scholarly journals A Study of Quality Indicator Model of Large-Scale Open Source Software Projects for Adoption Decision-making

2020 ◽  
Vol 176 ◽  
pp. 3665-3672
Author(s):  
Shinji Akatsu ◽  
Ayako Masuda ◽  
Tsuyoshi Shida ◽  
Kazuhiko Tsuda
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Quality Indicator ◽  
Large Scale ◽  
Software Projects ◽  
Adoption Decision ◽  
Indicator Model

scholarly journals A study of quality prediction for large-scale open source software projects

2021 ◽  
Vol 10 (1) ◽  
pp. 34
Author(s):  
Shinji Akatsu ◽  
Ayako Masuda ◽  
Tsuyoshi Shida ◽  
Kazuhiko Tsuda
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Quality Analysis ◽  
Quality Prediction ◽  
Software Projects ◽  
Resolution Rate ◽  
The Status

Open source software (OSS) has seen remarkable progress in recent years. Moreover, OSS usage in corporate information systems has been increasing steadily; consequently, the overall impact of OSS on the society is increasing as well. While product quality of enterprise software is assured by the provider, the deliverables of an OSS are developed by the OSS developer community; therefore, their quality is not guaranteed. Thus, the objective of this study is to build an artificial-intelligence-based quality prediction model that corporate businesses could use for decision-making to determine whether a desired OSS should be adopted. We define the quality of an OSS as “the resolution rate of issues processed by OSS developers as well as the promptness and continuity of doing so.” We selected 44 large-scale OSS projects from GitHub for our quality analysis. First, we investigated the monthly changes in the status of issue creation and resolution for each project. It was found that there are three different patterns in the increase of issue creation, and three patterns in the relationship between the increase in issue creation and that of resolution. It was confirmed that there are multiple cases of each pattern that affect the final resolution rate. Next, we investigated the correlation between the final resolution rate and that for a relevant number of months after issue creation. We deduced that the correlation coefficient even between the resolution rate in the first month and the final rate exceeded 0.5. Based on these analysis results, we conclude that the issue resolution rate in the first month once an issue is created is applicable as knowledge for knowledge-based AI systems that can be used to assist in decision-making regarding OSS adoption in business projects.

scholarly journals A large-scale empirical exploration on refactoring activities in open source software projects

2019 ◽  
Vol 180 ◽  
pp. 1-15 ◽  
Author(s):  
Carmine Vassallo ◽  
Giovanni Grano ◽  
Fabio Palomba ◽  
Harald C. Gall ◽  
Alberto Bacchelli
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Software Projects

A Study of Measurement for Development Efficiency in Large Scale Open Source Software Projects

2018 ◽  
Vol 138 (8) ◽  
pp. 1011-1019 ◽  
Author(s):  
Ayako Masuda ◽  
Chikako Morimoto ◽  
Tohru Matsuodani ◽  
Kazuhiko Tsuda
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Software Projects

scholarly journals On Predicting Rediscoveries of Software Defects

2021 ◽  
Author(s):  
Mefta Sadat
Keyword(s):  
Customer Satisfaction ◽  
Open Source ◽  
Predictive Model ◽  
Software Quality ◽  
Open Source Software ◽  
Large Scale ◽  
Software Defects ◽  
Enterprise Software ◽  
Software Projects ◽  
Multiple Clients

The same defect may be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. One solution is forcing clients to install a fix for every defect. However, this approach is economically infeasible, because it requires extra resources and increases downtime. Moreover, it may lead to regression of functionality, as new fixes may break the existing functionality. Our goal is to find a way to proactively predict defects that a client may rediscover in the future. We build a predictive model by leveraging recommender algorithms. We evaluate our approach with extracted rediscovery data from four groups of large-scale open source software projects (namely, Eclipse, Gentoo, KDE, and Libre) and one enterprise software. The datasets contain information about ⇡ 1.33 million unique defect reports over a period of 18 years (1999-2017). Our proposed approach may help in understanding the defect rediscovery phenomenon, leading to improvement of software quality and customer satisfaction.

scholarly journals On Predicting Rediscoveries of Software Defects

2021 ◽  
Author(s):  
Mefta Sadat
Keyword(s):  
Customer Satisfaction ◽  
Open Source ◽  
Predictive Model ◽  
Software Quality ◽  
Open Source Software ◽  
Large Scale ◽  
Software Defects ◽  
Enterprise Software ◽  
Software Projects ◽  
Multiple Clients

The same defect may be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. One solution is forcing clients to install a fix for every defect. However, this approach is economically infeasible, because it requires extra resources and increases downtime. Moreover, it may lead to regression of functionality, as new fixes may break the existing functionality. Our goal is to find a way to proactively predict defects that a client may rediscover in the future. We build a predictive model by leveraging recommender algorithms. We evaluate our approach with extracted rediscovery data from four groups of large-scale open source software projects (namely, Eclipse, Gentoo, KDE, and Libre) and one enterprise software. The datasets contain information about ⇡ 1.33 million unique defect reports over a period of 18 years (1999-2017). Our proposed approach may help in understanding the defect rediscovery phenomenon, leading to improvement of software quality and customer satisfaction.

The Impact of Ideology on the Organizational Adoption of Open Source Software

2011 ◽  
pp. 160-175
Author(s):  
Kris Ven ◽  
Jan Verelst
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Organizational Adoption ◽  
Adoption Decision ◽  
Small Organizations ◽  
The Impact

Previous research has shown that the open source movement shares a common ideology. Employees belonging to the open source movement often advocate the use of open source software within their organization. Hence, their belief in the underlying open source software ideology may influence the decision making on the adoption of open source software. This may result in an ideological—rather than pragmatic—decision. A recent study has shown that American organizations are quite pragmatic in their adoption decision. We argue that there may be circumstances in which there is more opportunity for ideological behavior. We therefore investigated the organizational adoption decision in Belgian organizations. Our results indicate that most organizations are pragmatic in their decision making. However, we have found evidence that suggests that the influence of ideology should not be completely disregarded in small organizations.

A Framework for Understanding the Open Source Revolution

2009 ◽  
pp. 439-454
Author(s):  
Jeff Elpern ◽  
Sergiu Dascalu
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Real World ◽  
Large Scale ◽  
Future Research ◽  
Software Systems ◽  
New Paradigm ◽  
Hierarchical Decision Making ◽  
Hierarchical Decision

Traditional software engineering methodologies have mostly evolved from the environment of proprietary, large-scale software systems. Here, software design principles operate within a hierarchical decision- making context. Development of banking, enterprise resource and complex weapons systems all fit this paradigm. However, another paradigm for developing software-intensive systems has emerged, the paradigm of open source software. Although from a traditional perspective open source projects might look like chaos, their real-world results have been spectacular. This chapter presents open source software development as a fundamentally new paradigm driven by economics and facilitated by new processes. The new paradigm’s revolutionary aspects are explored, a framework for describing the massive impact brought about by the new paradigm is proposed, and directions of future research are outlined. The proposed framework’s goals are to help the understanding of the open source paradigm as a new economic revolution and stimulate research in designing open source software.

scholarly journals The Influence of Risk Factors in Decision-Making Process for Open Source Software Adoption

2016 ◽  
Vol 15 (01) ◽  
pp. 151-185 ◽  
Author(s):  
Mario Silic ◽  
Andrea Back
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Media Coverage ◽  
Decision Making Process ◽  
It Security ◽  
Security Risk ◽  
Theoretical Understanding ◽  
Adoption Decision ◽  
Adoption Intention

“Nobody ever got fired for buying IBM,” was a widely used cliché in the 1970s in the corporate IT (information technology) world. Since then, the traditional process of purchasing software has dramatically changed, challenged by the advent of open source software (OSS). Since its inception in the 1980s, OSS has matured, grown, and become one of the important driving forces of the enterprise ecosystem. However, it has also brought important IT security risks that are impacting the OSS IT adoption decision-making process. The recent Heartbleed bug demonstrated the grandeur of the issue. While much of the noise relates to the amplification of perceived risks by the popular mass media coverage, the effect is that many enterprises, mainly for risk reasons, have still chosen not to adopt OSS. We investigated “how do information security related characteristics of OSS affect the risk perception and adoption decision of OSS” by conducting an online survey of 188 IT decision-makers. The proposed Open Source Risk Adoption Model offers novel insights on the importance of the perceived risk antecedents. Our research brings new theoretical contributions, such as understanding the perceived IT security risk (PISR) relationship with adoption intention (AI) in the OSS context, for researchers and important insights for IT information professionals. We have found that IT security risk has a significant role in OSS adoption intention. Our results offer possible future research directions and extend existing theoretical understanding of OSS adoption.

The Impact of Ideology on the Organizational Adoption of Open Source Software

2009 ◽  
pp. 349-364
Author(s):  
Kris Ven ◽  
Jan Verelst
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Organizational Adoption ◽  
Adoption Decision ◽  
Small Organizations ◽  
The Impact

Previous research has shown that the open source movement shares a common ideology. Employees belonging to the open source movement often advocate the use of open source software within their organization. Hence, their belief in the underlying open source software ideology may influence the decision making on the adoption of open source software. This may result in an ideological—rather than pragmatic—decision. A recent study has shown that American organizations are quite pragmatic in their adoption decision. We argue that there may be circumstances in which there is more opportunity for ideological behavior. We therefore investigated the organizational adoption decision in Belgian organizations. Our results indicate that most organizations are pragmatic in their decision making. However, we have found evidence that suggests that the influence of ideology should not be completely disregarded in small organizations.

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