Transformation of OSS

Fitzgerald (2006) poses a different framework for the progress and transition that open source software has undergone. He coins the phrase of open source software 2.0. At first open source software grew from software hackers with altruistic goals to save the world. As the evolvution continued, Fitzgerald believes that open source has morphed into a commercial enterprise where the software is free, but an entire industry has grown to support the software.

Fitzgerald (2006) offers a great comparison of FOSS (free open source software) and his new phenomenon OSS 2.0 (open sources software 2.0). His framework chart analyzes the differences between the two phenomena in regards to development life cycle, product domains, primary business strategies, product support, and licensing. As all technology advances, so does OSS. He makes excellent points in the shift dynamics of how OSS develops and operates now compared to yesterday. The OSS development of today is less like the original Eric Raymond’s “Bazaar style” and more strategic especially in respects to its business model, commercial support, and paid developers.

Reference

Fitzgerald, B. (2006). The transformation of open source software. MIS Quarterly, 30(3), 587-598. Retrieved from http://search.proquest.com/docview/218121722?accountid=26967

Decision Support Systems in OSS

Alavi and Joachimsthaler (1992) conducted research from a quantitative view of the empirical decision support system implementation literature to provide guidelines for implementing open source software project management. According to the authors, most theorists who have approached this issue from a cognitive stance agree that users solve problems and make decisions through the processing and utilization of information. Additionally, the authors point out that the decision support systems tend to focus on the analysis/heuristic dimension of research. In their research Alavi and Joachimsthaler (1992) discuss their variables of personality, demographics, and user situations. The authors also sought out articles from many avenues (working papers, dissertations, and conferences) to receive a better view of the research. Thus, their meta-analytic findings provide a more objective assessment of the strength of relationships between variables of interest than could be found by reviewing just journal articles.

Through the meta-analysis methodology, the authors reported their results in three sections: user factors, decision support systems implementation success variables and research methodology characteristics. From their research, they accomplished two specific objectives. First, they showed that user factors do impact decision support systems implementation success. This conclusion illustrates that the user situational variables are more important than individual differences and that manipulating user situational variables can improve the implementation success rate up to 30 percent. Secondly, they estimated the magnitudes of effects that can be expected in research which will serve as benchmarks for future studies.

Reference

Alavi, M., & Joachimsthaler, E. A. (1992). Revisiting DSS implementation research: A meta-analysis of the literature and suggestions for researchers. MIS Quarterly, 16(1), 95-117. Retrieved from http://search.proquest.com/docview/218129596?accountid=26967

Impact of Goals on Project Management

Tarek, Sengupta and Swett (1999) discuss the impact of goals on project management in their article and the effect it has on the progress of the project. Many have studied organizational behavior and the important of establishing goals. However, a literature gap remained in an empirical sense regarding the effect on projects that fail to meet goals and deadlines. Tarek, Sengupta and Swett's (1999) article explores the impact of project goals on managerial decision making in a project environment.

They investigated the differences that goals have on managerial planning and staffing decisions. Their research question explored their hypothesis in a role playing project simulation, where participants played the role of a software project manager. The two structures that were evaluated consisted of a cost/schedule structure and a quality/schedule structure. The experimental design goals involved minimizing overruns in both cost and schedule, and delivery of a quality product and schedule overruns.

Tarek, Sengupta and Swett (1999) discovered several specific results. First, the cost group preferred smaller cost adjustments and were more willing to extend the project completion timeline. On the other hand, the quality group increased the staff level in the later stages of the project and allocated more resources to the quality assurance of the project.

Since the goals did influence the project planning, the authors also examined whether goals affected cost, duration and quality of the project. The results showed that the quality group remained strong at meeting deadlines and goals, and therefore, the project’s cost tended to increase significantly. On the other hand, the cost group consistently under invested in the project which prolonged the timeline and often reduced the project’s quality.

Reference

Tarek, K. A., Sengupta, K., & Swett, C. (1999). The impact of goals on software project management: An experimental investigation. MIS Quarterly, 23(4), 531-555. Retrieved from http://search.proquest.com/docview/218117515?accountid=26967

Cross-Cultural Software Production

Walsham (2002) examines cross cultural software production by applying structuration theory. He illustrates his research through two case studies. The research focuses on four key elements (cross cultural contradiction and conflict, cultural heterogeneity, detailed work patterns in different cultures, and the dynamic nature of culture) to emphasis his hypothesis that the structuration theory enables a more sophisticated and detailed consideration of issues in cross cultural software production. Structuration theory describes the nature of human action and social organization. The theory views action and structure as two aspects of the same whole rather than seeing action take place within the constraints of social structure. Within the two case studies, Walsham (2002) defines and analyzes structure, culture, cross-cultural contradiction and conflict, and reflexivity and change. Through his analysis, Walsham (2002) creates a comparison table of different theories to illustrate his concept that structuration theory provides the most detailed outcome.

Walsham (2002) draws conclusions that business can achieve cross cultural education and training through readings, formal trainings, and on the job facilitation. To assist with the goals, he recommends open discussions about difficult cross cultural issues as starting points to increase understanding in cross cultural teams.

References

Walsham, G. (2002). Cross-cultural software production and use: a structurational analysis. MIS quarterly, 359-380.

Divisions of Skills within OSS Projects

Giuri, Ploner, Rullani, and Torrisi (2010) analyze the talent, groupings, and performance of open source software (OSS) projects within Sourceforge.net. The hypothesis relevant to my research pertains to the project performance affected by the modularity of tasks within the project. Giuri, Ploner, Rullani, and Torrisi (2010) did not have access to the source code, so the modularity does not concern the code, but rather the concept of the project being divided into several subprojects. Additionally, the authors focused on the activity within each of the subprojects and the activity’s affect on the whole project. Activity is defined as a fixed bug, patch, or new enhancement developed through a request and released in an update, product release, or CVS (concurrent version system) commitment.

They concluded that the organizational modularity of the project does have a positive effect on the project; however, the outcome of modularity to performance is nonlinear. Additional support to project performance arrives through developer skill level. Across the membership, the standard deviation of the experience level and skills remain significant when the equation includes controls. Moreover, the data points to better performance with segregation among member skill levels. The project profits from grouping specialists, generalists, high level members and low level members separately.

On the other hand, the study also suggests a negative consequence to interaction among skill diversity and modularity at the project level. The results lead to the concept that two organizational approaches exist: a “workshop-like” and “factory-like” organization. The workshop arena relies on its members with diversified skills who multitask; whereas, the factory concept involves high modularity and relatively low level skill diversity.

Reference

Giuri, P., Ploner, M., Rullani, F., & Torrisi, S. (2010). Skills, division of labor and performance in collective inventions: Evidence from open source software. International Journal of Industrial Organization, 28(1), 54-68.

Evaluating OSS Projects

Wray and Mathieu’s (2008) article, Evaluating the Performance of Open Source Software Projects Using Data Envelopment Analysis, parallels my research. The study provided excellent insights onefficiency of open source software (OSS). Wray and Mathieu (2008) limited their study to only security based OSS projects, which consisted of 34 projects. The study also utilized a limited number of inputs and outputs with the data envelopment analysis (DEA) model. In my research I hope to further their study by encompassing more projects along with more inputs and outputs in my DEA model.

DEA is a nonparametric linear programming formulation technique that accounts for multiple inputs and outputs to measure the efficiency of decision making units (DMU). In this study and my research, a DMU represents an OSS project. In essence, the DEA will rank DMU in order ofefficiency. From the results, we will be able to discover the indicators of successful efficient software development projects.

Wray and Mathieu (2008) selected OSS developers and bug submitters from 34 security projects on SourceForge.net as their input variables for the DEA. For their output measures, the study focused on the number of software downloads and the SourceForge.net project rank. SourceForge.net is the world’s largest OSS project hosting database that houses over 100,000 OSS projects with over 1 million registered users. SourceForge.net ranks projects weekly based upon traffic, communication, and development statistics collected on each project.

Wray and Mathieu (2008) discovered that the most relative efficient projects when compared to the others were Ophcrack, ClamWin FreeAntivirus, Simple Python Keylogger for Windows, ShellTer, Another File Integrity Checker, Network Security Toolkit, J2EE Certificate Authority, and BlockSSHD. The research conclusions can be used by security based OSS project managers to determine the relative efficiency of their project against other similar projects. The study can help with critical decisions on work effort allotment to project areas and assignments to produce larger yields and benefits.

Reference

Wray, B., & Mathieu, R. (2008). Evaluating the performance of open source software projects using data envelopment analysis. Information Management & Computer Security, 16(5), 449-462.

Measuring Success in OSS Projects

Ghapanchi, Aurum and Low (2011) collect open source software (OSS) literature and try to discover a commonality of the definition for success in OSS projects. The authors concentrated on OSS because it is unlike proprietary software due to its reliance on volunteer community members as developers, bug reporters, document writers, and troubleshooters. OSS projects have proven to be very beneficial and profitable; however, the majority of the OSS projects fail. The authors search through literature to find what makes certain OSS projects successful or at least a guage to measure the project's success.

The authors identified six broad measures for success in an OSS project. The measures included project activity, project efficiency, project effectiveness, project performance, user interest, and product quality. Ghapanchi, Aurum, and Low (2011) developed a chart that classified existing OSS literature into one of these six measures.

Additionally, they continued to define and explain the six measures. They describe project activity as one of the pillars of OSS project success. Activity stems production and growth along with product interests. Project efficiency involves maximum outputs from the projects available resources. Project effectiveness entails producing an effect or outcome. Project performance focuses on different measures to evaluate project outcomes during development. User interests are defined as the ability of an OSS project to attract community members to adopt the software. Finally, product quality deals with the software quality as an output from the development process.

Through these defined measures of success, the authors offer insight for both practitioners and researchers. The article offers an excellent resource for defining success and points to other excellent articles that I will read in the near future to grow my literature review.

Ghapanchi, A., Aurum, A., & Low, G. (2011). A taxonomy for measuring the success of open source software projects. First Monday, 16(8).

OSS Socialization

Qureshi and Fang (2011) approach open source software (OSS) projects in a slightly unique way using the socialization of a growth mixture model (GMM). They point out that there is a significant lack of literature involving the socialization of joiners in OSS projects. In this article, a joiner is defined as a community peripheral developer (a user that submit code for bug fixes and enhancements) that has been accepted as a core developer (a user who has access to update the source code). Additionally, the article defines the GMM as an analytical technique that summarizes data by modeling both intraindividual and interindividual variability in development trajectories through indentifying subpopulations, in this case joiners.

Qureshi and Fang (2011) hope to discover a common script that peripheral developers can follow in order to be accepted as core developers of an OSS project. Additionally, they wish to differentiate between the socialization patterns of peripheral developers moving towards becoming a core developer opposed to permanent peripheral developers.

Their sample included 870 joiners from 62 different OSS projects. In addition, they measured the level of socialization at a specific week in regards to the number of joiners' interactions with core developers on mailing lists. As they conducted the experiment, they developed a flow chart to illustrate the measurement process and the GMM.

Qureshi and Fang (2011) found two main results. First, they discovered that the joiner's discussions with core developers occur in a nonlinear growth trajectory. Secondly, they found joiners begin with different initial levels and follow different growth trajectories. Through observations of the different growth trajectories, they identify four latent trajectory classes. Additionally, the latent trajectory classes are connected with different time periods to attain the core developer status.

Furthermore, their results illustrate several important points of theory development with regards to socialization roles with core developers influencing the joiner's status the most.

Reference

Qureshi, I., & Fang,Y. (2011). Socialization in open source software projects: A growth mixture modeling approach. Organizational Research Methods, 14(1), 208-239.

OSS Hackerdom

Eric Steven Raymond, super mind in open source software, wrote multiple ground breaking articles and books explaining and analyzing the software world. He mostly focuses on open source and the hacker culture. Raymond (2000) wrote an excellent article titled, "A Brief History of Hackerdom" that outlines the events that lead to the culture of volunteer programmers.

Starting in 1945, the technology of computing attracted the world's brightest and most creative minds. "Real Programmers," a phrase eventually coined in the 1980s, wrote machine language code that was both artistic and eloquent. Real Programmers built and played with software for fun.

Most will agree that the hacker culture began in 1961 when MIT acquired the first PDP-1. The Tech Model Railroad Club became the center of MIT's artificial intelligent laboratory. Their culture grew with the introduction of ARPnet in 1969. The first artifacts of the hacker culture developed around 1973 to 1975 when the Jardon File launched across the ARPnet. The Jargon File later became published as "The Hacker's Dictionary."

Another important moment in the culture involved the XEROX PARC, the famed Palo Alto Research Center. From the early 1970s to the mid-1980s, PARC invented amazing hardware and software innovations, including mice, windows, icons, laser printers, and local area networks.

As a result of the innovations, three cultures stood in the 1980s: the ARPnet/PDP-10, Unix & C crowd, and microcomputer enthusiasts. During this period, Richard Stallman organized the Free Software Foundation, dedicated to producing high quality free software.

After 1987, Intel released an inexpensive chip set that made home computing affordable for the first time. Shortly afterwards, Linus Torvalds developed a free Unix kernel for 386 machines. Linux offered a full feature Unix OS with entirely free and redistributable source code. The ground breaking Linux OS evolved in an entirely unique way with a large number of volunteers coordinating over the Internet to develop the OS. The Internet was key in the Linux development. The Internet came to homes for the first time for only a few dollars and with the newly invented world wide web.

Reference

Raymond, E. S. (2000). A brief history of hackerdom. Thyrsus Enterprises. Retrieved February 22, 2012 from http://www.immagic.com/eLibrary/ARCHIVES/GENERAL/AUTHOR_P/R000825P.pdf .

Future Research in Open Source Software

Scacchi (2010), a leading researcher in open source software (OSS), discusses trends in his ACM conference proceeding, The Future of Research in Free/Open Source Software Development. Even though many take advantage of OSS, the computer science research community has not fully recognized OSS' potential to alter the research and development of software intensive systems. Millions of end users worldwide openly adopt and rely on tens of thousands of OSS projects. With such a high adoption rate, a growing number of research projects in physical, social, and human sciences have started to examine and adopt OSS projects to meet their needs as well. OSS now represents an alternative community intensive socio-technical approach to programming software.

Many topics involving OSS still need investigating and explaining. First, an individual developer’s interest, motivation and commitment to a project and its contributors are dynamic in terms of participating, joining, and contributing to an OSS project. Second, conflicts within OSS projects arise from technical decision making, such as who is in charge of which aspects of the project. Third, building communities and alliances points towards more dependency on the OSS projects. Fourth, the socio-technical web of OSS projects in terms of shared resources poses questions of how this dynamic structure solidifies. Lastly, more empirical studies that analyze, discover, and learn the large OSS ecosystem are needed.

Scacchi (2010) concludes by saying OSS development is emerging as an alternative approach to develop large software systems. OSS employs socio-technical practices, development processes, and community networking. OSS offer new practices, processes, and projects for study and comparison to the tradition software model. Many new research opportunities exist in the empirical examination, modeling, and simulation of OSS projects.

Reference

Scacchi, W. (2010). The Future of Research in Free/Open Source Software Development. ACM conference proceedings.

Open Source Software Movement

Carillo and Okoli (2009) discuss the open source software (OSS) movement as it relates to copyright and intellectual property law in The Open Source Movement: A Revolution in Software Development. According to Carillo and Okoli (2009), OSS appeared before proprietary software. The OSS mentality guided all software development. Richard Stallman organized the movement through the Free Software Foundation by defining and defusing legal mechanisms for the free software. OSS grants users the full right to the source code, to run the software for any purpose, to modify the source code and to distribute the software.

Even though OSS is free, businesses can still make a profit from installing and supporting OSS. Linus Torvalds, a Finnish programmer, started the Linux project that has exceeded $35.7 billion in profit by 2008. Raymond illustrates and paints an excellent picture of software development in his book, The Cathedral and the Bazaar. The book discusses the Mozilla project formation from the Netscape Communicator source code. Raymond explains the different mentalities of open and closed software development.

Carillo and Okolio (2009) continue to remark on the radical change in software development brought about by the OSS movement. The OSS movement has not only created high quality software, but it has also created a new type of virtual community. Moreover, the effects are having far reaching impacts influencing the way people view software. Furthermore, OSS is significantly shifting the conception of intellectual property rights view.

Reference

Carillo, K., & Okoli, C. (2009). The open source movement: A revolution in software development. The Journal of Computer Information Systems. Winter 2009. 49(2).

Open Source Software Developer Networks

Hahn, Moon and Zhang (2010) investigate the impact of new open source software (OSS) success based on the developers past relationships with developers on previous projects. OSS has many high profile cases that have performed extraordinarily well, such as Apache, Linux, OpenOffice, and PHP. On the other hand, the large majority of OSS projects fail due to the inability to attract a large number of developers to contribute to the project. In this study Hahn, Moon and Zhang (2010) focus on OSS project teams forming and more specifically on the joining behaviors of developers. Through an empirical test, they discovered that the previous relationships with other developers do increase the probability that an OSS project will attract more developers. Additionally, the study found that a prior developer’s tie with a project initiator increases the probability that a developer will join a project started by a past collaborator. Therefore, past ties with developers increases the probability of the OSS project success. Evidence of their study follows the critical mass theory and resource dependence theory. Participants will join a project only if it is perceived value is high and some of the perceived value comes from the developers who create the software. Additionally, if a project fails to attract developers in the early stages it will also fail to attract developers in subsequent development stages.

Reference

Hahn, J., Moon, J.Y., & Zhang, C. (2010). Emergence of new project teams from open source software developer networks: Impact of prior collaboration ties. Information Systems Research, 19(3), 369-405.

Floss Road Map

In the 2010 edition of the 2020 FLOSS Roadmap, Laisne, Aigrain, Bollier, and Tieman (2010) address the start of the Commons paradigm, the nature of FLOSS being global and cloud computing appearing as the key issues for FLOSS. The roadmap offers a projection of the influences that FLOSS will have up to 2020 and highlights possible impacts by FLOSS from a economical view in the information society. Additionally, the roadmap examines the questions of how openness is instrumental to modern innovation, how openness can improve industry, and how certain areas of the government could benefit from becoming more open.

Moreover, the roadmap points out the constraints that average users run up against as technology progress. One important constraint involves financial resources. The economic crisis and technological inflation pose the main cause to limited financial funds. FLOSS or Free/Libre Open Source Software offer a possible solution to easing financial burdens. Maintenance and customizing FLOSS still will cost, but the initial package is free. Another important constraint is security. Cyber criminals and privacy protection are the main concerns of security. FLOSS offers several unique advantages over closed software. First, the source code is available for the entity to patch or customize. Secondly, an entire community with many eyes look over the code, quick to point out flaws and security holes. Additionally, FLOSS developers are quick to release patches and new releases.

Furthermore, FLOSS is more than just innovative technology. Our global economy yearns for improvement and advancement. Technological progress in communication and information through FLOSS communities can help leverage entities’ efficiency and maximize profits. “FLOSS has tangible social value exceeding the social value created by closed and proprietary developments profitable only by the wealthiest.” (Laisne, Aigrain, Bollier,and Tieman, 2010, p. 12)

FLOSS contributes significantly to building prosperity and promises future economic advantages through shared knowledge. The FLOSS economy includes people and does not exclude them like closed systems. Additionally, FLOSS limits resistance in the digital society and leverages creation and innovation. However, FLOSS’ fate relies on the adoption of a powerful uniformed vision. The Commons paradigm provides the foundation, but only the future will show the adoption rate of FLOSS.

References

Laisne, J., Aigrain, P., Bollier, D., and Tieman, M. (2010). 2020 FLOSS Roadmap. Retrieved March 19, 2012 from http://www.2020flossroadmap.org/.