Points-to analysis is a static program analysis that tries to predict the dynamic behavior of programs without running them. It computes reference information by approximating for each pointer in the program a set of possible objects to which it could point to at runtime. In order to justify new analysis techniques, they need to be compared to the state of the art regarding their accuracy and efficiency. One of the main parameters influencing precision in points-to analysis is context-sensitivity that provides the analysis of each method separately for different contexts it was called on. The problem raised due to providing such a property to points-to analysis is decreasing of analysis scalability along with increasing memory consumption used during analysis process. The goal of this thesis is to present a comparison of precision and scalability of context-sensitive and context-insensitive analysis using three different points-to analysis techniques (Spark, Paddle, P2SSA) produced by two research groups. This comparison provides basic trade-offs regarding scalability on the one hand and efficiency and accuracy on the other. This work was intended to involve previous research work in this field consequently to investigate and implement several specific metrics covering each type of analysis regardless context-sensitivity – Spark, Paddle and P2SSA. These three approaches for points-to analysis demonstrate the intended achievements of different research groups. Common output format enables to choose the most efficient type of analysis for particular purpose.

This study investigates the impact of CALL training on in-service language teachers&rsquo / use of CALL-based activities in their classrooms and what factors influence their use of these activities in their classroom. The participants included 35 pre-service English as a Foreign Language (EFL) teachers who took an undergraduate-level elective CALL course (FLE318) offered during the 2008-2009 academic year in the Department of Foreign Language Education at Middle East Technical University and 25 of these participants who started teaching English during the Fall semester in the academic year 2009-2010 at several private and state institutions. Both quantitative and qualitative research methods were applied. The journals kept by the participants during and after the training, the lesson plans of micro and macro teaching, the questionnaires given to the participants to determine their perceived computer knowledge, the interview sessions held with the participants&rsquo / on their practices showed that the training provided to the participants helped them infuse a variety of CALL-based materials and tools into their classroom practices. The analyses also indicated that the most paramount factors or issues that affect the infusion of CALL-based materials in language teaching and learning are the school environment, curriculum, and the national exams.

This study investigated beliefs of members of an online Community of Practice (WIA) on the role of the community on professional development, teaching, and on Web 2.0 use. Through the analyses of the questionnaire, it was aimed at finding out the members&rsquo / ideas about the group as an online CoP and benefits of belonging to an online CoP. The data were collected from seventy nine members of the Webheads in Action from various countries by using an online questionnaire. Then, the responses to the multiple choice items were analyzed using PASSW. The data collected from the last section of the questionnairre were analyzed through content analysis and pattern coding. The findings revealed that the members believe that WIA plays an important role in the process of developing multiltiteracies skills and the Web 2.0 tools used in classroom teaching and for professional development. The findings also revealed that the participants believe that being a WIA member leads to motivation, collaboration and discovery. These beliefs are thought to provide insights about the advantages and disadvantages of learning in online CoPs and their effects on the members&rsquo / Web 2.0 use. The findings can also be beneficial for researchers, teacher trainers, and teachers wishing to join CoPs for professional development. They can understand the advantages and disadvantages, and the participation process in more detail. Moreover, these findings can indicate that online CoPs can provide a medium for coping with the increasing amount of information thanks to the recent technological developments, and acquiring new skills.

This study investigated beliefs of members of an online Community of Practice (WIA) on the role of the community on professional development, teaching, and on Web 2.0 use. Through the analyses of the questionnaire, it was aimed at finding out the members&rsquo / ideas about the group as an online CoP and benefits of belonging to an online CoP. The data were collected from seventy nine members of the Webheads in Action from various countries by using an online questionnaire. Then, the responses to the multiple choice items were analyzed using PASSW. The data collected from the last section of the questionnairre were analyzed through content analysis and pattern coding. The findings revealed that the members believe that WIA plays an important role in the process of developing multiltiteracies skills and the Web 2.0 tools used in classroom teaching and for professional development. The findings further revealed that the participants believe that being a WIA member leads to motivation, collaboration and discovery. These beliefs are thought to provide insights about the advantages and disadvantages of learning in online CoPs and their effects on the members&rsquo / Web 2.0 use. The findings can also be beneficial for researchers, teacher trainers, and teachers wishing to join CoPs for professional development. They can understand the advantages and disadvantages, and the participation process in more detail. Moreover, these findings can indicate that online CoPs can provide a medium for coping with the increasing amount of information thanks to the recent technological developments, and acquiring new skills.

Customer call centers with hundreds of agents working in parallel are ubiquitous in many industries. These systems have a large amount of daily traffic that is stochastic in nature. It becomes more and more difficult to manage a call center because of its increasingly large scale and the stochastic variability in arrival and service processes. In call center operations, customer abandonment is a key factor and may significantly impact the system performance. It must be modeled explicitly in order for an operational model to be relevant for decision making. In this thesis, a large-scale call center is modeled as a queue with many parallel servers. To model the customer abandonment, each customer is assigned a patience time. When his waiting time for service exceeds his patience time, a customer abandons the system without service. We develop analytical and numerical tools for analyzing such a queue. We first study a sequence of G/G/n+GI queues, where the customer patience times are independent and identically distributed (iid) following a general distribution. The focus is the abandonment and the queue length processes. We prove that under certain conditions, a deterministic relationship holds asymptotically in diffusion scaling between these two stochastic processes, as the number of servers goes to infinity. Next, we restrict the service time distribution to be a phase-type distribution with d phases. Using the aforementioned asymptotic relationship, we prove limit theorems for G/Ph/n+GI queues in the quality- and efficiency-driven (QED) regime. In particular, the limit process for the customer number in each phase is a d-dimensional piecewise Ornstein-Uhlenbeck (OU) process. Motivated by the diffusion limit process, we propose two approximate models for a GI/Ph/n+GI queue. In each model, a d-dimensional diffusion process is used to approximate the dynamics of the queue. These two models differ in how the patience time distribution is built into them. The first diffusion model uses the patience time density at zero and the second one uses the entire patience time distribution. We also develop a numerical algorithm to analyze these diffusion models. The algorithm solves the stationary distribution of each model. The computed stationary distribution is used to estimate the queue's performance. A crucial part of this algorithm is to choose an appropriate reference density that controls the convergence of the algorithm. We develop a systematic approach to constructing a reference density. With the proposed reference density, the algorithm is shown to converge quickly in numerical experiments. These experiments also show that the diffusion models are good approximations of queues with a moderate to large number of servers.

In the next generation of networks we will begin to see the true convergence of voice, multimedia, and data traffic. This merging of various dedicated networks will occur both in the wired and wireless domains. Given the growth in the areas of wireless voice and data, we see that the combination of mobile and Internet communication constitutes the driving force behind the third-generation wireless system and makes the basis for the fourth-generation wireless system. For services like voice over IP over wireless (VoIPoW), the main challenge is to achieve QoS and spectrum efficiency. In order to support better QoS the IETF Mobile IP Working Group is discussing a number of enhancements to the base protocol to reduce the latency, packet loss and signaling overhead experienced during handoff. This support also includes both the call admission and the subsequent scheduling of packet transmissions. In this thesis, we will first survey the work done on issues related to QoS provisioning for wireless network and then will address bandwidth allocation problem in packet radio network with special emphasis on wireline to wireless internetworking zone. The main aim of the thesis is to evolve a strategy to reduce the call dropping probability by negotiating the QoS in those conditions when we do not have the sufficient resources (mainly bandwidth) to allocate. In order to achieve the QoS we have investigated the behaviour of the Real-time Voice traffic on a wireless link and its relation to the associated quality of service. This investigation opens a way for QoS negotiation, in a condition like during handoff, when the network is not able to sustain the negotiated bandwidth. The main results of this work are, that even with reduced bandwidth, quality for speech can be maintained at a reasonable level and this way the call dropping can be reduced. Such a scheme is useful in those conditions when we do not have the sufficient bandwidth to allocate like during a handoff of a mobile host from one cell to another. Moreover the bandwidth is a scarce resource in wireless domain so there should be an efficient call admission control policy. Many call admission control policies are proposed in the literature; here we propose a simple scheme for real-time traffic, specially speech, in a base station which increases the system throughput. In addition to above, we have also experimented with Cellular IP, one of the implementations of proposed micro-mobility architecture to provide faster handoff and seamless mobility in wired and wireless network.

This thesis concerns anomaly detection as a mechanism for intrusion detection in a machine learning framework, using two kinds of audit data : system call traces and Unix shell command traces. Anomaly detection systems model the problem of intrusion detection as a problem of self-nonself discrimination problem. To be able to use machine learning algorithms for anomaly detection, precise definitions of two aspects namely, the learning model and the dissimilarity measure are required. The audit data considered in this thesis is intrinsically sequential. Thus the dissimilarity measure must be able to extract the temporal information in the data which in turn will be used for classification purposes. In this thesis, we study the application of a set of dissimilarity measures broadly termed as sequence kernels that are exclusively suited for such applications. This is done in conjunction with Instance Based learning algorithms (IBL) for anomaly detection. We demonstrate the performance of the system under a wide range of parameter settings and show conditions under which best performance is obtained. Finally, some possible future extensions to the work reported in this report are considered and discussed.

The thesis presents a contribution to the analysis and visualization of computational performance based on event traces with a particular focus on parallel programs and High Performance Computing (HPC). Event traces contain detailed information about specified incidents (events) during run-time of programs and allow minute investigation of dynamic program behavior, various performance metrics, and possible causes of performance flaws. Due to long running and highly parallel programs and very fine detail resolutions, event traces can accumulate huge amounts of data which become a challenge for interactive as well as automatic analysis and visualization tools. The thesis proposes a method of exploiting redundancy in the event traces in order to reduce the memory requirements and the computational complexity of event trace analysis. The sources of redundancy are repeated segments of the original program, either through iterative or recursive algorithms or through SPMD-style parallel programs, which produce equal or similar repeated event sequences. The data reduction technique is based on the novel Complete Call Graph (CCG) data structure which allows domain specific data compression for event traces in a combination of lossless and lossy methods. All deviations due to lossy data compression can be controlled by constant bounds. The compression of the CCG data structure is incorporated in the construction process, such that at no point substantial uncompressed parts have to be stored. Experiments with real-world example traces reveal the potential for very high data compression. The results range from factors of 3 to 15 for small scale compression with minimum deviation of the data to factors > 100 for large scale compression with moderate deviation. Based on the CCG data structure, new algorithms for the most common evaluation and analysis methods for event traces are presented, which require no explicit decompression. By avoiding repeated evaluation of formerly redundant event sequences, the computational effort of the new algorithms can be reduced in the same extent as memory consumption. The thesis includes a comprehensive discussion of the state-of-the-art and related work, a detailed presentation of the design of the CCG data structure, an elaborate description of algorithms for construction, compression, and analysis of CCGs, and an extensive experimental validation of all components. / Diese Dissertation stellt einen neuartigen Ansatz für die Analyse und Visualisierung der Berechnungs-Performance vor, der auf dem Ereignis-Tracing basiert und insbesondere auf parallele Programme und das Hochleistungsrechnen (High Performance Computing, HPC) zugeschnitten ist. Ereignis-Traces (Ereignis-Spuren) enthalten detaillierte Informationen über spezifizierte Ereignisse während der Laufzeit eines Programms und erlauben eine sehr genaue Untersuchung des dynamischen Verhaltens, verschiedener Performance-Metriken und potentieller Performance-Probleme. Aufgrund lang laufender und hoch paralleler Anwendungen und dem hohen Detailgrad kann das Ereignis-Tracing sehr große Datenmengen produzieren. Diese stellen ihrerseits eine Herausforderung für interaktive und automatische Analyse- und Visualisierungswerkzeuge dar. Die vorliegende Arbeit präsentiert eine Methode, die Redundanzen in den Ereignis-Traces ausnutzt, um sowohl die Speicheranforderungen als auch die Laufzeitkomplexität der Trace-Analyse zu reduzieren. Die Ursachen für Redundanzen sind wiederholt ausgeführte Programmabschnitte, entweder durch iterative oder rekursive Algorithmen oder durch SPMD-Parallelisierung, die gleiche oder ähnliche Ereignis-Sequenzen erzeugen. Die Datenreduktion basiert auf der neuartigen Datenstruktur der "Vollständigen Aufruf-Graphen" (Complete Call Graph, CCG) und erlaubt eine Kombination von verlustfreier und verlustbehafteter Datenkompression. Dabei können konstante Grenzen für alle Abweichungen durch verlustbehaftete Kompression vorgegeben werden. Die Datenkompression ist in den Aufbau der Datenstruktur integriert, so dass keine umfangreichen unkomprimierten Teile vor der Kompression im Hauptspeicher gehalten werden müssen. Das enorme Kompressionsvermögen des neuen Ansatzes wird anhand einer Reihe von Beispielen aus realen Anwendungsszenarien nachgewiesen. Die dabei erzielten Resultate reichen von Kompressionsfaktoren von 3 bis 5 mit nur minimalen Abweichungen aufgrund der verlustbehafteten Kompression bis zu Faktoren > 100 für hochgradige Kompression. Basierend auf der CCG_Datenstruktur werden außerdem neue Auswertungs- und Analyseverfahren für Ereignis-Traces vorgestellt, die ohne explizite Dekompression auskommen. Damit kann die Laufzeitkomplexität der Analyse im selben Maß gesenkt werden wie der Hauptspeicherbedarf, indem komprimierte Ereignis-Sequenzen nicht mehrmals analysiert werden. Die vorliegende Dissertation enthält eine ausführliche Vorstellung des Stands der Technik und verwandter Arbeiten in diesem Bereich, eine detaillierte Herleitung der neu eingeführten Daten-strukturen, der Konstruktions-, Kompressions- und Analysealgorithmen sowie eine umfangreiche experimentelle Auswertung und Validierung aller Bestandteile.

This thesis consists of four self-contained essays. Essay 1 (with Olof Åslund and Matz Dahlberg): In this essay we investigate the impact of commuter train access on individual labor market outcomes. Our study considers the exogenous introduction of a commuter train linking locations in the northern part of Uppsala County (Sweden) to the regional employment center, considerably decreasing commuting times by public transit to the center for those living close to the pre-existing railroad. Using difference-in-differences matching techniques on comprehensive individual panel data spanning over a decade, our intention-to-treat estimates show that the reform had mainly no impact on the earnings and employment development among the affected individuals. Essay 2: In this essay I look into the role of public transit for residential sorting by studying how the introduction of a commuter train linking locations in the northern part of Uppsala County (Sweden) to the regional employment center affected migration patterns in the areas served. Using a difference-in-difference(-in-difference) approach and comprehensive individual level data, I find that the commuter train had a positive effect on overall in-migration to the areas served and no effect on the average out-migration rate from these areas. With regards to sorting based on labor market status, I find no evidence of sorting based on employment status but some evidence that the train introduction increased the probability of moving out of the areas served for individuals with high labor incomes relative to the probability for individuals with lower income. Considering sorting along other lines than labor market status, the analysis suggests that people born in non-western countries came to be particularly attracted towards the areas served by the commuter train as compared to other similar areas. Essay 3: In this essay I look into the relation between housing mix and social mix in metropolitan Stockholm (Sweden) over the period 1990-2008. Using entropy measures, I find that although the distribution of tenure types over metropolitan Stockholm became somewhat more even over the studied period, people living in different tenure types still to a large extent tended to live in different parts of the city in 2008. The degree of residential segregation was much lower between different population groups. I further find that the mix of family types, and over time also of birth region groups and income groups, was rather different between different tenure types in the same municipality. The mix of different groups however tended to be similar within different tenure types in the same neighborhood. While the entropy measures provide a purely descriptive picture, the findings thus suggest that tenure type mix could be more useful for creating social mix at the municipal level than for creating social mix at the neighborhood level. Essay 4 (with Matz Dahlberg): The last decade’s immigration to western European countries has resulted in a culturally and religiously more diverse population in these countries. This diversification manifests itself in several ways, where one is through new features in the cityscape. Using a quasi-experimental approach, essay 4 examines how one such new feature, public calls to prayer, affects neighborhood dynamics (house prices and migration). The quasi-experiment is based on an unexpected political process that lead way to the first public call to prayer from a mosque in Sweden combined with rich (daily) information on housing sales. While our results indicate that the public calls to prayer increased house prices closer to the mosque, we find no evidence that the public calls to prayer served as a driver of residential segregation between natives and people born abroad around the mosque in question (no significant effects on migration behavior). Our findings are consistent with a story where some people have a willingness to pay for the possibility to more fully exert their religion which puts an upward pressure on housing in the vicinity of a mosque with public calls to prayer.

In the past decade, a night shift labor force has gained momentum in the global economy. The hyper-growth of the transnational call center industry in India provides a quintessential example. The night shift requirement of the transnational call industry also intersects with the spatial and temporal construction of gender. Research conducted in 2006 in Mumbai, Bangalore, and Ahmedabad indicates that the nightscape is primarily a male domain (with the exception of prostitutes, bar dancers, and call girls) and women’s entry into this domain generates a range of diverse responses from call centers, their employees, the employees’ families, the media, and the Indian public. This research illustrates that there is no linear outcome to how working the night shift at a call center affects women’s lives. Even though the global nature of the work combined with the relatively high salary is viewed as a liberating force in the lives of workers, in actuality women simultaneously experience opening and constriction for working in the industry. Through the collection of interviews, focus group data, and participant observation gathered during 10 months of fieldwork in India, I examine female night shift workers’ physical, temporal, social, and economic mobility to illustrate how global night shift labor is intersecting with the lives of women in ironic and unsettling ways. Call center employment certainly changes the temporal mobility of some women because it provides them with a legitimate reason to leave the house at night, whereas before this was considered unacceptable. Concerns about promiscuity and “bad character” related to working at night are deflected by linking employment to skill acquisition, high wages, and a contribution to the household. Women’s safety--a code word for their reputation--is preserved by segregating them, via private transport, from the other women of the night. Women consequently become more physically and economically mobile, but through the use of what I term mobility-morality narratives, households continue to maintain regimes of surveillance and control over when and how women come and go. Similarly their social mobility is limited by obligations to support family members and conform to gendered notions of a woman’s place. / text