ProCrawl: mining test models from multi-user web applications

Schur, Matthias; Röth, Andreas; Zeller, Andreas

doi:10.1145/2610384.2628051

Cited by 8 publications

(8 citation statements)

References 11 publications

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“…Korel provided an approach that generates test cases based on actual executions of AUT to search for the values of input variables, which influence undesirable execution flow, by using function minimization methods [50]. Schur et al provided an tool ProCrawl, which mined an extended finite-state machine as a behavior model and generated test scripts for regression testing [68,69]. Artzi et al used the Tarantula algorithm to localize source codes which lead to failures in web application by combining the concrete and symbolic execution information [9].…”

Section: Related Workmentioning

confidence: 99%

Automating performance bottleneck detection using search-based application profiling

Shen

Luo

Poshyvanyk

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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Application profiling is an important performance analysis technique, when an application under test is analyzed dynamically to determine its space and time complexities and the usage of its instructions. A big and important challenge is to profile nontrivial web applications with large numbers of combinations of their input parameter values. Identifying and understanding particular subsets of inputs leading to performance bottlenecks is mostly manual, intellectually intensive and laborious procedure.We propose a novel approach for automating performance bottleneck detection using search-based input-sensitive application profiling. Our key idea is to use a genetic algorithm as a search heuristic for obtaining combinations of input parameter values that maximizes a fitness function that represents the elapsed execution time of the application. We implemented our approach, coined as Genetic Algorithm-driven Profiler (GA-Prof) that combines a search-based heuristic with contrast data mining of execution traces to accurately determine performance bottlenecks. We evaluated GA-Prof to determine how effectively and efficiently it can detect injected performance bottlenecks into three popular open source web applications. Our results demonstrate that GA-Prof efficiently explores a large space of input value combinations while automatically and accurately detecting performance bottlenecks, thus suggesting that it is effective for automatic profiling.

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Section: Related Workmentioning

confidence: 99%

Automating performance bottleneck detection using search-based application profiling

Shen

Luo

Poshyvanyk

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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“…Making MBT more practical and easier to apply is one of the main open challenges, and the recent trend of automatically extracting models from the application under test is an interesting first step in this direction. So far, MBT from inferred models has focused on system testing with an effectiveness limited to detecting faults that cause easy-to-detect failures, such as program crashes [33,34,109]. Another major open challenge is extending MBT from inferred models to a broader set of testing levels and faults.…”

Section: Model-based Testingmentioning

confidence: 99%

“…This is also witnessed by the growing popularity of MBT in industry [110][111][112][113] and the increasing number of commercial tools available, such as Conformiq Designer [114], Smartesing CertifyIt [115,116] MBT from inferred models MBT from ripped models [32][33][34][35][36][37][38][39] Learningbased MBT [40][41][42][43][44] MBT from finite state models [45][46][47][48][49][50][51][52][53][54] MBT from UML models [55][56][57][58][59] MBT from feature models [60,61] MBT from specification models testing [118]. Recent studies also demonstrated a comparable effort when debugging test cases generated with MBT and manual testing [119].…”

Section: Model-based Testingmentioning

confidence: 99%

“…Mesbah et al defined an approach, called CRAWLAJAX, for building a state machine model of a Web application under test by exploring its GUI [120]. Interestingly, Schur et al have investigated the problem of generating models of Web applications when multiple users might be present [34]. Their approach is implemented in the ProCrawl tool, which has the capability to interact with an application using multiple types of users, obtaining a deeper exploration of the business logic.…”

Section: Run Testsmentioning

confidence: 99%

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Recent Advances in Automatic Black-Box Testing

Mariani

Pezzè

Zuddas

2015

Advances in Computers

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“…This article is a substantially revised and extended version of our original papers [33], [34]; we present a novel approach for learning transition guard conditions, as well as an extended evaluation including two additional case studies. Figure 1 shows a behavior model automatically extracted by PROCRAWL that represents the peer-review process in OPENCONF 1 , a popular web-based conference management system.…”

Section: Introductionmentioning

confidence: 99%

Mining Workflow Models from Web Applications

Schur

Röth

Zeller

2015

IIEEE Trans. Software Eng.

Self Cite

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Modern business applications predominantly rely on web technology, enabling software vendors to efficiently provide them as a service, removing some of the complexity of the traditional release and update process. While this facilitates shorter, more efficient and frequent release cycles, it requires continuous testing. Having insight into application behavior through explicit models can largely support development, testing and maintenance. Model-based testing allows efficient test creation based on a description of the states the application can be in and the transitions between these states. As specifying behavior models that are precise enough to be executable by a test automation tool is a hard task, an alternative is to extract them from running applications. However, mining such models is a challenge, in particular because one needs to know when two states are equivalent, as well as how to reach that state. We present ProCrawl (Process Crawler), a tool to mine behavior models from web applications that support multi-user workflows. ProCrawl incrementally learns a model by generating program runs and observing the application behavior through the user interface. In our evaluation on several real-world web applications, ProCrawl extracted models that concisely describe the implemented workflows and can be directly used for model-based testing.

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ProCrawl: mining test models from multi-user web applications

Cited by 8 publications

References 11 publications

Automating performance bottleneck detection using search-based application profiling

Automating performance bottleneck detection using search-based application profiling

Recent Advances in Automatic Black-Box Testing

Mining Workflow Models from Web Applications

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