Ripple: An Event Driven Design Representation Framework for Integrating Usability and Software Engineering Life Cycles

2005 ◽  
pp. 245-265 ◽  
Author(s):  
Pardha S. Pyla ◽  
Manuel A. Pérez-Quiñones ◽  
James D. Arthur ◽  
H. Rex Hartson
Keyword(s):  
Software Engineering ◽  
Life Cycles ◽  
Design Representation ◽  
Event Driven

Towards Knowledge Evolution in Software Engineering

2012 ◽  
pp. 8-24
Author(s):  
Yves Wautelet ◽  
Christophe Schinckus ◽  
Manuel Kolp
Keyword(s):  
Software Engineering ◽  
Life Cycles ◽  
Project Managers ◽  
Software Project ◽  
Modeling Languages ◽  
Software Projects ◽  
Theoretical Frameworks ◽  
Knowledge Evolution ◽  
Iterative Development ◽  
Early Implementation

This article presents an epistemological reading of knowledge evolution in software engineering (SE) both within a software project and into SE theoretical frameworks principally modeling languages and software development life cycles (SDLC). The article envisages SE as an artificial science and notably points to the use of iterative development as a more adequate framework for the enterprise applications. Iterative development has become popular in SE since it allows a more efficient knowledge acquisition process especially in user intensive applications by continuous organizational modeling and requirements acquisition, early implementation and testing, modularity,… SE is by nature a human activity: analysts, designers, developers and other project managers confront their visions of the software system they are building with users’ requirements. The study of software projects’ actors and stakeholders using Simon’s bounded rationality points to the use of an iterative development life cycle. The later, indeed, allows to better apprehend their rationality. Popper’s knowledge growth principle could at first seem suited for the analysis of the knowledge evolution in the SE field. However, this epistemology is better adapted to purely hard sciences as physics than to SE which also takes roots in human activities and by the way in social sciences. Consequently, we will nuance the vision using Lakatosian epistemology notably using his falsification principle criticism on SE as an evolving science. Finally the authors will point to adaptive rationality for a lecture of SE theorists and researchers’ rationality.

Towards Knowledge Evolution in Software Engineering

2010 ◽  
Vol 3 (1) ◽  
pp. 21-40
Author(s):  
Yves Wautelet ◽  
Christophe Schinckus ◽  
Manuel Kolp
Keyword(s):  
Software Engineering ◽  
Life Cycles ◽  
Project Managers ◽  
Software Project ◽  
Modeling Languages ◽  
Software Projects ◽  
Theoretical Frameworks ◽  
Knowledge Evolution ◽  
Iterative Development ◽  
Early Implementation

This article presents an epistemological reading of knowledge evolution in software engineering (SE) both within a software project and into SE theoretical frameworks principally modeling languages and software development life cycles (SDLC). The article envisages SE as an artificial science and notably points to the use of iterative development as a more adequate framework for the enterprise applications. Iterative development has become popular in SE since it allows a more efficient knowledge acquisition process especially in user intensive applications by continuous organizational modeling and requirements acquisition, early implementation and testing, modularity,… SE is by nature a human activity: analysts, designers, developers and other project managers confront their visions of the software system they are building with users’ requirements. The study of software projects’ actors and stakeholders using Simon’s bounded rationality points to the use of an iterative development life cycle. The later, indeed, allows to better apprehend their rationality. Popper’s knowledge growth principle could at first seem suited for the analysis of the knowledge evolution in the SE field. However, this epistemology is better adapted to purely hard sciences as physics than to SE which also takes roots in human activities and by the way in social sciences. Consequently, we will nuance the vision using Lakatosian epistemology notably using his falsification principle criticism on SE as an evolving science. Finally the authors will point to adaptive rationality for a lecture of SE theorists and researchers’ rationality.

scholarly journals Review of Relevant System Development Life Cycles (SDLCs) in Service-Oriented Software Engineering (SoSE)

2012 ◽  
Vol 10 (2) ◽  
Author(s):  
L. Rodríguez-Martínez ◽  
M. Mora ◽  
F. Álvarez ◽  
L. Garza ◽  
H. Durán ◽  
...  
Keyword(s):  
Software Engineering ◽  
System Development ◽  
Life Cycles ◽  
Software Systems ◽  
Computing Technology ◽  
New Paradigm ◽  
Development Life Cycle ◽  
Service Oriented ◽  
Component Based Software Engineering ◽  
Relevant Range

Service-oriented software engineering (SoSE) is a new  paradigm for building software systems, fostered by the availability of a new -but already mature- computing technology based on services.  SoSE advances the current object-oriented and the component-based software engineering paradigms. Under that new paradigm, multiple software-system development life cycle (SDLC) methodologies have been proposed; however, none of them have gained a total acceptance as the dominant SDLC in SoSE.  On this theoretical and practical situation, we believe that a research is required to reach more standardized and stabilized knowledge about SDLCs in SoSE.  Thus, this article reviews nine recent SDLCs proposed for SoSE with the aim to present a descriptive-comparative landscape of a relevant range of SDLCs for SoSE. Such description-comparison is guided by two criteria: (i) the extent of completeness of each SDLC, with respect to the proposed phases, activities and delivered artifacts, and (ii) the extent of the Boehm-Turner’s Rigor-Agility balance. Our results suggest that only three of the nine SDLCs studied already provide the best level of completeness and Rigor-Agility. Finally, we consider that the reported descriptivecomparative framework and their findings from each SDLC can be useful also for comparing and elaborating future SDLCs in SoSE.

Usability Engineering of User-Centered Web Sites

2011 ◽  
pp. 3890-3896
Author(s):  
Theresa A. O’Connell ◽  
Elizabeth D. Murphy
Keyword(s):  
Software Engineering ◽  
Web Sites ◽  
Web Site ◽  
Life Cycles ◽  
Usability Engineering ◽  
Site Development ◽  
User Centered

For Web sites to succeed, they must be user-centered. A user-centered focus throughout Web site development life cycles promotes Web site usability. This is accomplished through usability engineering carried out within the context of software engineering.

Life cycles in software and knowledge engineering: a comparative review

1989 ◽  
Vol 4 (3) ◽  
pp. 189-204 ◽  
Author(s):  
Michael Wilson ◽  
David Duce ◽  
Dan Simpson
Keyword(s):  
Life Cycle ◽  
Software Engineering ◽  
Program Verification ◽  
Knowledge Engineering ◽  
System Development ◽  
Life Cycles ◽  
Development Projects ◽  
Comparative Review ◽  
Life Cycle Models ◽  
System Life

AbstractProgress in software engineering has led to system development following models of the system life cycle. These models incorporate the use of prototyping and formal methods of program verification. They are becoming supported by integrated project support environments and permit the planning and monitoring of software development projects.In contrast, knowledge based systems (KBS) are developed using informal views of the system life cycle. Tools have been developed to support some stages of the life cycle in an undisciplined manner. The commercial use of KBS needs development projects to be planned and monitored. This requires methods and tools based on systematic life cycle models to be established for KBS.This paper reviews the current state of life cycle approaches to software engineering and KBS development projects in order to provide a direction for the development of methodical KBS life cycle models.

scholarly journals An Improvement of E-Commerce (Simpler) via Artificial Intelligence and Networks

2018 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Yaser A. Jasim
Keyword(s):  
Artificial Intelligence ◽  
Software Engineering ◽  
Expert Systems ◽  
Local Area Networks ◽  
Local Area ◽  
Automatic Computer ◽  
Event Driven ◽  
Vacuum Tubes ◽  
Dynamic Host Configuration ◽  
Dynamic Host Configuration Protocol

<p>Nowadays, many research has been dedicated to the distribution of expert systems; unfortunately, few have deliberated the study of <em>Dynamic Host Configuration Protocol</em> (DHCP). In this paper, the researcher will demonstrate the construction of vacuum tubes, which embodies the principles of software engineering. In order to classify this challenge, the researcher argues not only that <em>local-area networks</em> (LAN) can be made event-driven, stable, and random but the same is true for the <em>Universal Automatic Computer</em> (UNIVAC). </p>

Analysis of 13 implementations of the software engineering management and engineering basic profile guide of ISO/IEC 29110 in very small entities using different life cycles

2020 ◽  
Vol 32 (11) ◽  
Author(s):  
Mirna Muñoz ◽  
Adriana Peña ◽  
Jezreel Mejía ◽  
Gloria Piedad Gasca‐Hurtado ◽  
María Clara Gómez‐Alvarez ◽  
...  
Keyword(s):  
Software Engineering ◽  
Engineering Management ◽  
Life Cycles

Classical Methodologies, Techniques and Tools for Project Management

2011 ◽  
pp. 72-94
Author(s):  
Fabrizio Fioravanti
Keyword(s):  
Risk Management ◽  
Life Cycle ◽  
Project Management ◽  
Software Engineering ◽  
Software Development ◽  
Life Cycles ◽  
Software Management ◽  
The Past ◽  
Agile Methodologies

In order to better understand Agile methodologies, it is necessary to have a clear background of what software engineering has suggested in the past regarding the methodologies for approaching software development and software management (Agresti, 1986; Buxton, 1976; Ghezzi, 1990; Naur, 1969). For these reasons, in this chapter, the so-called classical methodologies for project management are considered and commented on, together with the techniques, meta-models such as the spiral life cycle, and tools such as risk management and assessment. It is important to know the background of software engineering in order to understand if Agile methodologies will fit your needs. In this chapter, the waterfall life cycle and a couple of evolutionary life cycles (Gilb, 1988), such as prototyping and spiral life cycles (Boehm, 1988), will be analyzed.

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