Communications of the ACM
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Why Is It Hard to Define Data Science?
Data science can be described as a science, as a research paradigm, as a research method, as a discipline, as a workflow, and…
From BLOG@CACM
Making Bad Decisions
In software engineering, many technical decisions are context-dependent, and there are often complex edge cases to consider.
From BLOG@CACM
High-Performance Mobile System-on-Chip Clusters
Simply stating the problem is not enough; it is necessary to look for a quick way out of the situation, relying on available resources.
From BLOG@CACM
Data Anonymization Using the Random Sum Method
The purpose of this blog post is to present an anonymization method that can be applied to the digital attributes of personal data.
From BLOG@CACM
Blockchain For What, Exactly?
Considering the real-world consequences of blockchain hype.
From BLOG@CACM
R&D or r&d: What's the Difference?
Research produces generalized knowledge; Development produces generalized functionality. Not all efforts that use research skills or that use development skills...
From BLOG@CACM
Log4j and the Thankless High-Risk Task of Managing Software Component Upgrades
Managing included versions of third-party software components too often puts developers in no-win situations.
From BLOG@CACM
Software Stories: Legal Trouble
Legal troubles represent another collection of potential pitfalls where developers often find themselves unprepared.
From BLOG@CACM
Cultivating Habits: -1 +2 for Researchers
The New Year is stereotypically the time when we resolve to start some good habits and get rid of some of the bad.
From BLOG@CACM
Framing the Description of the Shrinking Pipeline
The shrinking pipeline refers to the low percentages of women earning computer science academic degrees and holding faculty positions.12