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

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Client Server Legend Single-page UI Ajax Engine Figure 2.7 Client-centric AJAX Interaction. UI component programming improves simplicity because developers can use reusable components to assemble a Web page either declaratively or programmatically. User interactivity is improved because the user can interact with the application on a component level, similar to desktop applications. In addition, testing component-based software is inherently easier than testing traditional page-based web applications, which induces the property of reliability. Frameworks adhering to this constraint are very adaptable in terms of code mobility since state changes in the three code types (2.5.2) can be propagated to the client. 2.7.5 Web standards-based Constraining the Web elements to a set of standardized formats is one way of inducing portability on the Web. This constraint excludes approaches that need extra functionality (e.g., plug-ins, virtual machine) to run on the Web browser, such as Flash and Java applets, and makes the client cross-browser compatible. This constraint limits the nature of the data elements to those that are supported by web browsers. Also using web standards, web browsers that abide by standards are easily supported and hence some degree of reliability is induced (Avizienis et al., 2004). 2.7.6 Client-side Processing Client-side processing improves user interactivity and user-perceived latency through round-trip reduction. For instance, client-side form validation reduces unnecessary server-side error reports and reentry messages. Additionally, some server-side processing (e.g., sorting items) can be off-loaded to clients using mobile code that will improve server performance and increase the availability to more simultaneous connections. As a tradeoff, client performance can become an issue if many widgets need processing resources 44 2.7. Architectural Constraints
User Interactivity User-perceived Latency Network Performance Single-page Interface + Asynchronous Interaction + + Delta Communication + + + – – + Client-side processing + + + UI Component-based + + + + Web standards-based + + + Stateful + + + – – Push-based Publish/Subscribe + + – – + + Simplicity Scalability Portability Visibility Data Coherence Reliability Adaptability Table 2.2 Constraints and induced properties on the client. GWT takes advantage of client-side processing to the fullest, by generating all the UI client-side code as JavaScript and run it on the client. 2.7.7 Stateful A stateless server is one which treats each request as an independent transaction, unrelated to any previous request, i.e., each request must contain all of the information necessary to understand it, and cannot take advantage of any stored context on the server (Fielding and Taylor, 2002). Even though the Web architecture and HTTP are designed to be stateless, it is difficult to think of stateless Web applications. Within a Web application, the order of interactions is relevant, making interactions depend on each other, which requires an awareness of the overall component topology. The statefulness is imitated by a combination of HTTP, client-side cookies, and server-side session management. Unlike Rest, Spiar does not constrain the nature of the state explicitly. Nevertheless, since a stateless approach may decrease network performance (by increasing the repetitive data), and because of the component-based nature of the user interactions, a stateful solution might become favorable at the cost of scalability and visibility. 2.7.8 Push-based Publish/Subscribe The client-server interaction can be realized in both a push- or pull-based style. In a push-based style (Hauswirth and Jazayeri, 1999), the server broadcasts the state changes to the clients asynchronously every time its state changes. Event-based Integration (Barrett et al., 1996) and Asynchronous Rest (Khare and Taylor, 2004) are event-based styles allowing asynchronous notifi- Chapter 2. A Component- and Push-based Architectural Style for Ajax 45
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Analysis and Testing of Ajax-based
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Contents Preface List of Acronyms i
Page 5 and 6: 3.3.4 Single-page UI Model Definiti
Page 7 and 8: 6.3.2 Trigger . . . . . . . . . . .
Page 9 and 10: Preface our years have passed since
Page 11 and 12: List of Acronyms ASP Active Server
Page 13 and 14: Introduction A ccording to recent s
Page 15 and 16: Figure 1.2 Screen shot of the Mosai
Page 17 and 18: Figure 1.4 Screen shot of OpenLaszl
Page 19 and 20: DOM APIs, a technique that was call
Page 21 and 22: Figure 1.6 Screen shot of Google Su
Page 23 and 24: Figure 1.7 Screen shot of Google Do
Page 25 and 26: Reengineering Analysis & Testing Ar
Page 27 and 28: client/server and network-based env
Page 29 and 30: To the best of our knowledge, at th
Page 31 and 32: Table 1.1 ❳❳ ❳ ❳ ❳❳ Cha
Page 33 and 34: equally and we chose to use an alph
Page 35 and 36: A Component- and Push-based Archite
Page 37 and 38: Page Internet Application aRchitect
Page 39 and 40: XML message containing directives t
Page 41 and 42: 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: Client Server Legend Interaction po
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 and 94: Streaming Figure 4.3 shows how the
Page 95 and 96: 4.4 Experimental Design In this sec
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
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4.6.3 Received Publish Messages Fig
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Figure 4.12 Mean Number of Received
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Figure 4.13 Percentage of data item
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with pull is higher than push. This
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this scenario, a data item will onl
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With the pull approach, achieving t
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Crawling Ajax by Inferring User Int
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discusses the findings and open iss
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5.3 A Method for Crawling Ajax The
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Robot click UI Browser generate cli
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5.3.5 Creating States After firing
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1 crawl MyAjaxSite { 2 url: http://
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The generator uses JTidy 10 to pret
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G1. For the experiment we have manu
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19247 examined candidate elements,
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ich interactivity and responsivenes
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5.8 Related Work The concept behind
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Invariant-Based Automatic Testing o
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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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