The project investigated the advantages and disadvantages of Go while abooking system for Tieto was developed. The frameworks and APIs AngularJS,REST, JSON and mongoDB were used during the development of thebooking system. The result was a fully working stand-alone booking systemwith a login functionality. The back-end server was written in Go while thefront-end client was written in JavaScript using AngularJS. / Projektet undersökte fördelarna och nackdelar med Go medan ett bokningssystemför Tieto utvecklades. Under utvecklingen av bokningssystemet såanvändes ramverken och APIerna AngularJS, REST, JSON och mongoDB.Resultatet blev ett fullt fungerande fristående bokningssystem med supportför inloggning. Back-end servern var skriven i Go medan front-end klientenvar skriven i JavaScript med AngularJS.

Indiana University-Purdue University Indianapolis (IUPUI) / Current research in deep learning is primarily focused on using Python as a support language. Go, an emerging language, that has many benefits including native support for concurrency has seen a rise in adoption over the past few years. However, this language is not widely used to develop learning models due to the lack of supporting libraries and frameworks for model development. In this thesis, the use of Go for the development of neural network models in general and convolution neural networks is explored. The proposed study is based on a Go-CUDA implementation of neural network models called GoCuNets. This implementation is then compared to a Go-CPU deep learning implementation that takes advantage of Go's built in concurrency called ConvNetGo. A comparison of these two implementations shows a significant performance gain when using GoCuNets compared to ConvNetGo.

Описаны проблемы работы с ресурсами в крупных IT-компаниях и возможности применения облачных технологий для их решения. Исследованы существующие программные продукты для построения облачных платформ. Разработана и реализована архитектура продукта для работы с разными платформами виртуализации на основе существующего интерфейса взаимодействия OpenStack. / The problems of working with resources in large IT companies and the possibilities of using cloud technologies to solve them are described. The existing software products for building cloud platforms are investigated. The product architecture for working with different virtualization platforms based on the existing OpenStack interaction interface has been developed and implemented.

This project is about creating a Dashboard with suitable data models containing support ticket statistics for the company Sigma IT Consulting. The work flow used by Sigma today is to manually log in to the system to see the support ticket statistics, which can be a tedious and time consuming process. Furthermore, Sigma do not have any monitoring system for checking the health of their web application services. They have a need for an internal Dashboard containing this information with regularly updates. Our solution is to design suitable data models and implement them within a Dashboard application.

abstract: Graph theory is a critical component of computer science and software engineering, with algorithms concerning graph traversal and comprehension powering much of the largest problems in both industry and research. Engineers and researchers often have an accurate view of their target graph, however they struggle to implement a correct, and efficient, search over that graph. To facilitate rapid, correct, efficient, and intuitive development of graph based solutions we propose a new programming language construct - the search statement. Given a supra-root node, a procedure which determines the children of a given parent node, and optional definitions of the fail-fast acceptance or rejection of a solution, the search statement can conduct a search over any graph or network. Structurally, this statement is modelled after the common switch statement and is put into a largely imperative/procedural context to allow for immediate and intuitive development by most programmers. The Go programming language has been used as a foundation and proof-of-concept of the search statement. A Go compiler is provided which implements this construct. / Dissertation/Thesis / Masters Thesis Software Engineering 2018

Current research in deep learning is primarily focused on using Python as a support language. Go, an emerging language, that has many benefits including native support for concurrency has seen a rise in adoption over the past few years. However, this language is not widely used to develop learning models due to the lack of supporting libraries and frameworks for model development. In this thesis, the use of Go for the development of neural network models in general and convolution neural networks is explored. The proposed study is based on a Go-CUDA implementation of neural network models called GoCuNets. This implementation is then compared to a Go-CPU deep learning implementation that takes advantage of Go's built in concurrency called ConvNetGo. A comparison of these two implementations shows a significant performance gain when using GoCuNets compared to ConvNetGo.<br>

The goal of this study was to investigate how the use of language models in the context of code structure analysis could impact how developers manage code structure. To do this, a prototype tool GOSPLAT (GoLang Static Package Language-model Analysis Tool) was created. The objective was to, in a qualitative manner, find themes of both the strengths and shortcomings of GOSPLAT as well as the perceived need and willingness of a tool like this in a company setting. Methods used for this case study were primarily interviews and observations, where the researchers observed subjects when using the tool, as well as further investigating by conducting interviews at which they were more freely able to talk about their experiences. In this case study, both project managers and developers in a company participated. The results were mixed, with the solution both showing promising results for improvements in code quality, as well as limitations where it might have misled the developer. However, during the entire study, all subjects were adamant in their belief in a tool like GOSPLAT, showing genuine interest in incorporating such a tool into their workflow. In conclusion, a genuine need for tools like GOSPLAT was found to exist, and improvement areas were identified to enhance their effectiveness.

Decompilation or reverse compilation is the process of translating low-level machine-readable code into high-level human-readable code. The problem is non-trivial due to the amount of information lost during compilation, but it can be divided into several smaller problems which may be solved independently. This report explores the feasibility of composing a decompilation pipeline from independent components, and the potential of exposing those components to the end-user. The components of the decompilation pipeline are conceptually grouped into three modules. Firstly, the front-end translates a source language (e.g. x86 assembly) into LLVM IR; a platform-independent low-level intermediate representation. Secondly, the middle-end structures the LLVM IR by identifying high-level control flow primitives (e.g. pre-test loops, 2-way conditionals). Lastly, the back-end translates the structured LLVM IR into a high-level target programming language (e.g. Go). The control flow analysis stage of the middle-end uses subgraph isomorphism search algorithms to locate control flow primitives in CFGs, both of which are described using Graphviz DOT files. The decompilation pipeline has been proven capable of recovering nested pre-test and post-test loops (e.g. while, do-while), and 1-way and 2-way conditionals (e.g. if, if-else) from LLVM IR. Furthermore, the data-driven design of the control flow analysis stage facilitates extensions to identify new control flow primitives. There is huge potential for future development. The Go output could be made more idiomatic by extending the post-processing stage, using components such as Grind by Russ Cox which moves variable declarations closer to their usage. The language-agnostic aspects of the design will be validated by implementing components in other languages; e.g. data flow analysis in Haskell. Additional back-ends (e.g. Python output) will be implemented to verify that the general decompilation tasks (e.g. control flow analysis, data flow analysis) are handled by the middle-end. / <p>BSc dissertation written during an ERASMUS exchange from Uppsala University to the University of Portsmouth.</p>

Concurrency is generally considered to be difficult due to a lack of appropriate abstraction, rather than inherent complexity. Lock-based approaches to mutual exclusion are pervasive, despite the presence of models that are easier to understand, such as the message-passing model present in CSP (Communicating Sequential Processes). CSP provides a rich framework for building and reasoning about concurrent systems, but has historically required a change of programming language or paradigm in order to work with it. The Go programming language is a modern, imperative programming language that includes native support for processes and channels. The popularity of this language has grown and more and more people are being exposed to the fundamental ideas of CSP. There is a gap in the understanding of how a restrictive formal model can interact with and support the development of concurrent programs in a language such as Go. Through a series of case studies and analysis, we show how the CSP concurrency model can be used as the basis for the design of a concurrent system architecture without requiring the program to be written entirely as the composition of processes. It is also possible to use the CSP process algebra to build abstract models and use model-checking tools to verify properties of a concurrent system. These models can then be used to guide the decomposition of a system into a more fine-grained concurrent system. This thesis bridges the gap between the development of CSP-style concurrent software and the formal model of CSP. In particular, it shows how it is not necessary for a program or programming language to conform to rigid structure in order for CSP to be a useful tool for the development of reliable and easy to understand concurrent systems.

Att välja vilken eller vilka röststyrningstjänster man som företag vill stödja kan i dagens läge vara ett svårt val att göra. Det kan även var så att man inte har resurser att göra två olika implementationer. I den här undersökningen tittar vi på om det finns ett bra sätt att göra en implementation som kan hantera fler än en röststyrningstjänst. Tjänsterna vi har fokuserat på i undersökningen är Amazon Alexa och Google Assistant.