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

Advanced Cloud Privacy Threat Modeling

Privacy-preservation for sensitive data has become a challenging issue in cloud computing. Threat modeling as a part of requirements engineering in secure software development provides a structured approach for identifying attacks and proposing countermeasures against the exploitation of vulnerabilities in a system . This paper describes an extension of Cloud Privacy Threat Modeling (CPTM) methodology for privacy threat modeling in relation to processing sensitive data in cloud computing environments. It describes the modeling methodology that involved applying Method Engineering to specify characteristics of a cloud privacy threat modeling methodology, different steps in the proposed methodology and corresponding products. We believe that the extended methodology facilitates the application of a privacy-preserving cloud software development approach from requirements engineering to design

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

Taming the cloud: Safety, certification and compliance for software services - Keynote at the Workshop on Engineering Service-Oriented Applications (WESOA) 2011

The maturity of IT processes, such as software development, can be and is often certified. Current trends in the IT industry suggest that software systems in the future will be very different from their counterparts today, with an increasing adoption of the Service-Oriented Architecture (SOA) design pattern and the deployment of Software-as-a-Service (SaaS) on Cloud infrastructures. In this talk we discuss some issues surrounding engineering Software Services for Cloud infrastructures and highlight the need for enhanced control, service-level agreement and compliance mechanisms for Software Services. Cloud Infrastructures and Service Mash-ups

Models in the Cloud: Exploring Next Generation Environmental Software Systems

There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science

A proposed case for the cloud software engineering in security

This paper presents Cloud Software Engineering in Security (CSES) proposal that combines the benefits from each of good software engineering process and security. While other literature does not provide a proposal for Cloud security as yet, we use Business Process Modeling Notation (BPMN) to illustrate the concept of CSES from its design, implementation and test phases. BPMN can be used to raise alarm for protecting Cloud security in a real case scenario in real-time. Results from BPMN simulations show that a long execution time of 60 hours is required to protect real-time security of 2 petabytes (PB). When data is not in use, BPMN simulations show that the execution time for all data security rapidly falls off. We demonstrate a proposal to deal with Cloud security and aim to improve its current performance for Big Data

Feature placement algorithms for high-variability applications in cloud environments

While the use of cloud computing is on the rise, many obstacles to its adoption remain. One of the weaknesses of current cloud offerings is the difficulty of developing highly customizable applications while retaining the increased scalability and lower cost offered by the multi-tenant nature of cloud applications. In this paper we describe a Software Product Line Engineering (SPLE) approach to the modelling and deployment of customizable Software as a Service (SaaS) applications. Afterwards we define a formal feature placement problem to manage these applications, and compare several heuristic approaches to solve the problem. The scalability and performance of the algorithms is investigated in detail. Our experiments show that the heuristics scale and perform well for systems with a reasonable load

ARTIST: Model-Based Stairway to the Cloud

International audienceOver the past decade, cloud services emerged as one of the most promising technologies in IT. Since cloud computing allows improving the quality of software and, at the same time, aims at reducing costs of operating software and hardware, more and more software is delivered as a service in the cloud. However , moving existing software applications to the cloud and making them behave as software as a service is still a major challenge. In fact, in addition to technical aspects, business aspects also need to be considered. The ARTIST EU project (FP7) proposes a comprehensive model-based modernization approach, covering both business and technical aspects, to cloudify already existing software. In particular , ARTIST employs MDE techniques to automate the reverse engineering and forward engineering phases in a way that modernized software truly benefits from targeted cloud environments. In this paper we describe the overall ARTIST approach and present several lessons learned

Evolution of Software Engineering in the Changing Scenario of Modern Hardware Architecture, Semantic Web and Cloud Computing Platform

Traditional way of software engineering is no longer fully suitable in the changing scenario of modern hardwareand software architecture of parallel and distributed computing on Semantic web and Cloud computing platform. A parallelhardware architecture can support high performance computing but needs changes in programming style. Also the capabilityof Semantic web can link everything on the internet making an interoperable intelligent system. And with this capabilitymany beneficial business models like Web services and Cloud computing platform have been conceptualized. Cloudcomputing is the most anticipated future trend of computing. These changes in hardware and software architecture means weneed to re-visit the traditional software engineering process models meant for a single computer system. This paper firstsurveys the evolution of hardware architecture, newer business models, newer software applications and then analyses theneed for changes in software engineering process models to leverage all the benefits of the newer business models. Thispaper also emphasizes the vulnerability of the web applications and cloud computing platform in terms of risk managementof web applications in general and privacy and security of customer information in shared cloud platform which maythreaten the adoption of the cloud platform.Keywords/Index Terms— Agile Process Model , Cloud Computing Platform, Privacy and Security Issues, RiskManagement, Semantic Web, Software Evolution