Communications of the ACM
Latest Research
From Communications of the ACM
Technical Perspective: Analyzing Smart Contracts with MadMax
"MadMax: Analyzing the Out-of-Gas World of Smart Contracts," by Neville Grech et al., effectively discovers a new smart contract vulnerability, and proposes a detection...
From Communications of the ACM
MadMax: Analyzing the Out-of-Gas World of Smart Contracts
We identify gas-focused vulnerabilities and present MadMax: a static program analysis technique that automatically detects gas-focused vulnerabilities with very...
From Communications of the ACM
Technical Perspective: Two for the Price of One
"Lower Bounds for External Memory Integer Sorting via Network Coding" proves a remarkable connection between how efficiently computers can perform sorting and transmitting...
From Communications of the ACM
Lower Bounds for External Memory Integer Sorting via Network Coding
In this paper, we present a tight conditional lower bound on the complexity of external memory sorting of integers.
From Communications of the ACM
Technical Perspective: Progress in Spatial Computing for Flood Prediction
There are few algorithms for multi-flow graphs beyond flow accumulation. The authors of "Flood-Risk Analysis on Terrains" take a big step to fill this knowledge...
From Communications of the ACM
Flood-Risk Analysis on Terrains
In this paper, we study a number of flood-risk related problems, give an overview of efficient algorithms for them, as well as explore the efficacy and efficiency...
From Communications of the ACM
Technical Perspective: Computing the Value of Location Data
"Computing Value of Spatiotemporal Information," by Heba Aly et al., describes a technique for computing the monetary value of a person's location data for a potential...
From Communications of the ACM
Computing Value of Spatiotemporal Information
We investigate the intrinsic value of location data in the context of strong privacy, where location information is only available from end users via purchase. ...
From Communications of the ACM
Technical Perspective: Supporting Linear Algebra Operations in SQL
Do we need a completely new database system to support machine learning?
From Communications of the ACM
Scalable Linear Algebra on a Relational Database System
We show that by making just a few changes to a parallel/distributed relational database system, such a system can become a competitive platform for scalable linear...
From Communications of the ACM
Technical Perspective: Entity Matching with Magellan
Magellan's key insight is that a successful entity matching system must offer a versatile system building paradigm for entity matching that can be easily adapted...
From Communications of the ACM
Magellan: Toward Building Ecosystems of Entity Matching Solutions
Entity matching can be viewed as a special class of data science problems and thus can benefit from system building ideas in data science.
From Communications of the ACM
Technical Perspective: ASIC Clouds: Specializing the Datacenter
Can we build purpose-built, warehouse-scale datacenters customized for large-scale arrays of ASIC accelerators or, to use a term coined in the paper by Michael...
From Communications of the ACM
ASIC Clouds: Specializing the Datacenter for Planet-Scale Applications
This paper distills lessons from Bitcoin ASIC Clouds and applies them to other large scale workloads, showing superior TCO (total cost of ownership) versus CPU...
From Communications of the ACM
Technical Perspective: Why 'Correct' Computers Can Leak Your Information
"Spectre Attacks: Exploiting Speculative Execution," by Paul Kocher, et al., reviews how speculative execution and caches can be exploited, presents specific exploits...
From Communications of the ACM
Spectre Attacks: Exploiting Speculative Execution
This paper describes practical attacks that combine methodology from side-channel attacks, fault attacks, and return-oriented programming that can read arbitrary...
From Communications of the ACM
Technical Perspective: Algorithm Selection as a Learning Problem
"Data-Driven Algorithm Design," by Rishi Gupta and Tim Roughgarden, addresses the issue that the best algorithm to use for many problems depends on what the input...
From Communications of the ACM
Data-Driven Algorithm Design
We model the problem of identifying a good algorithm from data as a statistical learning problem.
From Communications of the ACM
Technical Perspective: Fake 'Likes' and Targeting Collusion Networks
"Measuring and Mitigating OAuth Access Token Abuse by Collusion Networks," by Shehroze Farooqi et al., explores a social-networking reputation manipulation ecosystem...
From Communications of the ACM