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

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Method Threshold RCR ICR Precision (%) Recall (%) STS 0.89 6 3 66 54 STS 0.91 9 4 69 82 STS 0.93 7 8 46 63 MMS 0.97 7 1 87 63 MMS 0.98 11 0 100 100 MMS 0.99 9 2 82 82 Table 3.2 Results of Clustering JPetstore Web Interface. Page W: Category viewProduct W: Product addItem viewItem removeItem W: Cart addItem W: Item checkout viewItem W: Singon register W: Register signon W: Order Figure 3.8 Target JPetstore Single-page Interface. 3.8 Discussion As mentioned before, we came to the idea of a tool support for ajaxification process when we first conducted a manual migration. The required knowledge for ajaxification was obtained by manually browsing the interface, from one page to the other, noting the differences, and building a map of the interaction model. This was when we realized that reverse engineering techniques should be able to provide some degree of support. Having a tool which provides us with information about the UI components needed and their positions on the navigational paths, can be of great value. Applying the techniques described in this chapter to our case study, we were able to find all reference classifications. Additionally, with some degree of manual intervention, we were able to create a single-page model of the 70 3.8. Discussion
target system. Even though the techniques introduced in this chapter have only been applied to one case study, considering the results obtained, we believe the applications can span real-world web application migration cases. Although the JPetStore interface is very simple, it is representative of dynamic transactional web applications, and this class of web applications is exactly what we aim for. Our approach is not meant for web sites that are composed of long pages such as news, article, or forum sites. We will need to conduct more case studies to find strengths and weaknesses of our techniques and improve the tool. We take a client-side analysis approach. While having the benefit of being server-code independent, the information that can be inferred from the serverside, such as scripting languages as JSP, is also essential for conducting a real migration process. One of the problems we encountered while carrying out the case study, was that some HTML pages contained elements that were not well-formed or were not recognized by the formatter. Even JTidy was not able to fix the problems and no conversion to XHTML could be conducted. For instance in a few pages, instead of element a was used. Manual intervention was required to fix the problem. This sort of problems are inherent in web applications and can cause real problems in real-world migration cases, where standard guidelines are neglected and faulty HTML code is written/generated. For a more detailed discussion of the limitations of the proposed approach see 7.2. 3.9 Related Work Reverse engineering techniques have been applied to web application settings primarily to gain a comprehensible view of the systems. Hassan and Holt (2002) present an approach to recover the architectural model of a web application by extracting relations between the various components and visualizing those relations. Di Lucca et al. (2002c,d) propose WARE which is a tool for reverse engineering Web applications to the Conallen extension (Conallen, 2003) of UML models. Draheim et al. (2005), present Revengie to reconstruct form-oriented analysis models for web applications. Ricca and Tonella (2001) propose ReWeb, a tool to analyze source code to recover a navigational model of a web site. They use the models obtained by ReWeb for testing (Tonella and Ricca, 2004) web applications. Supporting the migration of static to dynamic web pages is illustrated in (Ricca and Tonella, 2003) by applying an agglomerative hierarchical clustering approach. De Lucia et al. (2005, 2004b) present a program comprehension approach to identify duplicated HTML and JSP pages based on a similarity threshold using Levenshtein string edit distance method. They use three notions of Chapter 3. Migrating Multi-page Web Applications to Ajax Interfaces 71
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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
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 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: Figure 3.7 A candidate UI component
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
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
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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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