Shielding applications from an untrusted cloud with Haven Baumann et al. OSDI 2014 Our objective is to run existing server applications in the cloud with a level of trust and security roughly equivalent to a user operating their own hardware in a locked cage at a colocation facility. We're all familiar with the idea of … Continue reading Shielding applications from an untrusted cloud with Haven
Month: June 2016
IX: A protected dataplane operating system for high throughput and low latency
IX: A Protected Dataplane Operating System for High Throughput and Low Latency Belay et al. OSDI 2014 This is the second of Simon Peter's recommended papers in the 'Data Center OS Design' Research for Practice guide. Like Arrakis, IX splits the operating system into a control plane and data plane for networking. To quote Simon … Continue reading IX: A protected dataplane operating system for high throughput and low latency
Arrakis: the operating system is the control plane
Arrakis: The Operating System is the Control Plane - Peter et al. OSDI 2014 ACM Queue just introduced their "Research for Practice" series with Peter Bailis. Each edition contains 'expert curated guides to the best of CS research,' and in the first instalment Simon Peter selects a set of papers on data-center operating system trends, … Continue reading Arrakis: the operating system is the control plane
Identifying and quantifying architectural debt
Identifying and quantifying architectural debt - Xiao et al., ICSE 2016 (Update: thanks to Lu Xiao for providing an open access version of this paper, the link above has now been updated to point to it.) So finally we have arrived at Xiao et al.'s 2016 ICSE paper (see the write-ups on Design Rule Spaces … Continue reading Identifying and quantifying architectural debt
Hotspot Patterns: The formal definition and automatic detection of architecture smells
Hotspot Patterns: The formal definition and automatic detection of architecture smells - Mo et al. International Conference on Software Architecture, 2015 Yesterday we looked at Design Rule Spaces (DRSpaces) and how some design rule spaces seem to account for large numbers of the error-prone files within a project. Today's paper brings us up to date … Continue reading Hotspot Patterns: The formal definition and automatic detection of architecture smells
Design Rule Spaces: A new form of architectural insight
Design Rule Spaces: A new form of architectural insight - Xiao et al. ICSE '14 Continuing the theme of looking at ICSE 2016 papers, I want to share with you some interesting work by Xiao et al. on "Identifying and quantifying architectural debt." That paper however draws heavily on two previous works that it makes … Continue reading Design Rule Spaces: A new form of architectural insight
On the “naturalness” of buggy code
On the 'naturalness' of buggy code - Ray, Hellendoorn, et al. ICSE 2016 Last week we looked at a simpler approach to building static code checkers that by understanding less about the overall code structure and just focusing in on the things that really mattered was able to produce competitive results from very small checker … Continue reading On the “naturalness” of buggy code
BigDebug: Debugging primitives for interactive big data processing in Spark
BigDebug: Debugging primitives for interactive big data processing in Spark - Gulzar et al. ICSE 2016 BigDebug provides real-time interactive debugging support for Data-Intensive Scalable Computing (DISC) systems, or more particularly, Apache Spark. It provides breakpoints, watchpoints, latency monitoring, forward and backward tracing, crash monitoring, and a real-time fix-and-resume capability. The overheads are low for … Continue reading BigDebug: Debugging primitives for interactive big data processing in Spark
From Aristotle to Ringelmann
From Aristotle to Ringelmann: A large-scale analysis of team productivity and coordination in open-source software projects - Scholtes et al. ICSE 2016 A slightly different flavour of papers this week as we dip into the ICSE 2016 conference proceedings. We kick things off with a study looking at the effect of development team size on … Continue reading From Aristotle to Ringelmann
Semi-supervised sequence learning
Semi-supervised sequence learning - Dai & Le, NIPS 2015. The sequence to sequence learning approach we looked at yesterday has been used for machine translation, text parsing, image captioning, video analysis, and conversational modeling. In Semi-supervised sequence learning, Dai & Le use a clever twist on the sequence-to-sequence approach to enable it to be used … Continue reading Semi-supervised sequence learning
the morning paper 