Learning Software Industry Practices With Open Source and Free Software Tools

2017 ◽  
pp. 15-32
Author(s):  
Jagadeesh Nandigam ◽  
Venkat N. Gudivada
Keyword(s):  
Software Engineering ◽  
Open Source ◽  
Software Metrics ◽  
Software Industry ◽  
Engineering Ethics ◽  
Software Tools ◽  
Free Software ◽  
Incremental Development ◽  
Standards Compliance ◽  
Learning Software

This chapter describes a pragmatic approach to using open source and free software tools as valuable resources to affect learning of software industry practices using iterative and incremental development methods. The authors discuss how the above resources are used in teaching undergraduate Software Engineering (SE) courses. More specifically, they illustrate iterative and incremental development, documenting software requirements, version control and source code management, coding standards compliance, design visualization, software testing, software metrics, release deliverables, software engineering ethics, and professional practices. The authors also present how they positioned the activities of this course to qualify it for writing intensive designation. End of semester course evaluations and anecdotal evidence indicate that the proposed approach is effective in educating students in software industry practices.

Learning Software Industry Practices with Open Source and Free Software Tools

2015 ◽  
pp. 997-1012
Author(s):  
Jagadeesh Nandigam ◽  
Venkat N Gudivada
Keyword(s):  
Software Engineering ◽  
Open Source ◽  
Software Metrics ◽  
Software Industry ◽  
Engineering Ethics ◽  
Software Tools ◽  
Free Software ◽  
Incremental Development ◽  
Standards Compliance ◽  
Learning Software

This chapter describes a pragmatic approach to using open source and free software tools as valuable resources to affect learning of software industry practices using iterative and incremental development methods. The authors discuss how the above resources are used in teaching undergraduate Software Engineering (SE) courses. More specifically, they illustrate iterative and incremental development, documenting software requirements, version control and source code management, coding standards compliance, design visualization, software testing, software metrics, release deliverables, software engineering ethics, and professional practices. The authors also present how they positioned the activities of this course to qualify it for writing intensive designation. End of semester course evaluations and anecdotal evidence indicate that the proposed approach is effective in educating students in software industry practices.

Learning Software Industry Practices with Open Source and Free Software Tools

2014 ◽  
pp. 414-430
Author(s):  
Jagadeesh Nandigam ◽  
Venkat N Gudivada
Keyword(s):  
Software Engineering ◽  
Open Source ◽  
Software Metrics ◽  
Software Industry ◽  
Engineering Ethics ◽  
Software Tools ◽  
Free Software ◽  
Incremental Development ◽  
Standards Compliance ◽  
Learning Software

This chapter describes a pragmatic approach to using open source and free software tools as valuable resources to affect learning of software industry practices using iterative and incremental development methods. The authors discuss how the above resources are used in teaching undergraduate Software Engineering (SE) courses. More specifically, they illustrate iterative and incremental development, documenting software requirements, version control and source code management, coding standards compliance, design visualization, software testing, software metrics, release deliverables, software engineering ethics, and professional practices. The authors also present how they positioned the activities of this course to qualify it for writing intensive designation. End of semester course evaluations and anecdotal evidence indicate that the proposed approach is effective in educating students in software industry practices.

scholarly journals MetricRA: Learning Software Metrics through Augmented Reality

2018 ◽  
Author(s):  
Rebeca Motta ◽  
Mario Bonicenha ◽  
Claudia Susie Rodrigues ◽  
Cláudia Werner
Keyword(s):  
Software Engineering ◽  
Augmented Reality ◽  
Real World ◽  
Software Metrics ◽  
Engineering Students ◽  
Class Diagram ◽  
Abstract Concepts ◽  
Augmented Reality Technology ◽  
Learning Software

Augmented reality creates a bridge between virtual and real world, providing stimulating resources for different purposes. This technology enables new teaching possibilities since it can bring more abstract concepts into reality and put the knowledge related to several areas, such as Software Engineering, into practice. MetricRA is a tool developed to help Software Engineering students to understand Cohesion and Coupling metrics. The solution was implemented with Augmented Reality technology, where the user can control a class diagram to observe the metrics transformation. This article describes MetricRA tool and presents a study conducted to evaluate its ability to contribute to the understanding of the concepts proposed.

Making Government Policies for Education Possible by Means of Open Source Technology

2011 ◽  
pp. 343-368
Author(s):  
Marcos Castilho ◽  
Marcos S. Sunye ◽  
Daniel Weingaerter ◽  
Luis C.E. de Bona ◽  
Fabiano. Silva ◽  
...  
Keyword(s):  
Public Schools ◽  
Computer Science ◽  
Open Source ◽  
Internet Access ◽  
Software Tools ◽  
The State ◽  
Free Software ◽  
Government Policies ◽  
Innovative Technology ◽  
Centralized Management

In this chapter, we describe the products and services offered by the Department of Computer Science of the Federal University of Paraná within the scope of the Paraná Digital project. The department has designed laboratories with Internet access for 2,100 public schools of the state, with innovative technology through an environment entirely based upon free software tools, centralized management as well as continuous maintenance, and betterment of the services offered. We place special emphasis on our strategies, aiming at contributing to the adoption of such strategies in contexts relatively similar to ours, with which a parallel may be drawn concerning the hypothesis situation of the present project.

scholarly journals What Software Architecture Styles are Popular?

2021 ◽  
Vol 33 (3) ◽  
pp. 7-26
Author(s):  
Alexey Alexandrovich Mitsyuk ◽  
Nikolay Arsenovich Jamgaryan
Keyword(s):  
Software Engineering ◽  
Software Architecture ◽  
Open Source ◽  
Software Industry ◽  
Source Code ◽  
Automatic Recognition ◽  
Software Developers ◽  
Architecture Style ◽  
Repository Mining ◽  
Industrial Software

One can meet the software architecture style's notion in the software engineering literature. This notion is considered important in books on software architecture and university sources. However, many software developers are not so optimistic about it. It is not clear, whether this notion is just an academic concept, or is actually used in the software industry. In this paper, we measured industrial software developers' attitudes towards the concept of software architecture style. We also investigated the popularity of eleven concrete architecture styles. We applied two methods. A developers’ survey was applied to estimate developers' overall attitude and define what the community thinks about the automatic recognition of software architecture styles. Automatic crawlers were applied to mine the open-source code from the GitHub platform. These crawlers identified style smells in repositories using the features we proposed for the architecture styles. We found that the notion of software architecture style is not just a concept of academics in universities. Many software developers apply this concept in their work. We formulated features for the eleven concrete software architecture styles and developed crawlers based on these features. The results of repository mining using the features showed which styles are popular among developers of open-source projects from commercial companies and non-commercial communities. Automatic mining results were additionally validated by the Github developers survey.

scholarly journals REKAYASA PERANGKAT LUNAK BERBASIS SUMBER TERBUKA UNTUK MEMBANTU PELAKSANAAN AUDIT SISTEM INFORMASI

2010 ◽  
Vol 4 (1) ◽  
pp. 47
Author(s):  
Hari Setiabudi Husni
Keyword(s):  
Information System ◽  
Information Systems ◽  
Software Engineering ◽  
Open Source ◽  
Open Source Software ◽  
Software Industry ◽  
Source Code ◽  
Main Research ◽  
Functional Aspects ◽  
Final Output

This research was conducted on one budget period in 2009 funded by DIKTI young lecturer research project grant. The main research location is Bina Nusantara University. Due to tight research schedule, it was necessary to take some strategic steps to fulfill research goals. One of the strategic steps was to invite several experts in software industry to give advices regarding open source software engineering issues. The first achievement was findings of some open source software that could assist on auditing information systems. Afterwards, comparison from technical and functional aspects resulted in the best software to be tested for implementation and usage, namely ZenossCore. The final output of this research is successful reengineering of the source code for virtual file testing.Keywords: open source software, audit implementation, information system

scholarly journals Data Mining Techniques for Software Quality Prediction in Open Source Software

2019 ◽  
Vol 214 ◽  
pp. 05007
Author(s):  
Marco Canaparo ◽  
Elisabetta Ronchieri
Keyword(s):  
Data Mining ◽  
Software Engineering ◽  
Open Source ◽  
Software Quality ◽  
Open Source Software ◽  
Software Metrics ◽  
Prediction Models ◽  
Quality Prediction ◽  
Data Mining Techniques ◽  
Software Quality Prediction

Software quality monitoring and analysis are among the most productive topics in software engineering research. Their results may be effectively employed by engineers during software development life cycle. Open source software constitutes a valid test case for the assessment of software characteristics. The data mining approach has been proposed in literature to extract software characteristics from software engineering data. This paper aims at comparing diverse data mining techniques (e.g., derived from machine learning) for developing effective software quality prediction models. To achieve this goal, we tackled various issues, such as the collection of software metrics from open source repositories, the assessment of prediction models to detect software issues and the adoption of statistical methods to evaluate data mining techniques. The results of this study aspire to identify the data mining techniques that perform better amongst all the ones used in this paper for software quality prediction models.

Neural Network Model to Calculate the Creep Data Using Size

2017 ◽  
Vol 7 (8) ◽  
pp. 257
Author(s):  
Seetharam .K ◽  
Sharana Basava Gowda ◽  
. Varadaraj
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Software Engineering ◽  
Network Model ◽  
Neural Network Model ◽  
Software Metrics ◽  
Creep Data ◽  
Engineering Software ◽  
Function Points ◽  
Different Levels

In Software engineering software metrics play wide and deeper scope. Many projects fail because of risks in software engineering development[1]t. Among various risk factors creeping is also one factor. The paper discusses approximate volume of creeping requirements that occur after the completion of the nominal requirements phase. This is using software size measured in function points at four different levels. The major risk factors are depending both directly and indirectly associated with software size of development. Hence It is possible to predict risk due to creeping cause using size.

Sign in / Sign up

Export Citation Format

Share Document