Intermittent computer users, generally unable to program, often need more flexibility than current applications can offer them. A first step to providing such flexibility is to consider the psychological issues underlying the users' needs and the communication of these needs. This thesis does this by exploring the possibility of "Automatic Programming" where users communicate their requirements and the computer generates programs to meet them.

The use of active compliance enables robots to carry out tasks in the presence of significant sensing and control errors. Compliant motions are quite difficult for humans to specify, however. Furthermore, robot programs are quite sensitive to details of geometry and to error characteristics and must, therefore, be constructed anew for each task. These factors motivate the need for automatic synthesis tools for robot programming, especially for compliant motion. This paper describes a formal approach to the synthesis of compliant motion strategies from geometric descriptions of assembly operations and explicit estimates of errors in sensing and control. A key aspect of the approach is that it provides correctness criteria for compliant motion strategies.

The lens design is a fundamental but challenging problem, while modern lens design processes still follow the classic aberration optimization theory and need preliminary designs and experienced optical engineers to control the optimization process constantly. In this thesis, we develop a differentiable ray-tracing model and apply it to automatic lens design. Our method can do ray-tracing and render images with high accuracy, with the power to use the back-propagated gradient to optimize optical parameters. Different from traditional optical design, we propose to use the rendered images as the training criteria. The rendering loss shows superior results in optimizing lenses while also making the task easier. To remove the requirements of preliminary design and constant operations in conventional lens design, we propose a curriculum learning method that starts from a small aperture and field-of-view(FoV), gradually increases the design difficulty, and dynamically adjusts attention regions of rendered images. The proposed curriculum strategies empower us to optimize complex lenses from flat surfaces automatically. Given an existing lens design and setting all surfaces flat, our method can entirely recover the original design. Even with only design targets, our method can automatically generate starting points with flat surfaces and optimize to get a design with superior optical performance. The proposed method is applied to both spheric and aspheric lenses, both camera and cellphone lenses, showing a robust ability to optimize different types of lenses. In addition, we overcome the memory problem in differentiable rendering by splitting the differentiable rendering model into two sub-processes, which allows us to work with megapixel sensors and downstream imaging processing algorithms.

In today’s technology driven society, software is becoming increasingly important in more areas of our lives. The domain of software extends beyond the obvious domain of computers, tablets, and mobile phones. Smart devices and the internet-of-things have inspired the integra- tion of digital and computational technology into objects that some of us would never have guessed could be possible or even necessary. Fridges and freezers connected to social media sites, a toaster activated with a mobile phone, physical buttons for shopping, and verbally asking smart speakers to order a meal to be delivered. This is the world we live in and it is an exciting time for software engineers and computer scientists. The sheer volume of code that is currently in use has long since outgrown beyond the point of any hope for proper manual maintenance. The rate of which mobile application stores such as Google’s and Apple’s have expanded is astounding. The research presented here aims to shed a light on an emerging field of research, called Genetic Improvement ( GI ) of software. It is a methodology to change program code to improve existing software. This thesis details a framework for GI that is then applied to explore fitness landscape of bug fixing Python software, reduce execution time in a C ++ program, and integrated into a live system. We show that software is generally not fragile and although fitness landscapes for GI are flat they are not impossible to search in. This conclusion applies equally to bug fixing in small programs as well as execution time improvements. The framework’s application is shown to be transportable between programming languages with minimal effort. Additionally, it can be easily integrated into a system that runs a live web service.

by Ma Wai Yan. / Includes bibliographical references / Thesis (M.Ph.)--Chinese University of Hong Kong, 1985

Typescript (photocopy). / Digitized by Kansas Correctional Industries

A recognition assistant will help reconstruct the design of a program, given only its source code. A design assistant will assist a programmer by detecting errors and inconsistencies in his design choices and by automatically making many straightforward implementation decisions. An optimization assistant will help improve the performance of programs by identifying intermediate results that can be reused. A debugging assistant will aid in the detection, localization, and repair of errors in designs as well as completed programs.

The goal of the Programmer's Apprentice project is to develop a theory of how expert programmers analyze, synthesize, modify, explain, specify, verify, and document programs. This research goal overlaps both artificial intelligence and software engineering. From the viewpoint of artificial intelligence, we have chosen programming as a domain in which to study fundamental issues of knowledge representation and reasoning. From the viewpoint of software engineering, we seek to automate the programming process by applying techniques from artificial intelligence.

Inspection methods are a kind of engineering problem solving based on the recognition and use of standard forms or cliches. Examples are given of program analysis, program synthesis and program validation by inspection. A formalism, called the Plan Calculus, is defined and used to represent programming cliches in a convenient, canonical, and programming-language independent fashion.

Thesis (M.S.)--Kutztown University of Pennsylvania, 1993. / Source: Masters Abstracts International, Volume: 45-06, page: 3185. Abstract precedes thesis title page as [2] preliminary leaves. Typescript. Includes bibliographical references (leaves 90-94).