, the next task is to identify one or more faulty statements in the source code that have caused the failure. In this paper, we present a fault localization approach, called BEN, which produces a ranking of statements in terms of their likelihood of being faulty by leveraging the result of combinatorial testing. BEN consists of two major phases. In the first phase, BEN identifies a combination that is very likely to be failure-inducing. A combination is failure-inducing if it causes any test in which it appears to fail. In the second phase, BEN takes as input a failure-inducing combination identified in the first phase and produces a ranking of statements in terms of their likelihood to be faulty. We conducted an experiment in which our approach was applied to the Siemens suite and four real-world programs, flex, grep, gzip and sed, from Software Infrastructure Repository (SIR). The experimental results show that our approach can effectively and efficiently localize the faulty statements in these programs.