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

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DOM Client Browser Ajax Engine Engine HTTP Decoder Encoder Server App. UI Comp. update update update S update UI Push Client S Push Server Service Provider Legend Source Update Subscribe Channel Figure 2.5 Proposed push-based integration. 2.7 Architectural Constraints Architectural constraints can be used as restrictions on the roles of the architectural elements to induce the architectural properties desired of a system. Table 2.2 presents an overview of the constraints and induced properties. A “+” marks a direct positive effect, whereas a “–” indicates a direct negative effect. Spiar rests upon the following constraints chosen to retain the properties identified previously in this chapter. 2.7.1 Single Page Interface Spiar is based on the client-server style which is presumably the best known architecture for distributed applications, taking advantage of the separation of concerns principle in a network environment. The main constraint that distinguishes this style from the traditional Web architecture is its emphasis on a single page interface instead of the page-sequence model. This constraint induces the property of user interactivity. User interactivity is improved because the interaction is on a component level and the user does not have to wait for the entire page to be rendered again as a result of each action. Figure 2.6 and Figure 2.7 show the interaction style in a traditional web and in a single-page client-centric Ajax application respectively. 2.7.2 Asynchronous Interaction Ajax applications are designed to have a high user interactivity and a low user-perceived latency. Asynchronous interaction allows the user to, subsequently, initiate a request to the server at any time, and receive the control back from the client instantly. The requests are handled by the client at the background and the interface is updated according to server responses. This 42 2.7. Architectural Constraints
Client Server Legend Interaction possible Figure 2.6 Traditional multi-page Web Interaction. model of interaction is substantially different from the classic synchronous request, wait for response, and continue model. 2.7.3 Delta-communication Redundant data transfer which is mainly attributed to retransmissions of unchanged pages is one of the limitations of classic web applications. Many techniques such as caching, proxy servers and fragment-based resource change estimation and reduction (Bouras and Konidaris, 2005), have been adopted in order to reduce data redundancy. Delta-encoding (Mogul et al., 1997) uses caching techniques to reduce network traffic. However, it does not reduce the computational load since the server still needs to generate the entire page for each request (Naaman et al., 2004). Spiar goes one step further, and uses a delta-communication style of interaction. Here merely the state changes are interchanged between the client and the server as opposed to the full-page retrieval approach in classic web applications. Delta-communication is based on delta-encoding architectural principles but is different: delta-communication does not rely on caching and as a result, the client only needs to process the deltas. All Ajax frameworks hide the delta-communication details from the developers. This constraint induces the properties of network performance directly and as a consequence user-perceived latency and user interactivity. Network performance is improved because there are less redundant data (merely the delta) being transported. Data coherence is also improved because of the fine-grain nature of the data which can be transferred to the user faster than when dealing with data contained in large-grain web pages. 2.7.4 User Interface Component-based Spiar relies on a single page user interface with components similar to that of desktop applications, e.g., AWT’s UI component model. This model defines the state and behavior of UI components and the way they can interact. Chapter 2. A Component- and Push-based Architectural Style for Ajax 43
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Analysis and Testing of Ajax-based
Page 3 and 4: 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: DOM Client Browser event update Aja
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 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
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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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