Showstoppers for Continuous Delivery in Small Scale Projects

Small scale projects outsourced to consultants provide their own difficulties when compared to more standard software development. Some of these problems are a lack of infrastructure and customers inexperienced with software development. This thesis is looking at the possibility of implementing continuous delivery in such an environment. The concrete problems are small projects with very little room for experimentation. But also the inexperience in automated testing which is essential for efficient regression testing. This led this thesis in two directions. The first one is how can you create a situation where continuous delivery could be beneficial, where developers prefer writing automated test cases instead of performing Ad Hoc manual testing during development and relying on a larger testing phase towards the end, much like what is done in waterfall development. The solution is to perform more deliveries to the customer throughout the project, with the customer having the responsibility of providing feedback on these deliveries. For the developers to embrace automated testing, a shift in focus is needed, from functional testing through the GUI to smaller unit and integration tests that will be easier to write and maintain. The other direction is addressing the fact that there is very little to continuously deliver during early stages of development, which could essentially make up half the project length. But also that there are several small projects each year. Making configuration management a support function for projects allows for standardisation and sharing the cost between all the projects

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

Automation to Handle Customer Complaints in Banks Using BPM Tool

This project was implemented in a Leading Multinational Bank and Financial services corporation which concentrates on Consumer Banking, Corporate Banking, Finance and Insurance, Investment banking, mortgage loans, private banking, private equity, wealth management, credit cards and home equity products. This project was focused on developing a new customer centric application for automating Complaints mechanism throughout all platform. This project involved developing and testing the new application and focusing on being customer centric and to beat the growing demand of banking market

Cloud engineering is search based software engineering too

Many of the problems posed by the migration of computation to cloud platforms can be formulated and solved using techniques associated with Search Based Software Engineering (SBSE). Much of cloud software engineering involves problems of optimisation: performance, allocation, assignment and the dynamic balancing of resources to achieve pragmatic trade-offs between many competing technical and business objectives. SBSE is concerned with the application of computational search and optimisation to solve precisely these kinds of software engineering challenges. Interest in both cloud computing and SBSE has grown rapidly in the past five years, yet there has been little work on SBSE as a means of addressing cloud computing challenges. Like many computationally demanding activities, SBSE has the potential to benefit from the cloud; ‘SBSE in the cloud’. However, this paper focuses, instead, of the ways in which SBSE can benefit cloud computing. It thus develops the theme of ‘SBSE for the cloud’, formulating cloud computing challenges in ways that can be addressed using SBSE

Qualitative Analysis for Validating IEC 62443-4-2 Requirements in DevSecOps

Validation of conformance to cybersecurity standards for industrial automation and control systems is an expensive and time consuming process which can delay the time to market. It is therefore crucial to introduce conformance validation stages into the continuous integration/continuous delivery pipeline of products. However, designing such conformance validation in an automated fashion is a highly non-trivial task that requires expert knowledge and depends upon the available security tools, ease of integration into the DevOps pipeline, as well as support for IT and OT interfaces and protocols. This paper addresses the aforementioned problem focusing on the automated validation of ISA/IEC 62443-4-2 standard component requirements. We present an extensive qualitative analysis of the standard requirements and the current tooling landscape to perform validation. Our analysis demonstrates the coverage established by the currently available tools and sheds light on current gaps to achieve full automation and coverage. Furthermore, we showcase for every component requirement where in the CI/CD pipeline stage it is recommended to test it and the tools to do so

RADON: Rational decomposition and orchestration for serverless computing

Emerging serverless computing technologies, such as function as a service (FaaS), enable developers to virtualize the internal logic of an application, simplifying the management of cloud-native services and allowing cost savings through billing and scaling at the level of individual functions. Serverless computing is therefore rapidly shifting the attention of software vendors to the challenge of developing cloud applications deployable on FaaS platforms. In this vision paper, we present the research agenda of the RADON project (http://radon-h2020.eu), which aims to develop a model-driven DevOps framework for creating and managing applications based on serverless computing. RADON applications will consist of fine-grained and independent microservices that can efficiently and optimally exploit FaaS and container technologies. Our methodology strives to tackle complexity in designing such applications, including the solution of optimal decomposition, the reuse of serverless functions as well as the abstraction and actuation of event processing chains, while avoiding cloud vendor lock-in through models