Software defects caused by inadequate software testing can cost billions of dollars. Further, web application defects can be costly due to the fact that most web applications handle constant user interaction. However, software testing is often under time and budget constraints. By improving the time efficiency of software testing, many of the costs associated with defects can be saved. Current methods for web application testing can take too long to generate test suites. In addition, studies have shown that user-session-based test suites often find faults missed by other testing techniques. This project addresses this problem by utilizing existing user sessions for web application testing. The software testing method provided within this project utilizes previous knowledge about combinatorial coverage testing and improves time and computer memory efficiency by only considering test cases that exist in a user-session based test suite. The method takes the existing test suite and prioritizes the test cases based on a specific combinatorial criterion. In addition, this project presents an empirical study examining the application of the newly proposed combinatorial prioritization algorithm on an existing web application.

Due to the World Wide Web (WWW) has expanded speedily, the interaction between the user and the Web site is becoming persistently. Most proposed load control schemes developed based on the traditional Web site providing static files are not suitable for the Web site today. The new generation of WWW provides more varied and secure services. The greater part of applications are belonging to the session-based service. In order to provide better quality of services for the users, Web cluster architecture becomes the popular solution for most Web sites. This architecture combines serveral servers to work together and deals satisfied with the exponential increasing in service on WWW. In this paper, we proposed a session-based admission control and load balancing mechanism for Web cluster systems. The admission control scheme is used to prevent Web system from becoming overload by determining whether an establishment of TCP connection is admitted or not. The load balancing scheme assigns new sessions to the suitable back-end server and achieves good load balancing among back-end servers, which also increases the throughput of system. The simulation results demonstrate that our mechanism utilizes system resource efficiently and takes system utilization and percentage of completed session into account simultaneously. Therefore, our mechanism can ensure the sessions would not be aborted midway. To compare with others, our mechanism can attain higher throughput and maintain the request average delay time. Furthermore, whether the back-end servers are identical in capacity or not, their load always get good balance.

Context. Colossal systems that are evolving are primarily system of systems (SOS). The system of systems are characteristic of functionally independent subsystems. These subsystems exhibit heterogeneity in terms of software or hardware. Each subsystem may reflect heterogeneity in dimensions such as the system complexity, system configuration, programming language and platforms, etc. Exploratory testing (ET) is perceived to be the best for testing such systems. An enhancement to exploratory testing is the session-based test management (SBTM) where several activities form a part of each session. These activities are mainly dependent on tester and the test charter of that session. There is lack of information in existing literature regarding a standard framework to design test charters for exploratory testing which forms the main area of focus of this thesis research. Objectives. Firstly, to investigate the design of test charters in general. Secondly, to find out the factors influencing the design of test charters. Lastly, to develop a framework to design effective test charters in SOS context. Methods. A mixed method approach that incorporates both qualitative and quantitative research methods is used. This research includes the quantitative leg of the online survey along with the interviews and literature review that are qualitative in nature. Literature review has been chosen to investigate the test charter design in general. Besides, interviews and online surveys  have been used to research regarding the factors and test charter framework.  Snowball sampling method and convenience sampling method have been used to sample the research data. Moreover, thematic analysis method is used for analyzing the qualitative data while descriptive statistics is used for quantitative data analysis. Results. The design aspects of test charter are documented, the factors influencing test charter design and the framework for effective test charter design for exploratory testing are presented. Conclusions. The thesis objectives are fulfilled. The findings on how the test charters are generally designed have helped in gaining insight on the primary elements that constitute a test charter design. Further, investigating the factors influencing the test charter design has helped in knowing the main elements affecting the test charter design. Finally, the main contribution of this thesis, the developed flexible test charter framework for exploratory testing encapsulates variables that should be considered, controlled or varied systematically during the course of testing. It is deemed to act as a guideline for practitioners for effective test charter design.

Context: Exploratory Testing (ET) and Scripted Testing (ST) are two of the more commonly practiced manual testing approaches in industry. ST is a traditional testing approach in which testing is carried out by executing pre-designed test cases. While in ET, learning, test designing and test execution are carried out simultaneously. In many instances, ET and ST complement each other very well in projects; however, proponents of ET claim that ET is more cost-beneficial in comparison to ST. Moreover, a few studies have indicated that ET is more effective in defect detection. Nevertheless, to the best of our knowledge, no study has been conducted to compare the costs and benefits of these two approaches. Objectives: The aim of this study was to conduct a qualitative Cost-Benefit Analysis (CBA) of ET in comparison with ST. By comparing and analyzing these two testing approaches, this study attempts to aid in decision-making with respect to how resources should be allocated for ET and ST for certain projects. Methods: The factors of costs and benefits of ET and ST were identified by conducting six semi-structured interviews in industry. Based on the analysis of these factors, a CBA model is proposed. The academic and industrial evaluation of the proposed CBA model was performed by conducting five interviews with researchers and practitioners. In addition, a qualitative CBA of a process of ET, Session-Based Testing Management (SBTM), and a process of ST, Test-Case Based Testing (TCBT) is conducted by collecting data through questionnaires and interviews with industry practitioners. A total of 22 questionnaire responses and seven interviews were analyzed. Results: By analyzing the identified cost and benefit factors, a CBA model was developed based on the testing phases stated in the ISO/IEC 29119 standard. A qualitative CBA of the SBTM process in comparison with the TCBT process was conducted by applying the CBA model in a questionnaire. The following findings were gathered from the CBA: • The differences of the SBTM and TCBT processes are identified by an analysis of the activities performed in various organizations, which the respondents belonged to. • The results of the analysis and comparison, of the costs (in terms of effort) and benefits (quality of the testing activities) of these two testing processes, are presented with respect to each testing phase. • The factors that impact the costs and benefits of using SBTM and TCBT, are summarized and discussed in this report. • The scenarios, in which SBTM and TCBT can be more cost-beneficial, are identified based on practitioners’ opinions. Conclusions: According to the survey results, industry practitioners consider SBTM as more cost-beneficial in comparison with TCBT, particularly in the test design, implementation and test execution phases. However, industry practitioners also stressed that ET should not be considered as a replacement for ST. In some contexts, testing objectives are better achieved through a more scripted approach, while, in other contexts, testing objectives will benefit more from the ability to create and improve tests as they are being executed. Whether a testing approach is valuable or cost-beneficial also depends on the context of project and the required benefits.

In recent years, the most popular web search engines have excelled in their ability to answer short queries that require clear, localized and personalized answers. When it comes to complex exploratory search tasks however, the main challenge for the searcher remains the same as back in the 1990s: Trying to formulate a single query that contains all the right keywords to produce at least some relevant results. In this work we want to investigate new ways to facilitate exploratory search by making use of context information from the user's entire search process. Therefore we present the concept of session-based semantic search, with an optional extension to collaborative search scenarios. To improve the relevance of search results we expand queries with terms from the user's recent query history in the same search context (session-based search). We introduce a novel method for query classification based on statistical topic models which allows us to track the most important topics in a search session so that we can suggest relevant documents that could not be found through keyword matching. To demonstrate the potential of these concepts, we have built the prototype of a session-based semantic search engine which we release as free and open source software. In a qualitative user study that we have conducted, this prototype has shown promising results and was well-received by the participants. / Die führenden Web-Suchmaschinen haben sich in den letzten Jahren gegenseitig darin übertroffen, möglichst leicht verständliche, lokalisierte und personalisierte Antworten auf kurze Suchanfragen anzubieten. Bei komplexen explorativen Rechercheaufgaben hingegen ist die größte Herausforderung für den Nutzer immer noch die gleiche wie in den 1990er Jahren: Eine einzige Suchanfrage so zu formulieren, dass alle notwendigen Schlüsselwörter enthalten sind, um zumindest ein paar relevante Ergebnisse zu erhalten. In der vorliegenden Arbeit sollen neue Methoden entwickelt werden, um die explorative Suche zu erleichtern, indem Kontextinformationen aus dem gesamten Suchprozess des Nutzers einbezogen werden. Daher stellen wir das Konzept der sitzungsbasierten semantischen Suche vor, mit einer optionalen Erweiterung auf kollaborative Suchszenarien. Um die Relevanz von Suchergebnissen zu steigern, werden Suchanfragen mit Begriffen aus den letzten Anfragen des Nutzers angereichert, die im selben Suchkontext gestellt wurden (sitzungsbasierte Suche). Außerdem wird ein neuartiger Ansatz zur Klassifizierung von Suchanfragen eingeführt, der auf statistischen Themenmodellen basiert und es uns ermöglicht, die wichtigsten Themen in einer Suchsitzung zu erkennen, um damit weitere relevante Dokumente vorzuschlagen, die nicht durch Keyword-Matching gefunden werden konnten. Um das Potential dieser Konzepte zu demonstrieren, wurde im Rahmen dieser Arbeit der Prototyp einer sitzungsbasierten semantischen Suchmaschine entwickelt, den wir als freie Software veröffentlichen. In einer qualitativen Nutzerstudie hat dieser Prototyp vielversprechende Ergebnisse hervorgebracht und wurde von den Teilnehmern positiv aufgenommen.

Context: Exploratory testing (ET) is an approach to test software with a strong focus on personal skills and freedom of the tester. ET emphasises the simultaneous design and execution of tests with minimal test documentation. Test practitioners often claim that their choice to use ET as an important alternative to scripted testing is based on several benefits ET exhibits over the scripted testing. However, these claims lack empirical evidence as there is little research done in this area. Moreover, ET is usually considered an ad-hoc way of doing testing as everyone does it differently. There have been some attempts in past to provide structure to ET. Session based test management (SBTM) is an approach that attempts to provide some structure to ET and gives some basic guidelines to structuring the test sessions. However, these guidelines are still very abstract and are very open to individuals' interpretation. Objective: The main objective of this doctoral thesis is to support practitioners in their decisions about choosing exploratory versus scripted testing. Furthermore, it is also aimed to investigate the empirical evidence in support of ET and find ways to structure ET and classify different levels of exploration that drive the choices made by exploratory testers. Another objective of this thesis is to provide a decision support system to select levels of exploration in overall test process. Method: The findings presented in this thesis are obtained through a controlled experiment with participants from industry and academia, exploratory surveys, interviews and focus groups conducted at different companies including Ericsson AB, Sony Mobile Communications, Axis Communications AB and Softhouse Consulting Baltic AB. Results: Using the exploratory survey, we found three test techniques to be most relevant in context of testing software systems and in particular heterogeneous systems. The most frequently used technique mentioned by the practitioners is ET which is not a much researched topic. We also found many interesting claims about ET in grey literature produced by practitioners in the form of informal presentations and blogs but these claims lacked any empirical evidence. Therefore, a controlled experiment was conducted with students and industry practitioners to compare ET with scripted testing. The experiment results show that ET detects significantly more critical defects compared to scripted testing and is more time efficient. However, ET has its own limitations and there is not a single way to use it for testing. In order to provide structure to ET, we conducted a study where we propose checklists to support test charter design in ET. Furthermore, two more industrial focus group studies at four companies were conducted that resulted in a taxonomy of exploration levels in ET and a decision support method for selecting exploration levels in ET. Lastly, we investigated different problems that researchers face when conducting surveys in software engineering and have presented mitigation strategies for these problems. Conclusion: The taxonomy for levels of exploration in ET, proposed in this thesis, provided test practitioners at the companies a better understanding of the underlying concepts of ET and a way to structure their test charters. A number of influence factors elicited as part of this thesis also help them prioritise which level of exploration suits more to their testing in the context of their products. Furthermore, the decision support method provided the practitioners to reconsider their current test focus to test their products in a more effective way.

In recent years, the most popular web search engines have excelled in their ability to answer short queries that require clear, localized and personalized answers. When it comes to complex exploratory search tasks however, the main challenge for the searcher remains the same as back in the 1990s: Trying to formulate a single query that contains all the right keywords to produce at least some relevant results. In this work we want to investigate new ways to facilitate exploratory search by making use of context information from the user's entire search process. Therefore we present the concept of session-based semantic search, with an optional extension to collaborative search scenarios. To improve the relevance of search results we expand queries with terms from the user's recent query history in the same search context (session-based search). We introduce a novel method for query classification based on statistical topic models which allows us to track the most important topics in a search session so that we can suggest relevant documents that could not be found through keyword matching. To demonstrate the potential of these concepts, we have built the prototype of a session-based semantic search engine which we release as free and open source software. In a qualitative user study that we have conducted, this prototype has shown promising results and was well-received by the participants.:1. Introduction 2. Related Work 2.1. Topic Models 2.1.1. Common Traits 2.1.2. Topic Modeling Techniques 2.1.3. Topic Labeling 2.1.4. Topic Graph Visualization 2.2. Session-based Search 2.3. Query Classification 2.4. Collaborative Search 2.4.1. Aspects of Collaborative Search Systems 2.4.2. Collaborative Information Retrieval Systems 3. Core Concepts 3.1. Session-based Search 3.1.1. Session Data 3.1.2. Query Aggregation 3.2. Topic Centroid 3.2.1. Topic Identification 3.2.2. Topic Shift 3.2.3. Relevance Feedback 3.2.4. Topic Graph Visualization 3.3. Search Strategy 3.3.1. Prerequisites 3.3.2. Search Algorithms 3.3.3. Query Pipeline 3.4. Collaborative Search 3.4.1. Shared Topic Centroid 3.4.2. Group Management 3.4.3. Collaboration 3.5. Discussion 4. Prototype 4.1. Document Collection 4.1.1. Selection Criteria 4.1.2. Data Preparation 4.1.3. Search Index 4.2. Search Engine 4.2.1. Search Algorithms 4.2.2. Query Pipeline 4.2.3. Session Persistence 4.3. User Interface 4.4. Performance Review 4.5. Discussion 5. User Study 5.1. Methods 5.1.1. Procedure 5.1.2. Implementation 5.1.3. Tasks 5.1.4. Questionnaires 5.2. Results 5.2.1. Participants 5.2.2. Task Review 5.2.3. Literature Research Results 5.3. Discussion 6. Conclusion Bibliography Weblinks A. Appendix A.1. Prototype: Source Code A.2. Survey A.2.1. Tasks A.2.2. Document Filter for Google Scholar A.2.3. Questionnaires A.2.4. Participant’s Answers A.2.5. Participant’s Search Results / Die führenden Web-Suchmaschinen haben sich in den letzten Jahren gegenseitig darin übertroffen, möglichst leicht verständliche, lokalisierte und personalisierte Antworten auf kurze Suchanfragen anzubieten. Bei komplexen explorativen Rechercheaufgaben hingegen ist die größte Herausforderung für den Nutzer immer noch die gleiche wie in den 1990er Jahren: Eine einzige Suchanfrage so zu formulieren, dass alle notwendigen Schlüsselwörter enthalten sind, um zumindest ein paar relevante Ergebnisse zu erhalten. In der vorliegenden Arbeit sollen neue Methoden entwickelt werden, um die explorative Suche zu erleichtern, indem Kontextinformationen aus dem gesamten Suchprozess des Nutzers einbezogen werden. Daher stellen wir das Konzept der sitzungsbasierten semantischen Suche vor, mit einer optionalen Erweiterung auf kollaborative Suchszenarien. Um die Relevanz von Suchergebnissen zu steigern, werden Suchanfragen mit Begriffen aus den letzten Anfragen des Nutzers angereichert, die im selben Suchkontext gestellt wurden (sitzungsbasierte Suche). Außerdem wird ein neuartiger Ansatz zur Klassifizierung von Suchanfragen eingeführt, der auf statistischen Themenmodellen basiert und es uns ermöglicht, die wichtigsten Themen in einer Suchsitzung zu erkennen, um damit weitere relevante Dokumente vorzuschlagen, die nicht durch Keyword-Matching gefunden werden konnten. Um das Potential dieser Konzepte zu demonstrieren, wurde im Rahmen dieser Arbeit der Prototyp einer sitzungsbasierten semantischen Suchmaschine entwickelt, den wir als freie Software veröffentlichen. In einer qualitativen Nutzerstudie hat dieser Prototyp vielversprechende Ergebnisse hervorgebracht und wurde von den Teilnehmern positiv aufgenommen.:1. Introduction 2. Related Work 2.1. Topic Models 2.1.1. Common Traits 2.1.2. Topic Modeling Techniques 2.1.3. Topic Labeling 2.1.4. Topic Graph Visualization 2.2. Session-based Search 2.3. Query Classification 2.4. Collaborative Search 2.4.1. Aspects of Collaborative Search Systems 2.4.2. Collaborative Information Retrieval Systems 3. Core Concepts 3.1. Session-based Search 3.1.1. Session Data 3.1.2. Query Aggregation 3.2. Topic Centroid 3.2.1. Topic Identification 3.2.2. Topic Shift 3.2.3. Relevance Feedback 3.2.4. Topic Graph Visualization 3.3. Search Strategy 3.3.1. Prerequisites 3.3.2. Search Algorithms 3.3.3. Query Pipeline 3.4. Collaborative Search 3.4.1. Shared Topic Centroid 3.4.2. Group Management 3.4.3. Collaboration 3.5. Discussion 4. Prototype 4.1. Document Collection 4.1.1. Selection Criteria 4.1.2. Data Preparation 4.1.3. Search Index 4.2. Search Engine 4.2.1. Search Algorithms 4.2.2. Query Pipeline 4.2.3. Session Persistence 4.3. User Interface 4.4. Performance Review 4.5. Discussion 5. User Study 5.1. Methods 5.1.1. Procedure 5.1.2. Implementation 5.1.3. Tasks 5.1.4. Questionnaires 5.2. Results 5.2.1. Participants 5.2.2. Task Review 5.2.3. Literature Research Results 5.3. Discussion 6. Conclusion Bibliography Weblinks A. Appendix A.1. Prototype: Source Code A.2. Survey A.2.1. Tasks A.2.2. Document Filter for Google Scholar A.2.3. Questionnaires A.2.4. Participant’s Answers A.2.5. Participant’s Search Results

The industry of electronic commerce (e-commerce) constitutes a great part of the yearly retail consumption in Sweden. Looking at recent years, it has been seen that a rapidly growing sector within the mentioned field is the clothing industry for clothes and accessories for children and newborns. To get an overview of the items and help customers to find what they are looking for, many web stores have a system called a Recommendation System. The mechanics behind this service can look rather different depending on the method used. However, their unified goal is to provide a list of recommended items of interest to the customer.  A branch within this field is the Session Based Recommendation System (SBRS). These are models which are designed to work with the trace of products, called a session, that a user currently has visited on the web store. Based on that information they then formulate an output of recommended items. The SBRS models have been especially popularized since the majority of customers browse in an anonymous behavior, which means that they due to time efficiency often neglect the possibility of creating or logging into any personal web store account. This however limits the accessible information that a system can make use of to shape its item list.  It can be seen that the number of articles exploring SBRS within the fashion branch of clothing and accessories for children is very limited. This thesis is made to fill that gap. After a thorough literature study, three models were found to be of certain interest, the Short-Term Attention/Memory Priority (STAMP) model, Long Short-Term Memory (LSTM) model, and Gated Recurrent Unit (GRU) model. Further, the LSTM model is included as it is the collaborative company, BabyShop Group AB's current used method.  The results of this thesis show that the GRU model is a promising method, managing to predict the next item for a customer more consistently than any other of the evaluated models. Furthermore, it can also be seen that what embeddings the models use to represent the products plays a significant role in the learning and evaluation of the used data set.  Moreover, a benchmark model included in this thesis also shows the importance of filtering the data set of sessions. It can be seen that a majority of customers visit already-seen products, logged happenings most likely due to refreshing web pages or similar actions. This causes the session data set to be characterized by repeated items. For future work, it would therefore indeed be interesting to see how this data set can be filtered in a different way. To see how that affects the outcome of the used metrics in this thesis. / Industrin för elektronisk handel (e-handel) utgör en stor del av den årliga konsumtionen av återförsäljning i Sverige. Bara genom att följa de senaste åren har det kunnat ses att en snabbt växande sektor inom det nämnda området är den som berör kläder och accessoarer för barn.  För att kunna ge en överblick och hjälpa kunder att finna vad de söker använder många webbutiker ett system som kallas rekommendationssystem. Hur dessa system faktiskt fungerar kan se väldigt olika ut. Men deras gemensamma mål är att i slutändan kunna ge en lista av rekommenderade produkter till kunden. En gren inom detta område är sessionsbaserade rekommendationssystem. Detta är modeller som är designade för att arbeta med själva spåret av besökta produkter, de som en kund har varit inne på under sin nuvarande vistelse på webbutiken. Baserat på denna information formuleras sedan en lista av rekommenderade produkter till besökaren. Dessa typer av modeller har blivit särskilt populära då många kunder gillar att shoppa anonymt. Vilket i denna kontext betyder att de gärna slipper att behöva logga in på något personligt konto på webbutiken, där särskild information kan sparas. Men detta betyder också att mängden tillgängliga data minskas för rekommendationssystemet.  Antalet forskningsartiklar som utforskar sessionsbaserade rekommendationssystem för e-handel inom barnmode är väldigt begränsad. Denna avhandling är därför gjord med syftet att försöka fylla detta tomrum. En genomgående litteraturstudie visade att tre modeller var av särskilt intresse, nämligen Short-Term Attention/Memory Priority (STAMP), Gated Recurrent Unit (GRU) och Long Short Term Memory (LSTM) modellen. Den sistnämnda är inkluderad då detta är den nuvarande modellen som används av företaget som denna avhandling har gjorts i samarbete med, BabyShop Group AB.  Resultaten i denna avhandling kan påvisa att GRU är en mycket lovande modell som lyckades förutbestämma nästkommande produkt i en sessionskedja bäst. Utöver detta kan det också ses att embedding-vektorerna som används för att representera produkterna för modellerna spelar en avgörande roll. Speciellt för deras lärande och evaluering av data.  Förutom det påvisade en av riktvärdesmodellerna som användes i denna avhandling den viktiga innebörden av att filtrera sessionsdata. Det kan nämligen urskiljas i den data som erhölls från företaget att många kunder återbesöker en stor del av redan besökta produkter. Detta åstadkommas troligen av att kunderna uppdaterar sidan de är på, eller utför någon annan liknande handling. Det här gör att en stor del av den sessionsdata som används i denna avhandling innehåller många upprepade produkter i de givna sessionskedjorna. Som framtida arbete vore det därför intressant att utforska olika filtreringsmetoder som kan appliceras på den givna datamängden. Detta för att se hur en mera filtrerad datamängd påverkar slutresultatet av de använda mätmetoderna i denna avhandling.

This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. Furthermore, a RNN-LSTM model is, on a general behaviour level, trained to predict the customers next event and investigate its potential to detect anomalous behavior. The results indicate that simplicial complexes and their corresponding stable rank can be utilized to describe differences between genuine and fraudulent sessions on individual level. The use of a neural network suggests that there are deviant behaviors on general level concerning the difference between fraudulent and genuine sessions. The fact that this project was done without internal bank knowledge of fraudulent behaviour or historical knowledge of general suspicious activity and solely by data handling and anomaly detection shows great potential in session-based detection. Thus, this study concludes that the use of Topological Data Analysis and Neural Networks for detecting fraud and anomalous events provide valuable insight and opens the door for future research in the field. Further analysis must be done to see how effectively one could detect fraud mid-session. / I följande uppsats undersöks möjligheten att använda sessionbaserad kunddata från Svenska Handelsbanken AB för att detektera bedrägliga sessioner. Verktyg inom Topologisk Dataanalys används för att analysera kunders beteende och undersöka topologiska egenskaper såsom homologi och stabil rang på individnivå. Dessutom tränas en RNN-LSTM modell på en generell beteende nivå för att förutsäga kundens nästa händelse och undersöka dess potential att upptäcka avvikande beteende. Resultaten visar att simpliciella komplex och deras motsvarande stabil rang kan användas för att beskriva skillnader mellan genuina och bedrägliga sessioner på individnivå. Användningen av ett neuralt nätverk antyder att det finns avvikande beteenden på en generell nivå avseende skillnaden mellan bedrägliga och genuina sessioner. Det faktum att detta projekt genomfördes utan intern bankkännedom om bedrägerier eller historisk kunskap om allmäna misstänksamma aktiviteter och enbart genom datahantering och anomalidetektion visar stor potential för sessionbaserad detektion. Därmed drar denna studie slutsatsen att användningen av topologisk dataanalys och neurala nätverk för att upptäcka bedrägerier och avvikande händelser ger värdefulla insikter och öppnar dörren för framtida fortsätta studier inom området. Vidare analyser måste göras för att se hur effektivt man kan upptäcka bedrägerier mitt i sessioner.