scholarly journals Implementing Project Managers in the Software Engineering Classroom

2015 ◽  
Author(s):  
Samuel Malachowsky
Keyword(s):  
Software Engineering ◽  
Project Managers ◽  
Engineering Classroom

scholarly journals Practitioners’ Perspective on Software Project Management Education

RENOTE ◽  
2019 ◽  
Vol 17 (3) ◽  
pp. 273-284
Author(s):  
Maria Lydia Fioravanti ◽  
Antonio Cesar Amaru Maximiano ◽  
Ellen Francine Barbosa
Keyword(s):  
Project Management ◽  
Software Engineering ◽  
Management Education ◽  
Degree Program ◽  
Project Managers ◽  
Specific Information ◽  
Software Project ◽  
Software Project Management ◽  
Recent Graduates

Despite Software project management (SPM) being one of the most relevant topicsin the area of software engineering that should be addressed in computing programs, SPM skills of recent graduates are not satisfactory yet. In this context, besides being important to know there are skill deficiencies, we also need to gather specific information on how to adjust and improve the education on the corresponding topics. In this paper we attempt to identify what knowledge deficiencies in SPM can persist after a student graduates from a computing degree program. We surveyed practitioners that graduated and worked as software project managers to gather the knowledge deficiencies from the industry perspective. In general, the results indicated that there is a number of professionals who seeks postgraduate programs to fill the deficiencies of the undergrad programs.

The Influence of Personality Traits on Software Engineering and its Applications

2014 ◽  
pp. 83-95 ◽  
Author(s):  
Adrián Casado-Rivas ◽  
Manuel Muñoz Archidona
Keyword(s):  
Software Engineering ◽  
Personality Traits ◽  
High Performance ◽  
Project Managers ◽  
Big Five Personality ◽  
Software Project ◽  
Myers Briggs Type Indicator ◽  
Team Members ◽  
Engineering Teams ◽  
Software Engineers

In Software Engineering, personality traits have helped to better understand the human factor. In this chapter, the authors give an overview of important personality traits theories that have influenced Software Engineering and have been widely adopted. The theories considered are Myers-Briggs Type Indicator, Big Five Personality Traits, and Belbin Roles. The influence of personality traits has provided remarkable benefits to Software Engineering, especially in the making of teams. For software project managers, it is useful to know what set of soft skills correlates to a specific team role so as to analyze how personality traits have contributed to high performance and cohesive software engineering teams. The study of software engineers’ personality traits also helps to motivate team members. Creating teams that involve compatible individuals, each working on tasks that suit them, and having a motivated team improves team performance, productivity, and reduces project costs.

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 Beyond Subjectiviness: Assessing Abilities and Preferences to Create Software Development Teams

2021 ◽  
Author(s):  
Lucas Alves ◽  
Vinícius Ricardo ◽  
Laerte Xavier
Keyword(s):  
Genetic Algorithm ◽  
Software Engineering ◽  
Software Development ◽  
Interpersonal Relationships ◽  
Human Error ◽  
Project Managers ◽  
Specific Task ◽  
Development Teams ◽  
Software Development Teams ◽  
Performance Issues

The creation of software development teams that are affected by performance issues is a problem frequently observed in companies in the software development market. This process is commonly done through subjective methodologies. Such methodologies can be influenced by interpersonal relationships and susceptible to human error. This paper proposes a quantitative and data-oriented alternative to the process of forming workgroups through the use of a genetic algorithm capable of optimizing collaborator’s abilities and preferences when executing a specific task within a project. As a result, we show that the use of such genetic algorithm is able to create teams similar to the teams assembled by the project managers of companies in the industry of software engineering. Therefore, the ability of genetic algorithm on supporting the process of develoment teams assembly becomes evident.

Improving Credibility of Machine Learner Models in Software Engineering

2011 ◽  
pp. 52-72 ◽  
Author(s):  
Gary D. Boetticher
Keyword(s):  
Machine Learning ◽  
Software Engineering ◽  
Nearest Neighbor ◽  
Project Managers ◽  
Empirical Software Engineering ◽  
Software Project ◽  
Series Of Experiments ◽  
Test Sets ◽  
Fold Cross Validation ◽  
Machine Learning Models

Given a choice, software project managers frequently prefer traditional methods of making decisions rather than relying on empirical software engineering (empirical/machine learning- based models). One reason for this choice is the perceived lack of credibility associated with these models. To promote better empirical software engineering, a series of experiments are conducted on various NASA datasets to demonstrate the importance of assessing the ease/difficulty of a modeling situation. Each dataset is divided into three groups, a training set, and “nice/nasty” neighbor test sets. Using a nearest neighbor approach, “nice neighbors” align closest to same class training instances. “Nasty neighbors” align to the opposite class training instances. The “nice”, “nasty” experiments average 94% and 20%accuracy, respectively. Another set of experiments show how a ten-fold cross-validation is not sufficient in characterizing a dataset. Finally, a set of metric equations is proposed for improving the credibility assessment of empirical/machine learning models.

Metrics and Software Project Management for the 21st Century

1995 ◽  
Author(s):  
Johanna Rothman
Keyword(s):  
Project Management ◽  
Software Engineering ◽  
Process Control ◽  
Product Development ◽  
21St Century ◽  
Software Quality ◽  
Development Process ◽  
Project Managers ◽  
Software Project ◽  
Software Products

Abstract There is general agreement among the experts and practitioners that a crisis exists in Software Engineering. This crisis is in the area of software quality and schedules. How do we better predict product development progress on an ongoing basis? The quick answer is that all project managers need to know these things: • What are the requirements for functionality, cost, and schedule? • Do I have sufficient resources to meet those requirements? • Am I on target to meet those requirements? These questions are particularly critical for companies who produce complex software, such as real-time or process control products. There are ways to ensure that the requirements of schedule, functionality, and cost are met during project development. This paper will discuss project management activities, possible development process, and predictive measurements for project tracking and prediction for complex software products.

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