Second International Workshop on Software Architecture and Metrics Florence, Italy, May 16, 2015 Submission deadline: January 23, 2015 http://www.sei.cmu.edu/community/sam2015/ Software engineers of complex software systems face the challenge of how best to assess the achievement of quality attributes and other key drivers, how to reveal issues and risks early, and how to make decisions about architecture and system evolution. There is an increasing need to provide ongoing quantifiable insight into the quality of the system being developed to manage the pace of software delivery and technology churn. Additionally, it is highly desirable to improve feedback between development and deployment through measurable means for intrinsic quality, value, and cost. While there is body of work focusing on code quality and metrics, their applicability at the design and architecture level and at scale are inconsistent and not proven.
For pioneering leadership in the development of innovative curricula in computer science, Dr. Mary Shaw of Carnegie Mellon University received the National Medal of Technology and Innovation from President Barack Obama during a White House ceremony in November 2014. The SATURN 2015 program committee is pleased to announce that Dr. Shaw will deliver a keynote presentation at SATURN 2015, which will be held at the Lord Baltimore Hotel in Baltimore, Maryland, April 27-30.
Software Engineering Institute (SEI) research forms the foundation for a new one-day course from the SEI, Big Data: Architectures and Technologies.
To learn more, see this article about the SEI big-data course on the SEI website.
The new big-data course, along with one-day courses on DevOps and technical debt, will be offered at SATURN 2015, which will be held in Baltimore, Maryland, April 27-30.
Minimum Viable Architecture
In his Introduction to Minimum Viable Architecture, Savita Pahuja at InfoQ recalls an older blog by Kavis Technology that described the role of agile methods as serving a balancing function between the minimum viable product and the minimum viable architecture. Below are several recent opinions on this topic and a project that is putting the theory into practice. Less is More with Minimalist Architecture: Ruth Malan and Dana Bredemeyer wrote in the October 2002 issue of IT Professional that you should "sort out your highest-priority architectural requirements, and then do the least you possibly can to achieve them!" Good Enough Is Good Enough: Minimum Viable Architecture in a Startup: In a presentation given at the San Francisco Startup CTO Summit, Randy Shoup encourages startups to ignore the advice he's been giving for a decade on building large-scale systems.
The Watson Explorer
The Watson Developer Cloud brings Watson to developers and the cognitive cloud to Internet applications. Watson offers a variety of services for building cognitive apps, including language identification and translation, interpreting meaning based on context, and communicating with people in their own styles. Here are some reviews and links to APIs and sample code.
IBM's Watson Supercomputer Gives Developers Access to Cognitive Cloud: George Lawton at TechTarget provides an early review of the Watson Explorer’s unified view of enterprise information. The cloud allows the technology to be accessible for a greater variety of applications and improves the scale and time to market of those applications.
IBM Debuts First Watson Machine-Learning APIs: Serdar Yegulalp at Java World previews the eight services that developers can access for building cognitive apps based on Watson’s machine intelligence service. He focuses on visualization rendering as the service least limited by data training.
Deep Neural Networks
“At some fundamental level, no one understands machine learning.” —Christopher Olah
“Neural networks are one of the most beautiful programming paradigms ever invented.” —Michael Nielsen
This week, we round up a few examples on deep neural networks (DNNs), a subfield of machine learning that deals with developing training algorithms and uses raw video and speech data as input.
Replicating Deep Mind: Kristjan Korjus is working on a project to reproduce the results of Playing Atari with Deep Reinforcement Learning, by Volodymyr Mnih and colleagues of DeepMind Technologies. Mnih et al. presented a deep learning model that used reinforcement learning to learn control policies from sensory input and outperformed human experts on three of seven Atari games.
Deep Learning, NLP, and Representations: Christopher Olah at Colah's Blog looks at deep learning from a perspective on natural-language processing and discusses how different DNNs designed for different language-processing tasks have learned the same things.
We at the SEI are excited about the Team Software Process (TSP) Symposium, which we are holding in Pittsburgh, Pa. November 3-6, 2014. The theme of the symposium is "Going Beyond Methodology to Maximize Performance."
By this, we mean that the technical program goes beyond the core methodology of TSP to encompass a broader range of complementary practices that contribute to peak performance on system and software projects.
As part of our strategy to expand the scope of the symposium and bring in more architectural thinking to those who have adopted TSP and are using it, we've added several architecture-related sessions to the technical program. We at the SEI have seen how successful combining TSP and architecture-centric engineering approaches can be in the project we undertook with Bursatec, the technology subsidiary of the Mexican stock exchange.
This blog post began as a mission to compare and contrast mobile wallet systems. Instead, it became a survey of why mobile wallets are not more popular. The reason is not that we’re lacking choice in the mobile wallet economy. We can choose from Amazon Wallet, Apple Pay, Coin, Google Wallet, LoopPay, and Verizon’s Softcard, among others.
Why Aren’t Mobile Wallets More Popular in the US? and The Future Of Mobile Digital Wallet Technology in the UK: Lindsay Konsko at NerdWallet speculates on why the United States lags other countries in adopting virtual wallet technology; then Kristopher Arcand at Forrester explains why the UK lags the US.
Why Mobile Wallets Are Failing and Will Keep Failing: Kyle Chayka at Pacific Standard Magazine maintains that mobile wallets won’t be universally accepted by smartphone users until they are universally accepted by merchants.