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The author discusses computational methods utilized in the peer review process. It examines the availability of data in peer review, and experimentation in peer review design. It also discusses author identity bias, overall subjectivity in peer review, and author incentives.

The article discusses the lack of efficiency in how research data within the Computer Science discipline are shared. The author uses the acronym FAIR -- findable, accessible, interoperable, and reusable -- to capture how data should be made available at conferences and in journals.

The article discusses the relationship between artificial intelligence and computer science and the history and development of each discipline between 1950 and 1970. Information is presented on the research behind artificial intelligence and the beginning of graduate education programs in the United States in both artificial intelligence and computer science.

The article discusses an algorithm designed to compute maximum flow and minimum-cost flows. It builds on the works of prior researchers to propose new theorems and provides formulas and graphs to illustrate these theorems and schemes.

The article discusses the community that developed during the decade of the 1970's that fostered the growth of research into artificial intelligence. It details the slow progress of AI researchers in developing the field. It mentions the importance of military backing in aid of AI research, including funding acquired through Advanced Research Projects Agency (ARPA) to places like MIT and Stanford University. It outlines the continued struggle for broader funding. It describes the growth of AI organizations, increased conference attendance, class enrollment in universities, and the growing number of published articles throughout the 1970's as evidence of the growing support for this field in the academic and computer science communities.

The article examines the rise of ubiquitous computing. Describes the proliferation of smart phones, mobile computing devices and immersive technologies that produce "anywhere and everywhere data" and how such devices are becoming increasing entwined. Describes the local, temporal and contextual nature of generated data. Applies the post-cognitive framework from social science to information science in order to describe how information is transformed through interactions between media sources. Discusses how the various devices should complement each other as ubiquitous analytics works to leverage the shared data.

The Burrows-Wheeler Transform (BWT) is an invertible text transformation that permutes symbols of a text according to the lexicographical order of its suffixes. BWT is the main component of popular lossless compression programs (such as bzip2) as well as recent powerful compressed indexes (such as the r-index7), central in modern bioinformatics. The compressibility of BWT is quantified by the number r of equal-letter runs in the output. Despite the practical significance of BWT, no nontrivial upper bound on r is known. By contrast, the sizes of nearly all other known compression methods have been shown to be either always within a polylog n factor (where n is the length of the text) from z, the size of Lempel--Ziv (LZ77) parsing of the text, or much larger in the worst case (by an nε factor for ε > 0). In this paper, we show that r = O (z log² n) holds for every text. This result has numerous implications for text indexing and data compression; in particular: (1) it proves that many results related to BWT automatically apply to methods based on LZ77, for example, it is possible to obtain functionality of the suffix tree in O (z polylog n) space; (2) it shows that many text processing tasks can be solved in the optimal time assuming the text is compressible using LZ77 by a sufficiently large polylog n factor; and (3) it implies the first nontrivial relation between the number of runs in the BWT of the text and of its reverse. In addition, we provide an O (z polylog n)-time algorithm converting the LZ77 parsing into the run-length compressed BWT. To achieve this, we develop several new data structures and techniques of independent interest. In particular, we define compressed string synchronizing sets (generalizing the recently introduced powerful technique of string synchronizing sets11) and show how to efficiently construct them. Next, we propose a new variant of wavelet trees for sequences of long strings, establish a nontrivial bound on their size, and describe efficient construction algorithms. Finally, we develop new indexes that can be constructed directly from the LZ77 parsing and efficiently support pattern matching queries on text substrings. [ABSTRACT FROM AUTHOR]

The author writes about the importance of effectively communicating the broad and impactful aspects of computer science, moving beyond technical jargon to engage both educated non-experts and the general public. This involves creating concise "elevator speeches" and utilizing opportunities to bridge the gap in understanding terms like "artificial intelligence" (AI) and "machine learning." He feels that public engagement, such as interacting with journalists, giving interviews, and writing opinion articles, is crucial to demonstrate how computer science can address complex societal issues as well as secure support for the field, and that active participation in public engagement enhances the field's visibility, attracts diverse students, and safeguards its future, particularly in addressing concerns about AI ethics and workforce effects.

The article focuses on how revisiting key algorithms from computing history can unlock the hidden efficiency in computer science problems. The author discusses the shortest-path problem that has been long-standing, explores the use of the Bellman-Ford algorithm, and examines the work of Aaron Bernstein, Danupon Nanongkai, and Christian Wulff-Nilsen.

This article reflects on the author’s experiences as a black woman in the field of computing science. Topics include her educational experience in computing science, her personal communities’ support of her throughout her education, and how her experiences lead to her Science Everywhere project which encourages learners to think about STEM in all aspects of their daily lives.

This article investigates the current state of informatics higher education in Europe by utilizing the Informatics Europe Higher Education (IEHE) data portal. First, the article provides a detailed look at the IEHE data portal. Then the article provides a case study comparing informatics higher education at applied sciences universities compared to traditional research universities in five selected European countries using data providing in the portal.

Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. Given a set of points S and a radius parameter r > 0, the r-near neighbor (r-NN) problem asks for a data structure that, given any query point q, returns a point p within distance at most r from q. In this paper, we study the r-NN problem in the light of individual fairness and providing equal opportunities: all points that are within distance r from the query should have the same probability to be returned. The problem is of special interest in high dimensions, where Locality Sensitive Hashing (LSH), the theoretically leading approach to similarity search, does not provide any fairness guarantee. In this work, we show that LSH-based algorithms can be made fair, without a significant loss in efficiency. We propose several efficient data structures for the exact and approximate variants of the fair NN problem. Our approach works more generally for sampling uniformly from a subcollection of sets of a given collection and can be used in a few other applications. We also carried out an experimental evaluation that highlights the inherent unfairness of existing NN data structures. [ABSTRACT FROM AUTHOR]

The article presents the results of a study which investigated the correlation between the acceptance rate and impact rating of conference papers in the field of computer science. The papers with the highest impact ratings were found to be associated with highly selective conferences, defined as those which rejected between 70 and 85 percent of papers submitted. Such papers, on average, had higher impact ratings than papers which were published in journals without being presented at conferences. A rejection rate of 85 percent or more tended to suppress submission levels and reduce impact factors, while an acceptance rate over 30 percent was associated with less prestigious conferences.

The article explores Propositional Satisfiability (SAT), described by the authors as a cornerstone of computational complexity theory. Particular focus is given to how it has become a central target problem for solving hard computational problems in practice. Other topics discussed include how initial progress was made in SAT solving in the early 1990s and details on other eras of practical SAT solving.

In this article, various experts on computer science (CS) offer guides relating to the best of CS research. Particular focus is given to how to determine what papers are worth taking the time to read. Additional topics discussed include the ACM (Association for Computing Machinery), how datacenters are changing the way Web servers are designed and the notion of Network Functions Virtualization (NFV).

The article discusses the deployment of machine learning technology in production environments. The authors describe the algorithms which constitute and shape machine learning protocols with a focus on papers on subjects including the MauveDB project to integrate machine learning technology into relational databases, scalable response prediction for online advertising, and optimization of neural network queries for object detection in video streams.

An interview with Association for Computing Machinery (ACM) fellow Dana Stewart Scott who discusses various topics including his career involving the fields of computing science, automata theory, and the theory of programming languages. Scott's receipt of the ACM's A.M. Turing Award with colleague Michael Rabin in 1976 is mentioned, along with Scott's education, his involvement with mathematical logic, and his work at the University of Chicago and the University of California, Berkeley.

The article discusses the publication process for academic papers in computer science (CS) and provides a proposal for CSPub (clean-slate or computer science publication), an open-access publication system. The author identifies problems which he believes could be addressed by CSPub including low acceptance rates, the resubmission of rejected papers, and short incremental work which is published due to the demands of promotion and tenure systems.

The article discusses the status of research papers published by computer science (CS) conferences, as compared with those published in CS journals. Debate has occurred in relation to the proper way in which to qualify the research presented in a paper. Problems exist in determining the quality of research in various journals due to the wide array of publication opportunities available. A scale that has been created to measure the quality of conference papers in a variety of ways, such as citations and rejection rates, is discussed.

The author discusses collusion rings in computer science research, and his experiences with and knowledge of attempts to undermine peer-review of computer science conference publications. According to the author, collusion rings go beyond the computer architecture field. The author describes the peer-review process, how a collusion ring works, and outlines how the computer research field should respond.

The article presents information on self-plagiarism in computer science. Students submit assignments inherited from their friends, online paper-mills provide term papers on popular topics, and occasionally researchers are found falsifying data or publishing the work of others as their own. Self-plagiarism occurs when authors reuse portions of their previous writings in subsequent research papers. Occasionally, the derived paper is simply a retitled and reformatted version of the original one, but more frequently it is assembled from bits and pieces of previous work. Incorporating texts or ideas from previously published work while unaware of the existence of that work. Incorporating texts or ideas from previously published work when writing to a community different from that in which the original work was published. Missing from the ACM and IEEE policy documents is any discussion of what the consequences of ignoring the rules and guidelines might be and whose responsibility it is to prevent plagiarized and self-plagiarized papers from being published. In contrast, most university course syllabi address the definition of plagiarism and who will look for it, as well as its potential consequences.

The article presents tips on academic publishing for computer scientists. Specific guides to publication for the NeurIPS and VLDB conference series are offered and "maximalist" and "perfectionist" strategies for publication are compared with respect to top-tier journals and the most prestigious conferences.

The article focuses on the Internet's essential simplicity. The authors discuss the fundamental Internet design choices that have been in place since the 1980s, examines the rationale behind these design choices in an effort to understand the "why, not how" of the Internet, and offers insights for all computer scientists. A "Brief Internet Timeline" is also provided.

The article provides a perspective on the use of algorithms in maintaining maximum flow through computing networks. Offers a critique of various max-flow theorems and algorithms. Discusses prior research into max-flow applications. Mentions the hope for future breakthroughs in developing scalable max-flow algorithms.

The authors present their thoughts about the significance of computer ethics and the construction and support of ethical computing cultures in an era of rapid technological innovations. The article revisits the "Menlo Report" from 2012, calls for codes of data science ethics, and research governance.

An excerpt from a speech delivered by computer scientist and computer science professor Donald Knuth at Stanford University on May 7, 2014, about computer science history is presented.

Monitoring and troubleshooting distributed systems are notoriously difficult; potential problems are complex, varied, and unpredictable. The monitoring and diagnosis tools commonly used today—logs, counters, and metrics—have two important limitations: what gets recorded is defined a priori, and the information is recorded in a component- or machine-centric way, making it extremely hard to correlate events that cross these boundaries. This paper presents Pivot Tracing, a monitoring framework for distributed systems that addresses both limitations by combining dynamic instrumentation with a novel relational operator: the happened-before join. Pivot Tracing gives users, at runtime, the ability to define arbitrary metrics at one point of the system, while being able to select, filter, and group by events meaningful at other parts of the system, even when crossing component or machine boundaries. Pivot Tracing does not correlate cross-component events using expensive global aggregations, nor does it perform offline analysis. Instead, Pivot Tracing directly correlates events as they happen by piggybacking metadata alongside requests as they execute. This gives Pivot Tracing low runtime overhead—less than 1% for many cross-component monitoring queries. [ABSTRACT FROM AUTHOR]

The article offers advice on how to make the field of computing more inclusive. Particular focus is given to how this relates to the work of the Association for Computing Machinery (ACM). Additional topics discussed include making technology accessible for people with disabilities, SIGCHI, the ACM Special Interest Group on Computer-Human Interaction, and a telepresence robots.

The article discusses the factors that affect the sharing of research artifacts relating to computer systems according to the authors. Topics covered include the importance of sharing research artifacts for repeatability and benefaction, the research studies the evaluated the willingness of computer science researchers in sharing code and data, and details relating to the three measures of weak repeatability determined by the authors.

The article discusses hybrid computation systems involving satisfiability (SAT) solving and computer algebra systems (CAS) that combine mathematical algorithms and efficient search and learning processes.

The author discusses the significance of total-system analysis in computer science, particularly trust in total-system analysis and the difficulty in achieving such trust and assurance. It examines artificial intelligence, cryptography, and multilevel security. The article also examines hierarchically layered designs and methods.

The author presents an argument that the field of computer science should move away from its use of conferences as a venue for the primary publication of research papers, and adopt an approach more in line with that of other scholarly disciplines, which would involve the use of peer-reviewed journals as the primary venue for publication of original research, and conferences as a forum for professional discussions and networking.

The article describes several achievements in the field of theoretical computer science (TCS) and computer research in Latin America. It discusses several areas of research that were developed by regional conferences including LATIN, LAGOS, and Latincrypt. The article discusses research including graph theory, pattern matching and information retrieval, and algorithms.

The article examines alleged trends in European computer science research. The relative rates of publication and citation of computer science research articles across Europe, North America, and Asia are compared along with relative rates of collaborative and independent research and alleged asymmetry of benefits derived from collaborative research is described.

The article discusses the importance of performance measurements in improving the quality of systems being measured and the developers' intuition. Topics include the lack of performance evaluation education and widespread agreement on how to measure performance within the computer science industry, the importance of understanding the system's performance as well as why it performs that way, and the application of the scientific method to improve intuition about systems.

The article discusses the computer programming language known as Go, which was created at the high technology firm Google in 2007, and open source released in 2009. It examines the decision making processes concerning the design and success of Go, how Go treats language features, and the March 2022 release of Go 1.18.

This article reports that research conferences are often the most desirable venues for presenting research results. For academic computer scientists and engineers, preferring conferences over journals is so common that they even lobby administrators to ensure that conference papers can be viewed in the same light as journal papers in other fields. Hence, the health of conferences is vital to the computer science research mission. One conventional indication of health is the number of submissions and the acceptance rate at the conference. Calls for papers often include encouraging words for big idea or new direction papers. The problem is that reviewers see so many regular papers it is just too difficult to switch gears and be more understanding when evaluating bolder papers with holes in arguments or missing measurements. Program committees typically start with a ranked list of papers based on the average of numerical ratings in order to cope with the large number of submissions. Big idea papers are sure to get some poor evaluations, which cause them to drop down the list.