Matching Items (3)
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- All Subjects: Computer software--Development.
- Creators: Collofello, James
Description
Smartphones have become increasingly common over the past few years, and mobile games continue to be the most common type of application (Apple, Inc., 2013). For many people, the social aspect of gaming is very important, and thus most mobile games include support for playing with multiple players. However, there is a lack of common knowledge about which implementation of this functionality is most favorable from a development standpoint. In this study, we evaluate three different types of multiplayer gameplay (pass-and-play, Bluetooth, and GameCenter) via development cost and user interviews. We find that pass-and-play, the most easily-implemented mode, is not favored by players due to its inconvenience. We also find that GameCenter is not as well favored as expected due to latency of GameCenter's servers, and that Bluetooth multiplayer is the most well favored for social play due to its similarity to real-life play. Despite there being a large overhead in developing and testing Bluetooth and GameCenter multiplayer due to Apple's development process, this is irrelevant since professional developers must enroll in this process anyway. Therefore, the most effective multiplayer mode to develop is mostly determined by whether Internet play is desirable: Bluetooth if not, GameCenter if so. Future studies involving more complete development work and more types of multiplayer modes could yield more promising results.
ContributorsBradley, Michael Robert (Author) / Collofello, James (Thesis director) / Wilkerson, Kelly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
The following is a case study composed of three workflow investigations at the open source software development (OSSD) based Apache Software Foundation (Apache). I start with an examination of the workload inequality within the Apache, particularly with regard to requirements writing. I established that the stronger a participant's experience indicators are, the more likely they are to propose a requirement that is not a defect and the more likely the requirement is eventually implemented. Requirements at Apache are divided into work tickets (tickets). In our second investigation, I reported many insights into the distribution patterns of these tickets. The participants that create the tickets often had the best track records for determining who should participate in that ticket. Tickets that were at one point volunteered for (self-assigned) had a lower incident of neglect but in some cases were also associated with severe delay. When a participant claims a ticket but postpones the work involved, these tickets exist without a solution for five to ten times as long, depending on the circumstances. I make recommendations that may reduce the incidence of tickets that are claimed but not implemented in a timely manner. After giving an in-depth explanation of how I obtained this data set through web crawlers, I describe the pattern mining platform I developed to make my data mining efforts highly scalable and repeatable. Lastly, I used process mining techniques to show that workflow patterns vary greatly within teams at Apache. I investigated a variety of process choices and how they might be influencing the outcomes of OSSD projects. I report a moderately negative association between how often a team updates the specifics of a requirement and how often requirements are completed. I also verified that the prevalence of volunteerism indicators is positively associated with work completion but what was surprising is that this correlation is stronger if I exclude the very large projects. I suggest the largest projects at Apache may benefit from some level of traditional delegation in addition to the phenomenon of volunteerism that OSSD is normally associated with.
ContributorsPanos, Ryan (Author) / Collofello, James (Thesis advisor) / Fowler, John (Thesis advisor) / Pan, Rong (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2017
Description
Affect signals what humans care about and is involved in rational decision-making and action selection. Many technologies may be improved by the capability to recognize human affect and to respond adaptively by appropriately modifying their operation. This capability, named affect-driven self-adaptation, benefits systems as diverse as learning environments, healthcare applications, and video games, and indeed has the potential to improve systems that interact intimately with users across all sectors of society. The main challenge is that existing approaches to advancing affect-driven self-adaptive systems typically limit their applicability by supporting the creation of one-of-a-kind systems with hard-wired affect recognition and self-adaptation capabilities, which are brittle, costly to change, and difficult to reuse. A solution to this limitation is to leverage the development of affect-driven self-adaptive systems with a manufacturing vision.
This dissertation demonstrates how using a software product line paradigm can jumpstart the development of affect-driven self-adaptive systems with that manufacturing vision. Applying a software product line approach to the affect-driven self-adaptive domain provides a comprehensive, flexible and reusable infrastructure of components with mechanisms to monitor a user’s affect and his/her contextual interaction with a system, to detect opportunities for improvements, to select a course of action, and to effect changes. It also provides a domain-specific architecture and well-documented process guidelines, which facilitate an understanding of the organization of affect-driven self-adaptive systems and their implementation by systematically customizing the infrastructure to effectively address the particular requirements of specific systems.
The software product line approach is evaluated by applying it in the development of learning environments and video games that demonstrate the significant potential of the solution, across diverse development scenarios and applications.
The key contributions of this work include extending self-adaptive system modeling, implementing a reusable infrastructure, and leveraging the use of patterns to exploit the commonalities between systems in the affect-driven self-adaptation domain.
This dissertation demonstrates how using a software product line paradigm can jumpstart the development of affect-driven self-adaptive systems with that manufacturing vision. Applying a software product line approach to the affect-driven self-adaptive domain provides a comprehensive, flexible and reusable infrastructure of components with mechanisms to monitor a user’s affect and his/her contextual interaction with a system, to detect opportunities for improvements, to select a course of action, and to effect changes. It also provides a domain-specific architecture and well-documented process guidelines, which facilitate an understanding of the organization of affect-driven self-adaptive systems and their implementation by systematically customizing the infrastructure to effectively address the particular requirements of specific systems.
The software product line approach is evaluated by applying it in the development of learning environments and video games that demonstrate the significant potential of the solution, across diverse development scenarios and applications.
The key contributions of this work include extending self-adaptive system modeling, implementing a reusable infrastructure, and leveraging the use of patterns to exploit the commonalities between systems in the affect-driven self-adaptation domain.
ContributorsGonzalez-Sanchez, Javier (Author) / Burleson, Winslow (Thesis advisor) / Collofello, James (Thesis advisor) / Garlan, David (Committee member) / Sarjoughian, Hessam S. (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2016