Non-functional requirements optimisation for multi-tier cloud applications: An early warning system case study

With the rapid development of science and technology, database programming technology has become more mature and perfect, and it has been widely used in the field of computer software engineering, laying a good foundation for the development of computer software engineering and the whole society. Based on this, this paper briefly introduces the database file generation process in computer software engineering, and then summarizes the database programming technology in computer software engineering. Based on this, it analyzes the importance of database programming technology in computer software engineering, discusses the application points of database programming technology in computer software engineering, and provides support for better application of database programming technology.

work of W. Edwards Deming has convinced industry that must first measure quality and then emphasise process to improve quality. In response to Deming's arguments and in light of perception that software industry is unable to produce quality products on schedule, and within budget, more software development organisations are now emphasising process measurement, monitoring, and assessment. This paper describes what is meant by software process and discusses an approach for its measurement and improvement. INTRODUCTION Unreliable software makes big news, from emergency services disasters to social security payment blunders. Improved software quality is essential to ensure reliable products and services, and gain customer satisfaction. While software development has existed for more than four decades, we failed so far to make as an industry and as an engineering discipline rather than craft. Developing reliable and usable software that is delivered on and within budget still represents difficult endeavour for many organisations. As role of software becomes increasingly critical for businesses as well as for human lives, problems caused by software products that are late, over budget, or that do not work, become magnified. If lives are lost or people inconvenienced due to incapable computer software, news media is there to make big stories. Organisations are realising that their fundamental problems is immaturity of their software process. Robert Lai (1993) proposes that process improvement is second maturity wave of software industry. He states that the first wave of software was developed using waterfall model in 1970's. Today we are Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 216 Software Management in midst of second wave maturity movement as we attempt to formally define development process and best ways to continuously improve it (Lai 1993). Taking lead in this area has been Watts Humphrey (Humphrey 1989, 1990, 1991), and Software Engineering Institute (SEI) at Carnegie Mellon University. SEI started in 1986 to develop process maturity framework to help organisations appraise maturity of their software process, and to provide guidance for organisations to improve their software process capability. A brief description of framework was released in September 1987, including maturity questionnaire. SEI evolved model and questionnaire into 5 -Level Capability Maturity Model (CMM) in 1991. In February 1993, released CMM version 1.1 (Paulk et al 1993). This paper discusses software process and describes capability maturity model (CMM). It also shows how CMM can be used as basis to measure maturity of software process of an organisation and plan its improvement. SOFTWARE QUALITY AND PROCESS IMPROVEMENT In his book Quality is Free Phil Crosby states that: Quality is free. It is not gift, is free. What cost money are unqualify of things all actions that involve not doing jobs right first time (Crosby 1980). If such statement is true for many disciplines, is particularly true for evidence is abundant in number of software products which exceeded their budget, were produced late, failed to satisfy user requirements, and are full of bugs. demand for improved software quality is increasing to ensure reliable products and services. benefits of improved quality comes in form of reduction in failure costs. For software projects failure costs include (DTI 1992): • costs of correcting defects, both before and after delivery • overruns against and budget • unnecessary high maintenance costs • indirect costs which users incur due to poor quality software link between process maturity and software quality is expressed in premise that The quality of software system is governed by quality of process used to develop and maintain it. One stumbling block to improving software quality seems to be that not enough attention is paid to overall development process itself. While software professionals typically devote their to developing, testing or documenting software products, no one has prime responsibility for improving software process. Experience has shown that if Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 Managing Systems 217 no one is working on software process, orderly improvement is unlikely. process certainly won't improve itself, rather, most likely, will deteriorate over time. Continuous improvement can occur only if process infrastructure is in place. Watts Humphrey argues in an early article published in Datamation, April 1989 that: Without work on process, there will be little or no progress in improving software. THE SOFTWARE PROCESS Adopting process view of software development represents revolutionary change in perspective. A process orientation to software development involves elements of structure, focus, measurement, ownership, skills, and supporting technology. In this section we investigate what is meant by software process. What Is Software Process According to Webster's dictionary, process is a system of operations in producing something .. series of actions, changes, or functions that achieve an end result. Chambers Concise Dictionary defines process as a series of actions or events .. sequence of operations or changes undergone. IEEE defines process as a sequence of steps performed for given purpose. In general business context, process is defined as a structured, measured set of activities designed to produce specified output for particular customer or market (Davenport 1993). These definitions put strong emphasis on HOW work is done, in contrast to product focus's emphasis on WHAT. Accordingly, process can be considered as a specific ordering of work activities across and place, with beginning, an end, and clearly identified inputs and outputs: structure for action. In this paper we will adopt following definitions quoted in (Humphrey 1990, Paulk et al 1993) are intended to encompass software throughout its life, which covers new development, enhancement, and repair. software process is The set of activities, methods, and practices used in production and evolution of software. software engineering process is The total set of software engineering activities needed to transform user's requirements into software. Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 218 Software Management People and Software Process Software development is still people-intensive activity. Talented people are most important element in any software organisation. Even if you get best people available, if they do not follow common process, if everyone wrote in different programming languages, used different conventions, or didn't co-ordinate their design and code changes with their peers, results will be chaos. Successful software organisations have learned that even best professionals need structured and disciplined environment in which to do cooperative work. Software organisations that do not establish such disciplines condemn their people to endless hours of repetitively solving technically trivial problems. obvious fact is that attracting best people is vital, but is also essential to support them with an effectively managed software process. Technology and Software Process Another myth is widespread belief that some technologically advanced tool or method will provide magic answer to software crisis. This is not only wrong, but is dangerous. Organisations which jumped on bandwagon of CASE tools, and ended up in failure and wasted and effort have learned their lesson hard way. Just ask yourself before introducing technology: What do I want to automate? In absence of defined, practised, and managed process, introducing automation can lead to increased chaos. There are several factors which limit effective use of software technology: an illdefined process, inconsistent process implementation, and poor process management. Software technology cannot be fully effective until these problems have been properly addressed. Need for Defined Process If no effort is made to define and enhance software development process across whole organisation, each software development project latches on to its own tools, methods, and practices with little guidance available on how to use them. This ad hoc approach will not be sufficient to tackle task of developing complex software systems. goal of software process management is to enable organisations to produce software that meets cost, schedules, and quality objectives. principles are same that underpins statistical process control-principles that have been successfully used in controlling scientific experiments and in high -volume manufacturing operations. Statistical concepts have been found to be just as applicable to software development as they are to production of manufactured goods such as motor cars. Applying such concepts will only be possible if there is defined and managed process. Software Process Models Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517

Software engineers have always been experimenting with various models in an endeavor to improve upon software processes. Recently, a new area of software process improvement through experience management has got attention of the software engineering community. Software developers are experimenting with experience management to improve software process. This chapter explores the role of experience management in mitigating the effects of software crisis and investigates the current state of EM in Indian software engineering environment. The chapter discusses the need and integration of knowledge and experience management practices in software engineering environments. The chapter begins with the discussion of the ills of software engineering, classically referred to as “software crisis,” like late delivery of the systems, ill-functionality, and cost overruns, and justifies how managing the knowledge and experience of software engineers and practitioners can ward off these evils. The chapter then discusses the models and methodologies for knowledge and experience management in software engineering. Finally, the chapter sheds light on the major works carried out in this area and suggests possible future research avenues in this domain.

Empathy, defined as the ability to understand and share others’ perspectives and emotions, is essential in software engineering (SE), where developers often collaborate with diverse stakeholders. It is also considered as a vital competency in many professional fields such as medicine, healthcare, nursing, animal science, education, marketing, and project management. Despite its importance, empathy remains under-researched in SE. To further explore this, we conducted a socio-technical grounded theory (STGT) study through in-depth semi-structured interviews with 22 software developers and stakeholders. Our study explored the role of empathy in SE and how SE activities and processes can be improved by considering empathy. Through applying the systematic steps of STGT data analysis and theory development, we developed a theory that explains the role of empathy in SE. Our theory details the contexts in which empathy arises, the conditions that shape it, the causes and consequences of its presence and absence. We also identified contingencies for enhancing empathy or overcoming barriers to its expression. Our findings provide practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

In various fields of computer science, rapidly growing hardware power, such as high-speed network, high-performance CPU, huge disk capacity, and large memory space, has been fruitfully harnessed. Examples of such usage are large scale data and web mining, grid computing, and multimedia environments. We propose that such rich hardware can also catapult software engineering to the next level. Huge amounts of software engineering data can be systematically collected and organized from tens of thousands of projects inside organizations, or from outside an organization through the Internet. The collected data can be analyzed extensively to extract and correlate multi-project knowledge for improving organization-wide productivity and quality. We call such an approach for software engineering Mega Software Engineering. In this paper, we propose the concept of Mega Software Engineering, and demonstrate some novel data analysis characteristic of Mega Software Engineering. We describe a framework for enabling Mega Software Engineering.KeywordsSoftware EngineeringSoftware EngineerSoftware ProjectCollaborative FilterGlobal Software DevelopmentThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Due to the high complexity and numerous abstract processes in the subject Software Engineering (SWE), both, challenges in teaching and in learning arise. The teaching of Software Engineering is attempted by a new didactic approach to convey a deeper understanding of the complexity and the processes of Software Engineering in the context of the course. The approach complements the classical ex-cathedra lecture with a seminar and a project phase, whereby the direct application of theoretical knowledge is achieved in real-world situations. In addition to the consolidation of factual knowledge, transferable skills, such as presentation, communication and teamwork skills, can be encouraged. The approach focuses on self-studying as well as collaborative learning. The knowledge gained from team working is multiplied by the Wiki and spread over the whole semester.

The pay-as-you-go model supported by existing cloud infrastructure providers is appealing to most application service providers to deliver their applications in the cloud. Within this context, elasticity of applications has become one of the most important features in cloud computing. This elasticity enables real-time acquisition/release of compute resources to meet application performance demands. In this thesis we investigate the problem of delivering cost-effective elasticity services for cloud applications. Traditionally, the application level elasticity addresses the question of how to scale applications up and down to meet their performance requirements, but does not adequately address issues relating to minimising the costs of using the service. With this current limitation in mind, we propose a scaling approach that makes use of cost-aware criteria to detect the bottlenecks within multi-tier cloud applications, and scale these applications only at bottleneck tiers to reduce the costs incurred by consuming cloud infrastructure resources. Our approach is generic for a wide class of multi-tier applications, and we demonstrate its effectiveness by studying the behaviour of an example electronic commerce site application. Furthermore, we consider the characteristics of the algorithm for implementing the business logic of cloud applications, and investigate the elasticity at the algorithm level: when dealing with large-scale data under resource and time constraints, the algorithm’s output should be elastic with respect to the resource consumed. We propose a novel framework to guide the development of elastic algorithms that adapt to the available budget while guaranteeing the quality of output result, e.g. prediction accuracy for classification tasks, improves monotonically with the used budget. We demonstrate the application of the framework by developing two elastic data mining algorithms as examples. Experimental evaluations have been performed using prediction accuracy as the quality measure on real datasets. The results show that both algorithms indeed exhibit consistent increase in quality.

Welcome to the International Conference on Software and Systems Process (ICSSP) held in Zurich, Switzerland, on June 2nd and 3rd, 2012. Having grown from a Software Process Workshop in 2005 to the International Conference on Software Process (ICSP) in 2007, and finally to the International Conference on Software and Systems Process (ICSSP) in 2011, this conference series has established its place in the software engineering community as a respected conference focusing on research and practice related to software and systems development process. Software and software systems development use processes as one major means for achieving and ensuring the quality of the final product. This leads to specific challenges regarding software processes such as simplicity, adaptability, standard conformance, the coordination of multiple domains and lifecycles, etc. Processes from other domains (e.g., health care, manufacturing, business, aerospace, automotive systems, and others) face similar challenges. Yet, they share interesting similarities with and differences to software processes. The question is: How can we in the software domain learn from other domains to meet our software process engineering challenges? The ICSSP conferences hence connect the traditional software and systems process community with outside views and insights, broadening its scope of software development processes to system development and explicitly including processes of other domains such as health care, business, and manufacturing. By sharing process development theories and practices from such domains, ICSSP 2012 is investigating novel solutions to today's process challenges. Correspondingly, the main theme of ICSSP 2012 is Beyond Software and Software Systems Processes, signaling our goal of learning from domains other than the traditional software process community.

Development of cloud applications must consider many aspects inherent in the distributed nature of clouds, mainly those related to elasticity, high access level to computational resources, multi-tenant behavior, transparency, pay-per-use model, and resource scalability. In addition, portability is a key feature that must be present in any development framework to allow extensions and simplify resource sharing by standardized interfaces. Open source approaches can be used, but the model must be composed of independent parts to optimize the availability of active components in the infrastructure. Hybrid cloud models are interesting because widely acceptable solutions can be developed without “reinventing the wheel.” Private clouds are more suitable for keeping restricted data or supporting services of small enterprises or institutions. However, their infrastructure must offer alternatives to provide services outside their own domain. In this context, a private cloud can use frameworks of public clouds and aggregate services to support the development of new applications. This generally occurs in PaaS models, where the platform offers pre-configured tools to interact with services of other domains. Security issues must also be considered at all stages of development, as most of the communication takes place among services located in different domains, linked by Internet connections. Solutions such as OpenID guarantee that public cloud services are used for the purpose of authentication, but additional security features in the source domain must be assured. In this chapter, a development framework is presented to guide the development of widely acceptable cloud applications, following standardized open source solutions. This framework, originally developed for a robotic environment, can be extended to support other cloud environments. The study presents aspects related to multi-scheduling of virtual machines and suggests how virtualized applications can be developed with different methodologies, such as dynamic IP, Web service with SOAP communication, MapReduce approach, and OCCI-based infrastructure.KeywordsCloud computingHybrid cloudOCCIOpenIDCloud frameworkMapReduceVirtualization

The International Conference on Software and System Processes (ICSSP), continuing the success of Software Process Workshop (SPW), the Software Process Modeling and Simulation Workshop (ProSim) and the International Conference on Software Process (ICSP) conference series, has become the established premier event in the field of software and systems engineering processes. It provides a leading forum for the exchange of research outcomes and industrial best-practices in process development from software and systems disciplines. ICSSP 2018 was held in Gothenburg, Sweden, 26-27 May 2018, co-located with the 40th International Conference on Software Engineering (ICSE). The theme of ICSSP 2018 was studying \Demands on Processes, Processes on Demand" by recognizing the demands on processes that include the need for both welldeveloped plans and incremental deliveries (agile and hybrid processes), utilization of increased automation (model-based engineering and DevOps), higher degrees of customer collaboration, comprehensive analysis of existing products for reuse (open source and COTS), and performance requirements of enterprise-level architectures. Papers presented at ICSSP discussed these issues across different domains, providing concepts, evidence, and experiences.

Software process is the most important part of software project management, and software process models are important means of implementing the software process in any software organization. When there is need to improve the software process, then the need to improve the work-task part (software process models) of the software process must arise. As, there is need of increasing the commitment of software project managers through out the software development life cycle (SDLC), so we need to give them the list of activities in Waterfall Model, which should be made efficient by the software development team, to get the 80% productivity (output) easily, by reducing the effort of software development and ultimately increasing the performance of the software process. So, the idea of 80/20 rule (Pareto Principle, 1935) can be applied in the software engineering process model, in this regard. The Pareto Principle (1935) directed us to focus on what is really important in any field and field's work. Software process is most important part of software project management (SPM). This is also then ultimately needed for software project management (SPM) improvement. Our main research work is to improve the work-task part of the software process (i.e. software process models by applying the Pareto Principle - 80/20 Rule (1935) (or law of vital few) (1935), in the software engineering process models (or work-task part of the software process). This will be to facilitate the software project manager, using the software process models practically more efficient than without application of 80/20 Rule in software engineering Waterfall model. This has resulted in the reduction of the software development effort and increase in the performance of the software process. The results (efficient and improved software process models) will be implemented in the software industry, by software project managers, by focusing on the list of activities giving 80 percent of the overall productivity of the software process. The results will be the list of activities having the capability to give 20 percent of the overall productivity of the software Waterfall process, to be ignored, eliminated or designated to reduce the effort.

Software engineering environments have a history of about two decades. Early environments provided support for small fragments of the software process (usually focusing on programming-in-the small). Then there was a trend towards support for more complete software processes (from early phases like requirements analysis and design down to testing and configuration management). Ten years ago the notion of process-centered software engineering environments initiated a new field in software engineering: software process research. The key idea is to use a model of a software process as input parameter for a software engineering environment. The environment is supposed to “behave” in accordance to the process model. Some aspects of this vision became true, others turned out to be of little practicability. In this article, we discuss the history of software engineering environments with a particular focus on process-centered software engineering environments (PCSEEs). We discuss the notion of distributed software processes (as one of the most substantial current trends in software process research) and we motivate the notion of a software process middleware which serves as basis of real-world software processes spread over various sites. In addition, we discuss some other trends in the software process research arena.

The software engineering process is a growing concern for many software development organizations. The need for well-educated software engineers is bringing new software engineering programs to universities. In many programs, software process education adds up to a few hours of lectures in an introductory software engineering course. This paper presents the structure and the content for a full, one-semester course on software processes, which has been designed in close collaboration with industry. The course is based on a software process called UPEDU (Unified Process for EDUcation), pronounced Yoopeedoo, and has been customized from the Rational Unified Process (RUP) for the educational environment. Many artifacts derived from a project case study are used as examples or templates. The content of the course is oriented towards the cognitive skills needed to perform the various activities required in the software process.

The main core of software engineering key technologies is the development of software services, ensuring the scientificity, security, and stability of the application software engineering system. At present, China’s economic development urgently needs the support of software engineering technology. Based on the T-ACO algorithm, the scientificity of software engineering and the accuracy of data have been significantly improved compared with traditional software engineering technology. It plays an important role in promoting the follow-up software engineering technology. In order to effectively analyze the key technology of engineering software, an improved ant colony algorithm based on T distribution is proposed in this paper. Because the basic ant colony algorithm is easy to fall into the local optimum and the optimization accuracy is low, in the optimization process, at the beginning of the pheromone update, the introduction of the T distribution is helpful for the basic ant colony algorithm to make up for its shortcomings. Adding pheromone variables to the basic ant colony algorithm improves the diversity of the ant colony, thereby eliminating the limitations of local optimal solutions. At the same time, the T-ACO algorithm also improves the search accuracy and convergence speed of automatic data generation in software engineering. In this paper, the performance of the T-ACO algorithm is simulated by experiments. Experimental analysis shows that when the population size is small, the T-ACO algorithm may sometimes not converge to the optimal solution, but when the population size is large (≥50), the T-ACO algorithm may converge to the optimal solution. It can realize the coverage of the total path by the output test case set. While the other two algorithms can achieve full path coverage, they are not stable, resulting in an average coverage between 90% and 100%. The T-ACO algorithm not only has good accuracy in creating test case sets, but also has good algorithm performance, and it is suitable as a multipath test case creation algorithm.

In general, operating systems (OSs) are designed to mediate access to device hardware by applications. They process different kinds of system calls using an indiscriminate kernel with the same configuration. Applications in cloud computing platforms are constructed from service components. Each of the service components is assigned separately to an individual virtual machine (VM), which leads to homogeneous system calls on each VM. In addition, the requirements for kernel function and configuration of system parameters from different VMs are different. Therefore, the suit-to-all design incurs an unnecessary performance overhead and restricts the OS’s processing capacity in cloud computing. In this paper, we propose an adaptive model for cloud computing to resolve the conflict between generality and performance. Our model adaptively specializes the OS of a VM according to the resource-consuming characteristics of workloads on the VM. We implement a prototype of the adaptive model, vSpec. There are five classes of VM: CPU-intensive, memory-intensive, I/O-intensive, networkintensive and compound, according to the resource-consuming characteristics of the workloads running on the VMs. vSpec specializes the OS of a VM according to the VM class. We perform comprehensive experiments to evaluate the effectiveness of vSpec on benchmarks and real-world applications.