Abstract
The present Special Issue of the Journal of Logical and Algebraic Methods in Programming was planned as a tribute to Jose Manuel Esgalhado Valenca on the occasion of his Jubilation. A tribute to a professor, in the deepest sense of the word, a colleague and a friend, but above all to a long and inspiring academic journey that has so profoundly shaped the development of Informatics as a scientific area in Portugal. A scientific area that, as he taught us, needs to be understood broadly: not only as an independent research domain, but also as an educational pillar, a strategy for social and economic development, a foundation for a multifaceted professional career. This preface introduces some steps of such a journey. The Special Issue features a selection of scientific papers written by his collaborators, colleagues and friends, covering the different areas Jose Valenca helped to launch and consolidate in Portugal, namely computational logic, verification and mechanized reasoning, and information security. (c) 2022 Published by Elsevier Inc.

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The Communications website, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications , we'll publish selected posts or excerpts. twitter Follow us on Twitter at http://twitter.com/blogCACM http://cacm.acm.org/blogs/blog-cacm Carlos Baquero offers guidance on how to decide where to publish one's paper.

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Carlos Baquero on whether using artificial intelligence provides an unfair advantage to writers.

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Carlos Baquero and Rosa Cabecinhas consider how readers make assumptions about authors’ roles and relative contributions when reading papers. It is not unexpected that when reading papers, readers also make simplifications and have assumptions about author roles and relative contributions. Experts also observed that the success of a new work depends not only on its factual quality, but on the prior recognition of the author and its institution. Work done at more prestigious departments can diffuse more rapidly through the science networks. The bias that occurs both on author and institution recognition is now well-known and a justification for blind review mechanisms.

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Many techniques have contributed to the advancement of automated program repair, such as: generate and validate approaches, constraint-based solvers and even neural machine translation. Simultaneously, artificial intelligence has allowed the creation of general-purpose pre-trained models that support several downstream tasks. In this paper, we describe a technique that takes advantage of a generative model - CodeGPT - to automatically repair buggy programs by making use of its code completion capabilities. We also elaborate on where to perform code completion in a buggy line and how we circumvent the open-ended nature of code generation to appropriately fit the new code in the original program. Furthermore, we validate our approach on the ManySStuBs4j dataset containing real-world open-source projects and show that our tool is able to fix 1739 programs out of 6415 - a 27% repair rate. The repaired programs range from single-line changes to multiple line modifications. In fact, our technique is able to fix programs which were missing relatively complex expressions prior to being analyzed. In the end, we present case studies that showcase different scenarios our technique was able to handle.

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The worldwide Web has dramatically evolved in recent years. Web pages are dynamic, expressed by programs written in common programming languages given rise to sophisticated Web applications. Thus, Web browsers are almost operating systems, having to interpret/compile such programs and execute them. Although JavaScript is widely used to express dynamic Web pages, it has several shortcomings and performance inefficiencies. To overcome such limitations, major IT powerhouses are developing a new portable and size/load efficient language: WebAssembly. In this paper, we conduct the first systematic study on the energy and run-time performance of WebAssembly and JavaScript on the Web. We used micro-benchmarks and also real applications in order to have more realistic results. Preliminary results show that WebAssembly, while still in its infancy, is starting to already outperform JavaScript, with much more room to grow. A statistical analysis indicates that WebAssembly produces significant performance differences compared to JavaScript. However, these differences differ between micro-benchmarks and real-world benchmarks. Our results also show that WebAssembly improved energy efficiency by 30%, on average, and showed how different WebAssembly behaviour is among three popular Web Browsers: Google Chrome, Microsoft Edge, and Mozilla Firefox. Our findings indicate that WebAssembly is faster than JavaScript and even more energy-efficient. Additionally, our benchmarking framework is also available to allow further research and replication.