The Dawn of Fully Automated Contract Drafting: Machine Learning Breathes New Life Into a Decades-Old Promise

Technological advances within contract drafting software have seemingly plateaued. Despite the decades-long hopes and promises of many commentators, critics doubt this technology will ever fully automate the drafting process. But, while there has been a lack of innovation in contract drafting software, technological advances have continued to improve contract review and analysis programs. “Machine learning,” the leading innovative force in these areas, has proven incredibly efficient, performing in mere minutes tasks that would otherwise take a team of lawyers tens of hours. Some contract drafting programs have already experimented with machine learning capabilities, and this technology may pave the way for the full automation of contract drafting. Although intellectual property, data access, and ethical obstacles may delay complete integration of machine learning into contract drafting, full automation is likely still viable

Technological Evolution in Software Engineering

In all software development processes, the software must evolve in response to its environment or user needs to maintain satisfactory performance. If software doesn’t support change, it gradually becomes useless. With many organizations today, being software-centric organizations, this has huge implications for their business: evolve your software, or risk your software becoming gradually useless, and therefore, your entire business. Technology Evolution is a highly relevant subject, Intel’s business model for the last 50 years, has been that of Moore’s Law, a hardware centric Technology Evolution model. As a Software Engineer at Intel, our business group faces a similar issue, we must continually adapt, and evolve our software, in response to our customer’s needs, and current technology trends, if we don’t evolve our software, our competitors will evolve theirs faster, and our business group, will gradually cease to exist, without competitive, and evolving software. The software evolution phenomenon was first identified in the late 60s though not termed as such till 1974. The goal of this article, is to explore the current literature on software evolution, and its impacts on software development activities, and software organizations. As a manager, and practicing Software Engineer, software evolvability, the ability, inter alia, for responsiveness and timely implementation of needed changes, will play an ever increasing more critical role in ensuring the survival of a society ever more dependent on computers

Organization and management of ATLAS software releases

International audienceATLAS is one of the largest collaborations ever undertaken in the physical sciences. This paper explains how the software infrastructure is organized to manage collaborative code development by around 300 developers with varying degrees of expertise, situated in 30 different countries. We will describe how the succeeding releases of the software are built, validated and subsequently deployed to remote sites. Several software management tools have been used, the majority of which are not ATLAS specific; we will show how they have been integrated. ATLAS offline software currently consists of about 2 MSLOC contained in 6800 C++ classes, organized in almost 1000 packages

Autonomous service composition in symbiotic networks

Part 2: PhD Workshop: Autonomic Network and Service ManagementInternational audienceTo cope with the ever-growing number of wired and wireless networks, we introduce the notion of so-called symbiotic networks. These networks seamlessly operate across layers and over network boundaries, resulting in improved scalability, dependability, and energy efficiency. This particular Ph.D. research focuses on software services operating in such symbiotic networks. When two or more networks merge, the services provided on them may be combined into a service composition that is much more than the sum of its parts. Driven by two distinct use cases, we aim to enable fully autonomous service composition and resource provisioning. For the first use case, an in-building over-the-top service platform, we describe a software architecture and a set of generic resource provisioning algorithms. The second use case, which focuses on wireless body area networks, will allow us to expand our research domain into highly dynamic symbiotic network environments, where services appear and disappear more frequently

Organization and management of ATLAS offline software releases

ATLAS is one of the largest collaborations ever undertaken in the physical sciences. This paper explains how the software infrastructure is organized to manage collaborative code development by around 300 developers with varying degrees of expertise, situated in 30 different countries. ATLAS offline software currently consists of about 2 million source lines of code contained in 6800 C++ classes, organized in almost 1000 packages. We will describe how releases of the offline ATLAS software are built, validated and subsequently deployed to remote sites. Several software management tools have been used, the majority of which are not ATLAS specific; we will show how they have been integrated

A Survey of Adaptive Resonance Theory Neural Network Models for Engineering Applications

This survey samples from the ever-growing family of adaptive resonance theory (ART) neural network models used to perform the three primary machine learning modalities, namely, unsupervised, supervised and reinforcement learning. It comprises a representative list from classic to modern ART models, thereby painting a general picture of the architectures developed by researchers over the past 30 years. The learning dynamics of these ART models are briefly described, and their distinctive characteristics such as code representation, long-term memory and corresponding geometric interpretation are discussed. Useful engineering properties of ART (speed, configurability, explainability, parallelization and hardware implementation) are examined along with current challenges. Finally, a compilation of online software libraries is provided. It is expected that this overview will be helpful to new and seasoned ART researchers

How, What, Where, and Why to Open Source Small Satellite Software

How do you open source small satellite software? What are the expected costs, obstacles, and benefits? Why would you even want to release your software to the world? Is it safe to use open source software? Open source software like Ball Aerospace COSMOS fills an important need for SmallSat missions where spending the budget for a traditional ground system would be more than the full cost of the satellite. However, nothing is ever truly free and there are a lot of misunderstandings about open source software in the Aerospace industry. This presentation will answer those questions while discussing the specific choices that were made in open sourcing the Ball Aerospace COSMOS Command and Control System. Additionally, this presentation will discuss the adoption of COSMOS since it was open sourced 4 years ago and where it is going in the future