Analysis and Testing of Ajax-based Single-page Web Applications

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programmers to organize topics according to containment relationships. It also allows topic names to contain wildcards, which offers the possibility to subscribe and publish to several topics whose names match a given set of keywords. Bayeux defines the following phases in order to establish a Comet connection: 1. The client performs a handshake with the server, receives a client ID and list of supported connection types, such as IFrame or long-polling (See Section 4.2.3). 2. The client sends a connection request with its ID and its preferred connection type. 3. The client later subscribes to a channel and receives updates Although the Bayeux specification supports both streaming and long polling modes, the Cometd framework currently only implements the long polling approach. Please note that, although there are other frameworks that support the Bayeux protocol, in this chapter we will use the terms Bayeux and Cometd interchangeably. 4.3.2 Direct Web Remoting (DWR) Direct Web Remoting (DWR) 4 is a Java open source library which allows scripting code in a browser to use Java functions running on a web server just as if they were in the browser. DWR works by dynamically generating JavaScript based on Java classes. To the user it feels like the execution is taking place on the browser, but in reality the server is executing the code and DWR is marshalling the data back and forwards. DWR works similar to the RPC mechanism (e.g., Java RMI), but without requiring any plugins. It consists of two main parts: • A Java Servlet running on the server that processes requests and sends responses back to the browser. • A JavaScript engine running in the browser that sends requests and can dynamically update the DOM with received responses from the server. From version 2.0 and above DWR supports Comet and calls this type of communication “Active Reverse Ajax” (Direct Web Remoting, 2007). Currently, DWR does not support Bayeux, and has adopted its own protocol to exchange data. DWR supports the long polling as well as the streaming mode. Because Cometd has no streaming implementation, we will only use the long polling mode of both libraries in our experiment, in order to be able to make a comparison. 4 http://getahead.org/dwr 82 4.3. Comet Implementations
4.4 Experimental Design In this section we first present our research questions. Later we describe our proposed approach, and the independent and dependent variables which we will use to conduct the experiment and come to answers to our questions. 4.4.1 Goal and Research Questions We set up our experiments in order to evaluate several dependent variables using the GQM/MEDEA 5 framework proposed by Briand et al. (Briand et al., 2002). First, we describe the goal, perspective and environment of our experiment: Goal. To obtain a rigorous understanding of the actual performance trade offs between a push-based and a pull-based approach to Ajax data delivery. Perspective:. In particular, we aim at an automated, repeatable experiment, in which as many (combinations) of the factors that influence performance (such as the number of users, the number of published messages, the intervals between messages, etc.) can be taken into account. Environment. The experiments are targeted at distributed environments, particularly those with UNIX/Linux nodes. Further relevant factors of these systems will be described in Section 4.5.2. We have formulated a number of questions that we would like to find answers for in each approach. Our research questions can be summarized as: RQ1 How fast are state changes (new messages) on the server propagated to the clients? RQ2 What is the scalability and overall performance of the server? RQ3 To what extent is the network traffic generated between the server and clients influenced? RQ4 How reliable is each approach? Are there messages that are missed or abundantly received on the clients? 4.4.2 Outline of the Proposed Approach In order to obtain an answer to our research questions, we propose the following steps: 1. creating two separate web applications, having the same functionality, using each push library (one for Cometd and one for DWR), consisting of the client and the server parts, 5 Goal Question Metric/MEtric DEfinition Approach Chapter 4. Performance Testing of Data Delivery Techniques for Ajax 83
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Analysis and Testing of Ajax-based
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Contents Preface List of Acronyms i
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3.3.4 Single-page UI Model Definiti
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6.3.2 Trigger . . . . . . . . . . .
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Preface our years have passed since
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List of Acronyms ASP Active Server
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Introduction A ccording to recent s
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Figure 1.2 Screen shot of the Mosai
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Figure 1.4 Screen shot of OpenLaszl
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DOM APIs, a technique that was call
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Figure 1.6 Screen shot of Google Su
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Figure 1.7 Screen shot of Google Do
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Reengineering Analysis & Testing Ar
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client/server and network-based env
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To the best of our knowledge, at th
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Table 1.1 ❳❳ ❳ ❳ ❳❳ Cha
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equally and we chose to use an alph
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A Component- and Push-based Archite
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Page Internet Application aRchitect
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XML message containing directives t
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server sends the data to the client
Page 43 and 44: • Code reuse: shared implementati
Page 45 and 46: Rest provides Ajax demands Large-gr
Page 47 and 48: work well, will lose customers (Off
Page 49 and 50: communication between client and se
Page 51 and 52: GWT uses an RPC style of calling se
Page 53 and 54: DOM Client Browser event update Aja
Page 55 and 56: Client Server Legend Interaction po
Page 57 and 58: User Interactivity User-perceived L
Page 59 and 60: User Interactivity User-perceived L
Page 61 and 62: and does not comply with the Resour
Page 63 and 64: 2.8.9 Design Models Figure 2.8 show
Page 65 and 66: of user tasks as first class entiti
Page 67 and 68: Migrating Multi-page Web Applicatio
Page 69 and 70: Web App 1 Page deltaChange viewChan
Page 71 and 72: gational and structural model of th
Page 73 and 74: Classic Web application Retrieve pa
Page 75 and 76: Algorithm 1 1: procedure start (Pag
Page 77 and 78: 3.5.2 Identifying Elements The list
Page 79 and 80: Classification # of pages Home (Ind
Page 81 and 82: Figure 3.7 A candidate UI component
Page 83 and 84: target system. Even though the tech
Page 85 and 86: Third, we proposed a schema-based c
Page 87 and 88: Performance Testing of Data Deliver
Page 89 and 90: Figure 4.1 A screenshot taken from
Page 91 and 92: the user. Ideally, the pulling inte
Page 93: Streaming Figure 4.3 shows how the
Page 97 and 98: Mean Publish Trip-time (MPT) We def
Page 99 and 100: tributes to the complexity of contr
Page 101 and 102: 8. Start the publisher and begin pu
Page 103 and 104: Figure 4.8 Sample Stock Ticker Appl
Page 105 and 106: Figure 4.9 Mean Publish Trip-time C
Page 107 and 108: 4.6.3 Received Publish Messages Fig
Page 109 and 110: Figure 4.12 Mean Number of Received
Page 111 and 112: Figure 4.13 Percentage of data item
Page 113 and 114: with pull is higher than push. This
Page 115 and 116: this scenario, a data item will onl
Page 117 and 118: With the pull approach, achieving t
Page 119 and 120: Crawling Ajax by Inferring User Int
Page 121 and 122: discusses the findings and open iss
Page 123 and 124: 5.3 A Method for Crawling Ajax The
Page 125 and 126: Robot click UI Browser generate cli
Page 127 and 128: 5.3.5 Creating States After firing
Page 129 and 130: 1 crawl MyAjaxSite { 2 url: http://
Page 131 and 132: The generator uses JTidy 10 to pret
Page 133 and 134: G1. For the experiment we have manu
Page 135 and 136: 19247 examined candidate elements,
Page 137 and 138: ich interactivity and responsivenes
Page 139 and 140: 5.8 Related Work The concept behind
Page 141 and 142: Invariant-Based Automatic Testing o
Page 143 and 144: has some support for client-side sc
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6.3.2 Trigger Once we are able to d
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a new edge is created on the graph
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Other Invariants. In line with the
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6.7.1 Oracle Comparators After each
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Algorithm 4 Pre/postCrawling hooks
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LOC Server-side LOC Client-side DOM
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todo items, removing all items inst
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Failure Cause Violated Invariant In
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plications) is that it is very hard
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1. A series of fault models that ca
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Conclusion ith the advent of Ajax t
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out to be an appropriate framework
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plays a more prominent role in the
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correct behavior. Violations in the
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A great deal of our work has focuse
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A Single-page Ajax Example Applicat
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1 if(navigator.appName == "Microsof
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Figure A.5 The run-time DOM instanc
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Figure A.7 The request/response tra
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Samenvatting ⋆ Analyse en Testing
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een dergelijk model te creëren, do
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Bibliography Abrams, M., Phanouriou
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Bouras, C. and Konidaris, A. (2005)
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De Lucia, A., Scanniello, G., and T
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Garofalakis, M., Gionis, A., Rastog
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Levenshtein, V. L. (1996). Binary c
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Netscape (1995). An exploration of
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Sprenkle, S., Pollock, L., Esquivel
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Wohlin, C., Runeson, P., Höst, M.,
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Curriculum Vitae Personal Data Full
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A. Dijkstra. Stepping through Haske
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M. A. Abam. New Data Structures and
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