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Designing a consulting services architecture model
textDuring my years of experience in the technology industry, it has become obvious that standard processes and methodologies within the engineering discipline are at a mature state. The realization though is that software engineering specifically lags behind. Most software engineering methodologies that I have studied focus on the mission of software development. It is this realization and the need for structure that led me to review existing methodologies used within my company's software services organization. The definition of what a successful software services methodology entails is rather limited. This report will provide a history of existing software engineering methodologies that I have studied, describe an initial services method that was being developed within my organization, develop a new model that addresses previous shortcomings and identify additional components required to further define a strong software services-oriented delivery methodology.Electrical and Computer Engineerin
Milestones in Software Engineering and Knowledge Engineering History: A Comparative Review
We present a review of the historical evolution of software engineering, intertwining it with the history of knowledge engineering because âthose who cannot remember the past are condemned to repeat it.â This retrospective represents a further step forward to understanding the current state of both types of engineerings; history has also positive experiences; some of them we would like to remember and to repeat. Two types of engineerings had parallel and divergent evolutions but following a similar pattern. We also define a set of milestones that represent a convergence or divergence of the software development methodologies. These milestones do not appear at the same time in software engineering and knowledge engineering, so lessons learned in one discipline can help in the evolution of the other one
History of visual systems in the Systems Engineering Simulator
The Systems Engineering Simulator (SES) houses a variety of real-time computer generated visual systems. The earliest machine dates from the mid-1960's and is one of the first real-time graphics systems in the world. The latest acquisition is the state-of-the-art Evans and Sutherland CT6. Between the span of time from the mid-1960's to the late 1980's, tremendous strides have been made in the real-time graphics world. These strides include advances in both software and hardware engineering. The purpose is to explore the history of the development of these real-time computer generated image systems from the first machine to the present. Hardware advances as well as software algorithm changes are presented. This history is not only quite interesting but also provides us with a perspective with which we can look backward and forward
Review: The Technical and Social History of Software Engineering
In his recent book The Technical and Social History of Software Engineering, Capers Jones promises to fill a long-standing need for a text that gives readers an understanding of the history of software engineering. In this paper, I examine the extent to which Jones succeeds in meeting that promise
git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories
Data from software repositories have become an important foundation for the
empirical study of software engineering processes. A recurring theme in the
repository mining literature is the inference of developer networks capturing
e.g. collaboration, coordination, or communication from the commit history of
projects. Most of the studied networks are based on the co-authorship of
software artefacts defined at the level of files, modules, or packages. While
this approach has led to insights into the social aspects of software
development, it neglects detailed information on code changes and code
ownership, e.g. which exact lines of code have been authored by which
developers, that is contained in the commit log of software projects.
Addressing this issue, we introduce git2net, a scalable python software that
facilitates the extraction of fine-grained co-editing networks in large git
repositories. It uses text mining techniques to analyse the detailed history of
textual modifications within files. This information allows us to construct
directed, weighted, and time-stamped networks, where a link signifies that one
developer has edited a block of source code originally written by another
developer. Our tool is applied in case studies of an Open Source and a
commercial software project. We argue that it opens up a massive new source of
high-resolution data on human collaboration patterns.Comment: MSR 2019, 12 pages, 10 figure
Historical roots of Agile methods: where did âAgile thinkingâ come from?
The appearance of Agile methods has been the most noticeable change to software process thinking in the last fifteen years [16], but in fact many of the âAgile ideasâ have been around since 70âs or even before. Many studies and reviews have been conducted about Agile methods which ascribe their emergence as a reaction against traditional methods. In this paper, we argue that although Agile methods are new as a whole, they have strong roots in the history of software engineering. In addition to the iterative and incremental approaches that have been in use since 1957 [21], people who criticised the traditional methods suggested alternative approaches which were actually Agile ideas such as the response to change, customer involvement, and working software over documentation. The authors of this paper believe that education about the history of Agile thinking will help to develop better understanding as well as promoting the use of Agile methods. We therefore present and discuss the reasons behind the development and introduction of Agile methods, as a reaction to traditional methods, as a result of people's experience, and in particular focusing on reusing ideas from histor
Space station software reliability analysis based on failures observed during testing at the multisystem integration facility
Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented
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