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

More documents

Recommendations

Info

whether this is too small to be representative. However, our results are based on dynamic analysis rather than static code analysis, hence the amount of code is not the determining factor. Instead, the size of the derived state machine is the factor limiting the scalability of our approach, which is only moderately (if at all) related to the size of the JavaScript code. 6.10.7 Threats to Validity Some of the issues concerning the external validity of our empirical evaluation have been covered in the above discussion on scope, generated code, application size, and scalability. Apart from the two case studies described here, we conducted two more (on TaskFreak 17 and the Java PetStore 2.0 18 ), which gave comparable results. With respect to internal validity, we minimized the chance of Atusa errors by including a rigorous JUnit test suite. Atusa, however, also makes use of many (complex) third party components, and we did encounter several problems in some of them. While these bugs do limit the current applicability of our approach, they do not affect the validity of our results. As far as the choice of faults in the first case study is concerned, we selected them form the TUDU bug tracking system, based on our fault models which we believe are representative of the types of faults that occur during Ajax development. The choice is, therefore, not biased towards the tool but the fault models we have. With respect to reliability, our tools and the TUDU case are open source, making the case fully reproducible. 6.10.8 Ajax Testing Strategies Atusa is a first, but essential step in testing Ajax applications, offering a solution for the reach/trigger/propagate problem. Thanks to the plugin-based architecture of Atusa, it now becomes possible to extend, refine, and evaluate existing software testing strategies (such as evolutionary, state-based, category-partition, and selective regression testing) for the domain of Ajax applications. 6.11 Concluding Remarks In this chapter, we have proposed a method for testing Ajax applications automatically. Our starting point for supporting Ajax-testing is Crawljax, a crawler for Ajax applications that we proposed in our earlier work (Mesbah et al., 2008), which can dynamically make a full pass over an Ajax application. Our current work resolves the subsequent problems of extending the crawler with data entry point handling to reach faulty Ajax states, triggering faults in those states, and propagating them so that failure can be determined. To that end, this chapter makes the following contributions: 17 http://www.taskfreak.com 18 https://blueprints.dev.java.net/petstore/ 150 6.11. Concluding Remarks
1. A series of fault models that can be automatically checked on any user interface state, capturing different categories of errors that are likely to occur in Ajax applications (e.g., DOM violations, error message occurrences), through (DOM-based) generic and application-specific invariants which server as oracle. 2. An algorithm for deriving a test suite achieving all transitions coverage of the state-flow graph obtained during crawling. The resulting test suite can be refined manually to add test cases for specific paths or states, and can be used to conduct regression testing of Ajax applications. 3. An open source tool called Atusa implementing the approach, offering generic invariant checking components as well as a plugin-mechanism to add application-specific state validators and test suite generation. 4. An empirical validation, by means of two case studies, of the fault revealing capabilities and the scalability of the approach, as well as the level of automation that can be achieved and manual effort required to use the approach. Given the growing popularity of Ajax applications, we see many opportunities for using Atusa in practice. Furthermore, the open source and pluginbased nature of Atusa makes it a suitable vehicle for other researchers interested in experimenting with other new techniques for testing Ajax applications. Our future work will include conducting further case studies, as well as the development of Atusa plugins, capable of spotting security vulnerabilities in Ajax applications. Chapter 6. Invariant-Based Automatic Testing of Ajax User Interfaces 151
Page 1 and 2:
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 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 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
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
Page 145 and 146: 6.3.2 Trigger Once we are able to d
Page 147 and 148: a new edge is created on the graph
Page 149 and 150: Other Invariants. In line with the
Page 151 and 152: 6.7.1 Oracle Comparators After each
Page 153 and 154: Algorithm 4 Pre/postCrawling hooks
Page 155 and 156: LOC Server-side LOC Client-side DOM
Page 157 and 158: todo items, removing all items inst
Page 159 and 160: Failure Cause Violated Invariant In
Page 161: plications) is that it is very hard
Page 165 and 166: Conclusion ith the advent of Ajax t
Page 167 and 168: out to be an appropriate framework
Page 169 and 170: plays a more prominent role in the
Page 171 and 172: correct behavior. Violations in the
Page 173 and 174: A great deal of our work has focuse
Page 175 and 176: A Single-page Ajax Example Applicat
Page 177 and 178: 1 if(navigator.appName == "Microsof
Page 179 and 180: Figure A.5 The run-time DOM instanc
Page 181 and 182: Figure A.7 The request/response tra
Page 183 and 184: Samenvatting ⋆ Analyse en Testing
Page 185 and 186: een dergelijk model te creëren, do
Page 187 and 188: Bibliography Abrams, M., Phanouriou
Page 189 and 190: Bouras, C. and Konidaris, A. (2005)
Page 191 and 192: De Lucia, A., Scanniello, G., and T
Page 193 and 194: Garofalakis, M., Gionis, A., Rastog
Page 195 and 196: Levenshtein, V. L. (1996). Binary c
Page 197 and 198: Netscape (1995). An exploration of
Page 199 and 200: Sprenkle, S., Pollock, L., Esquivel
Page 201 and 202: Wohlin, C., Runeson, P., Höst, M.,
Page 203 and 204: Curriculum Vitae Personal Data Full
Page 205 and 206: A. Dijkstra. Stepping through Haske
Page 207 and 208: M. A. Abam. New Data Structures and
show all

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

Create successful ePaper yourself

Delete template?

Save as template?