scholarly journals IT Systems Development: An IS Curricula Course that Combines Best Practices of Project Management and Software Engineering

10.28945/3315 ◽  
2009 ◽  
Author(s):  
Abdallah Tubaishat
Keyword(s):  
Project Management ◽  
Software Engineering ◽  
Best Practices ◽  
Software Development ◽  
Systems Development ◽  
Software Projects ◽  
Team Members ◽  
It Systems ◽  
Engineering Best Practices ◽  
Development Course

Most computing programs still devote little time to software life cycle development, software processes, quality issues, team skills, and other areas of software engineering essential to effective commercial software development. A teaching project was developed and implemented by accommodating knowledge and practices that are applicable to most projects in the area of project management and in the area of software development to Information Systems (IS) students. This approach is relevant to IS model curricula and is in accordance with IS2002.10 project management and practice course guidelines. The rationale behind this approach is to overcome the relative lack of experience of IS students in many aspects of project management and software development by introducing them how to plan, organize, and control software development projects, and to help students strengthen good software engineering practices prior to entering IT industry and become more efficient. We present results of a case study based on a survey conducted in an IT Systems Development course. Survey results show that including topics on project management and Software Engineering best practices lab into an IT Systems Development course helped students (a) deal with non-technical issues of software projects, (b) develop their ability to communicate clearly with team members, and (c) overcome their lack of experience in many aspects of project management and software development.

scholarly journals Juego lúdico GetKanban Game para apoyar el proceso de enseñanza aprendizaje de la disciplina de gestión de proyectos de software en los estudiantes de TIC`S

2020 ◽  
Vol 6 (3) ◽  
pp. 27-34
Author(s):  
E.J. Robles Gómez ◽  
J.A. Flores Lara ◽  
J.C. Ontiveros Neri
Keyword(s):  
Project Management ◽  
Software Engineering ◽  
Software Development ◽  
Systems Engineering ◽  
Educational Institution ◽  
Development Projects ◽  
Software Project ◽  
Software Projects ◽  
Teaching Learning ◽  
On Time Delivery

El juego getKanban es una herramienta para enseñar la metodología Kanban y SCRUM de una manera divertida. Facilita la enseñanza de la gestión de proyectos de software a través de un juego de mesa, donde los jugadores aprenden a formular estrategias de gestión de proyectos y las implementan para elaborar proyectos de calidad en tiempo y forma. El presente artículo muestra los resultados de la implementación del juego en una institución educativa de nivel superior, con alumnos de Ingeniería en Sistemas Computacionales de octavo semestre. Se puede apreciar que al utilizar este juego ayuda de manera efectiva a la enseñanza de Kanban y SCRUM, para la gestión de proyectos de software. Por lo cual se recomienda poder implementar este tipo de juegos como estrategia didáctica para la enseñanza/aprendizaje de Ingeniería de Software aplicada a la Gestión de Proyectos de Desarrollo de Software. The game Kanban is a tool to teach the methodology in a fun way. It facilitates the teaching of software project management through where players learn to formulate strategies and implement them to develop quality projects on time Delivery. This article shows the results of the implementation of the game in an educational institution of higher level, with students of Computer Systems Engineering eighth semester. It can be seen that by using this game it helps in an effective way to teach Kanban for the management of software projects. Therefore, it is recommended to be able to implement this type of games as a didactic strategy for the teaching / learning of Software Engineering applied to the Management of Software Development Projects

A Framework for Risk Management in AI System Development Projects

2019 ◽  
pp. 1-20
Author(s):  
Kitti Photikitti ◽  
Kitikorn Dowpiset ◽  
Jirapun Daengdej
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Project Management ◽  
Software Development ◽  
System Development ◽  
Systems Development ◽  
Development Projects ◽  
Software Project ◽  
Software Projects ◽  
Very High

It has been well-known that the chance of successfully delivering a software project within an allocated time and budget is very low. Most of the researches in this area have concluded that “user's requirements” of the systems is one of the most difficult risks to deal with in this case. Interestingly, until today, regardless of amount of effort put into this area, the possibility of project failure is still very high. The issue with requirement can be significantly increased when developing an artificial intelligence (AI) system, where one would like the systems to autonomously behave. This is because we are not only dealing with user's requirements, but we must also be able to deal with “system's behavior” that, in many cases, do not even exist during software development. This chapter discusses a preliminary work on a framework for risk management for AI systems development projects. The goal of this framework is to help project management in minimizing risk that can lead AI software projects to fail due to the inability to finish the projects on time and within budget.

Programmatic modeling for biological systems

2021 ◽  
Author(s):  
Alexander L.R. Lubbock ◽  
Carlos F. Lopez
Keyword(s):  
Software Engineering ◽  
Best Practices ◽  
Computational Modeling ◽  
User Interfaces ◽  
Model Development ◽  
List Type ◽  
Cellular Processes ◽  
Domain Specific ◽  
Community Benefits ◽  
Engineering Best Practices

AbstractComputational modeling has become an established technique to encode mathematical representations of cellular processes and gain mechanistic insights that drive testable predictions. These models are often constructed using graphical user interfaces or domain-specific languages, with SBML used for interchange. Models are typically simulated, calibrated, and analyzed either within a single application, or using import and export from various tools. Here, we describe a programmatic modeling paradigm, in which modeling is augmented with best practices from software engineering. We focus on Python - a popular, user-friendly programming language with a large scientific package ecosystem. Models themselves can be encoded as programs, adding benefits such as modularity, testing, and automated documentation generators while still being exportable to SBML. Automated version control and testing ensures models and their modules have expected properties and behavior. Programmatic modeling is a key technology to enable collaborative model development and enhance dissemination, transparency, and reproducibility.HighlightsProgrammatic modeling combines computational modeling with software engineering best practices.An executable model enables users to leverage all available resources from the language.Community benefits include improved collaboration, reusability, and reproducibility.Python has multiple modeling frameworks with a broad, active scientific ecosystem.

Systematische Methodenauswahl bei der Digitalisierung/Systematic selection of methods for digitization projects – Leveraging established software development methods in the manufacturing industry

2020 ◽  
Vol 110 (04) ◽  
pp. 226-230
Author(s):  
Andreas Selmaier ◽  
Benedikt Martens ◽  
Martin Sjarov ◽  
Marlene Kuhn ◽  
Meike Herbert ◽  
...  
Keyword(s):  
Software Development ◽  
Manufacturing Industry ◽  
Project Planning ◽  
Production Environment ◽  
Software Projects ◽  
It Systems ◽  
Planning Methods ◽  
Systematic Selection ◽  
Iterative Procedures ◽  
Selection Of

Digitalisierungsprojekte sind Softwareprojekte. Sequenzielle Planungsmethoden, wie sie im konventionellen Projektmanagement überwiegend Anwendung finden, eignen sich nur bedingt für diesen Projekttyp, da die anwendungsspezifischen Anforderungen sowie die Abhängigkeiten der Anlagen und IT-Systeme untereinander zu einem erheblichen Anstieg der Gesamtkomplexität führen. In diesem Beitrag wird daher ein Ansatz zur systematischen Auswahl geeigneter Projektmanagementmethoden für Digitalisierungsprojekte vorgestellt, welcher die traditionelle Projektplanung im Produktionsumfeld um iterative Vorgehensweisen aus der Software- entwicklung ergänzt.   Digitalization projects are software projects. Less suitable for such projects are sequential planning methods often used in conventional project management, as application-specific requirements and interdependencies of facilities and IT systems considerably increase overall complexity. Therefore, this paper presents an approach for the systematic selection of suitable management methods for digitalization projects, which adds iterative procedures from software development to traditional project planning in the production environment.

Managing Software Projects with Team Software Process (TSP)

2013 ◽  
pp. 84-117
Author(s):  
Salmiza Saul Hamid ◽  
Mohd Hairul Nizam Md Nasir ◽  
Shamsul Sahibuddin ◽  
Mustaffa Kamal Mohd Nor
Keyword(s):  
Project Management ◽  
Software Development ◽  
Management Practices ◽  
Software Process ◽  
Development Project ◽  
Software Projects ◽  
Engineering Teams ◽  
Software Development Project ◽  
Software Failure ◽  
Team Software Process

Despite the widespread use of sound project management practices and process improvement models over the last several years, the failure of software projects remains a challenge to organisations. As part of the attempt to address software industry challenges, several models, frameworks, and methods have been developed that are intended to improve software processes to produce quality software on time, under budget, and in accordance with previously stipulated functionalities. One of the most widely practised methods is the Team Software Process (TSP). The TSP was designed to provide an operational framework for establishing an effective team environment and guiding engineering teams in their work. This chapter provides an overview of the TSP and its associated structures and processes. It also highlights how the TSP operational framework can assist project manager and software development team to deliver successful projects by controlling and minimizing the most common software failure factors. Comparative analysis between the TSP and conventional project management has also been presented. Additionally, the results of TSP implementation in industrial settings are highlighted with particular reference to scheduling, quality, and productivity. The last section indicates additional advantages of TSP and comments on the future of TSP in the global software development project.

Influential Agile Software Parameters

2011 ◽  
pp. 1938-1943
Author(s):  
Subhas C. Misra ◽  
Vinod Kumar ◽  
Uma Kumar
Keyword(s):  
Project Management ◽  
Software Process ◽  
Systems Development ◽  
The Other ◽  
Software Systems ◽  
Software Projects ◽  
Optimal Cost ◽  
Management Processes ◽  
Agile Software ◽  
Refining Processes

Successful software systems development is a delicate balance among several distinct factors (Jalote, 2002) such as enabling people to grow professionally; documenting processes representing the gained experiences and knowledge of the organization members; using know how to apply the suitable processes to similar circumstances; and refining processes based on achieved experience. Software projects have two main dimensions: engineering and project management. The engineering dimension concerns the construction of a system, and focuses mainly on issues such as how to build a system. The project management dimension is in charge with properly planning and controlling the engineering activities to meet project goals for optimal cost, schedule, and quality. For a project, the engineering processes specify how to perform activities such as requirement specification, design, testing, and so on. The project management processes, on the other hand, specify how to set milestones, organize personnel, manage risks, monitor progress, and so on (Jalote, 2002). A software process may be defined as “a set of activities, methods, practices, and transformations that people use to develop and maintain software, and the associated products and artifacts.”1 This is pictorially depicted in Figure 1 (Donaldson & Siegel, 2000).

Multi-Agent Systems as Computational Organizations

2011 ◽  
pp. 1658-1683
Author(s):  
Franco Zambonelli ◽  
Nicholas R. Jennings ◽  
Michael Wooldridge
Keyword(s):  
Software Engineering ◽  
Software Development ◽  
Systems Development ◽  
Multi Agent Systems ◽  
Design Development ◽  
Analysis And Design ◽  
Agent Systems ◽  
Multi Agent ◽  
Traditional Approaches ◽  
System Paradigm

The multi-agent system paradigm introduces a number of new design/development issues when compared with more traditional approaches to software development and calls for the adoption of new software engineering abstractions. To this end, in this chapter, we elaborate on the potential of analyzing and architecting complex multi-agent systems in terms of computational organizations. Specifically, we identify the appropriate organizational abstractions that are central to the analysis and design of such systems, discuss their role and importance, and show how such abstractions are exploited in the context of the Gaia methodology for multi-agent systems development.

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