ACM Computing Reviews
ACM Computing Reviews is an ACM monthly journal produced in collaboration with Thinkcloud.
The ACM Computing Reviews database is the largest and most comprehensive database of reviews covering the computing literature, providing practitioners, researchers, educators, and students with an unparalleled resource that provides a unique roadmap to the vast ocean of scholarly and practical information in one of the fastest moving fields of knowledge today.
Every year, over 8,000 books, 2,500 dissertations, 20,000 journal articles from over 750 journal titles and over 30,000 conference papers from over 500 conferences are published in the field of computing. This does not include the thousands of master's theses, technical reports, technical manuals, working papers, blog entries, presentations, or other materials published each year. Filtering this vast quantity of information is difficult and there are very few high quality resources available to help individuals to do this well. ACM Computing Reviews is such a resource.
The ACM Computing Reviews database is an essential companion product to the ACM Digital Library. Both databases are closely related and have been integrated to connect reviews to full text wherever possible.
The ACM Computing Reviews contains the following:
- The most comprehensive coverage of the computing literature
- Expert reviews from over 1,000 subject matter
- Approximately 30,000 reviews covering books, journal articles, and conference proceedings from different publishers and hundreds of thousands of publications
- Commentary from authors and reviewers of reviewed materials
- Powerful search tools
- Searchable archives dating back to 1985
- New reviews published on site daily
- Alerting profiles
- RSS feeds of partial reviews
- Fully indexed and integrated with the ACM Digital Library full text database and Guide to Computing Literature bibliographic database
- Affordable pricing
- Simplified IP authentication for Institutional subscribers
- Edited by a panel of leading experts
To gain a better understanding of the ACM Computing Reviews functionality, click on the PDF Tip Sheet for any section below. For an overall instructional quide, read the QUICK START Tip sheet or please go directly to the ACM Computing Reviews site at:
ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.
Written by leading domain experts for software engineers, ACM Case Studies provide an in-depth look at how software teams overcome specific challenges by implementing new technologies, adopting new practices, or a combination of both. Often through first-hand accounts, these pieces explore what the challenges were, the tools and techniques that were used to combat them, and the solution that was achieved.
Why I Belong to ACM
Hear from Bryan Cantrill, vice president of engineering at Joyent, Ben Fried chief information officer at Google, and Theo Schlossnagle, OmniTI founder on why they are members of ACM.