Pre-deployment field testing in is the process of testing software to uncover unforeseen problems before it is released in the market. It is commonly conducted by recruiting users to experiment with the software in as natural setting as possible. Information regarding the software is then sent to the developers as logs. Log data helps developers fix bugs and better understand the user behaviors so they can refine functionality to user needs. More importantly, logs contain specific problems as well as call traces that can be used by developers to trace its origins. However, developers focus their analysis on post-deployment data such as bug reports and CVS data to resolve problems, which has the disadvantage of releasing software before it can be optimized. Therefore, more techniques are needed to harness field testing data to reduce post deployment problems. We propose techniques to process log data generated by users in order to resolve problems in the application before its deployment. We introduce a metric system to predict the user perceived quality in software if it were to be released into market in its current state. We also provide visualization techniques which can identify the state of problems and patterns of problem interaction with users that provide insight into solving the problems. The visualization techniques can also be extended to determine the point of origin of a problem, to resolve it more efficiently. Additionally, we devise a method to determine the priority of reported problems. The results generated from the case studies on mobile software applications. The metric results showed a strong ability predict the number of reported bugs in the software after its release. The visualization techniques uncovered problem patterns that provided insight to developers to the relationship between problems and users themselves. Our analysis on the characteristics of problems determined the highest priority problems and their distribution among users. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2009-09-16 17:50:31.094

Providing service via theWeb differs from other service provision environments in that it is possible for the unexpected arrival of a massive number of service requests in a small time-frame, a situation commonly referred to as a flash crowd. Events of this nature are beyond the control of the service provider, and have the potential to severely degrade service quality and, in the worst case, to deny service to all clients completely. The occurrence, severity and sought Web content of a flash crowd is beyond the control of service provision software. How this software reacts to such a flash crowd, however, is not. Given the short-lived nature of flash crowds, it is unreasonable to expect such systems to increase the system resources they can apply to a particular flash crowd event. It is also difficult to predict the particular nature of any flash crowd, and subsequently which system resources will bottleneck. The driving hypothesis of this research is that, if we are to reasonably expect to have software react effectively to flash crowd events, we need to alter that software at runtime to remove system bottlenecks, whilst a flash crowd event is in progress. This is a special case of what is usually known as "unanticipated software evolution". This thesis reports on an investigation into how unanticipated software evolution can be applied to running Web service provision software to remove system bottlenecks. It does so by introducing automated dynamic Web content degradation to running software currently subject to simulated flash crowd events. The thesis describes and validates appropriate runtime extensions to allow generative object communication architectures (a promising class of architecture for unanticipated software evolution) to be converted initially into a Web application server, and then later accept further runtime behaviour changes. Such changes could alter system bottlenecks by replacing the key programming logic causing system bottlenecks at runtime.

User experience is today widely known but the complexity of this phenomenon is rarely left unnoticed. It is righteous to claim that the mobile application landscape is characterized by tough competition and high demands from users. To meet these demands the performance of the application is essential. There appears to exist consensus in existing literature regarding the importance of performance attributes for the user experience of mobile applications. However, there is limited research on how startup time is perceived and its effects on the user experience. Hence, this thesis aims to contribute to this field by investigating the formulated research question: To what extent does startup performance affect the user experience for a mobile application? Using a mixed method approach, this research aims to deepen the understanding of how end users of mobile applications perceive performance. The quantitative part of this study investigates what proxy variables that affect the performance during the startup process of a mobile application. The qualitative part aims to assess how users perceive startup time with respect to influencing factors and the effects on user experience. / Användarupplevelse är idag ett välkänt men komplext fenomen. Marknaden för mobila applikationer karaktäriseras av hård konkurrens och höga krav från användarna där tidigare studier har fastställt att prestanda-attribut har betydelse för användarupplevelsen. Det finns däremot begränsad empirisk litteratur kring hur prestanda uppfattas av användarna och effekterna på användarupplevelsen. Det är inom detta område som denna uppsats syftar till att bidra med kunskap. Detta genom att undersöka och besvara den formulerade forskningsfrågan: I vilken utsträckning påverkar start-prestandan användarupplevelsen för en mobilapplikation? Genom att använda en kombination av kvantitativa och kvalitativa metoder, syftar studien till att öka förståelsen kring hur användare av mobila applikationer uppfattar prestanda. Den kvantitativa studien undersöker vilka proxy-variabler som påverkar starttiden för en mobilapplikation. Den kvalitativa studien syftar följaktligen till att utvärdera hur användare uppfattar starttiden för en mobilapplikation med hänsyn till externa faktorer och dess effekt på användarupplevelsen.