Guided test generation for web applications

Thummalapenta, Suresh; Lakshmi, K. Vasanta; Sinha, Saurabh; Sinha, Nishant; Chandra, Satish

doi:10.1109/icse.2013.6606562

Cited by 34 publications

(34 citation statements)

References 25 publications

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“…systems are non-deterministic, the main focus of FSMbased testing work has been on deterministic FSMs and these have been found to be sufficient in important application domains such as hardware [24], protocol conformance testing [5], [25], [26], [27], [28], [29], objectoriented systems [30], web services [31], [32], [33], [34], and general software [35].…”

Section: Finite State Machines (Fsms)mentioning

confidence: 99%

Parallel Algorithms for Testing Finite State Machines:Generating UIO Sequences

Hierons

Türker

2016

IIEEE Trans. Software Eng.

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Abstract-This paper describes an efficient parallel algorithm that uses many-core GPUs for automatically deriving Unique Input Output sequences (UIOs) from Finite State Machines. The proposed algorithm uses the global scope of the GPU's global memory through coalesced memory access and minimises the transfer between CPU and GPU memory. The results of experiments indicate that the proposed method yields considerably better results compared to a single core UIO construction algorithm. Our algorithm is scalable and when multiple GPUs are added into the system the approach can handle FSMs whose size is larger than the memory available on a single GPU.

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Section: Finite State Machines (Fsms)mentioning

confidence: 99%

Parallel Algorithms for Testing Finite State Machines:Generating UIO Sequences

Hierons

Türker

2016

IIEEE Trans. Software Eng.

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“…The main restriction we make is that we consider deterministic FSMs. The main focus of FSM-based testing has been on deterministic FSMs and these have been used in areas such as hardware [47], protocol conformance testing [5], [8], [9], [11], object-oriented systems [12], web services [13], [48], [49], and general software [50].…”

Section: Finite State Machines (Fsms)mentioning

confidence: 99%

Parallel Algorithms for Generating Harmonised State Identifiers and Characterising Sets

Hierons

Türker

2016

IEEE Trans. Comput.

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Abstract-Many automated finite state machine (FSM) based test generation algorithms require that a characterising set (CS) or a set of harmonised state identifiers (HSIs) is first produced. The only previously published algorithms for partial FSMs were brute-force algorithms with exponential worst case time complexity. This paper presents polynomial time algorithms and also massively parallel implementations of both the polynomial time algorithms and the brute-force algorithms. In the experiments the parallel algorithms scaled better than the sequential algorithms and took much less time. Interestingly, while the parallel version of the polynomial time algorithm was fastest for most sizes of FSMs, the parallel version of the brute-force algorithm scaled better due to lower memory requirements.

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“…EventBreak [41] uses a performanceguided test generation algorithm to identify unresponsiveness web applications. These and other UI-level test generation approaches [38,35,19,7,18,55,15] may be combined with DLint to extend the set of analyzed executions.…”

Section: Related Workmentioning

confidence: 99%

DLint: dynamically checking bad coding practices in JavaScript

Gong

Pradel

Sridharan

et al. 2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

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JavaScript is becoming one of the most popular languages, yet it is known for its suboptimal design. To effectively use JavaScript despite its design flaws, developers try to follow informal code quality rules that help avoiding correctness, maintainability, performance, and security problems. Lightweight static analyses, implemented in "lint-like" tools, are widely used to find violations of these rules, but are of limited use because of the language's dynamic nature. This paper presents DLint, a dynamic analysis approach to check code quality rules in JavaScript. DLint consists of a generic framework and an extensible set of checkers that each address a particular rule. We formally describe and implement 28 checkers that address problems missed by state-of-the-art static approaches. Applying the approach in a comprehensive empirical study on over 200 popular web sites shows that static and dynamic checking complement each other. On average per web site, DLint detects 49 problems that are missed statically, including visible bugs on the web sites of IKEA, Hilton, eBay, and CNBC.

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Guided test generation for web applications

Cited by 34 publications

References 25 publications

Parallel Algorithms for Testing Finite State Machines:Generating UIO Sequences

Parallel Algorithms for Testing Finite State Machines:Generating UIO Sequences

Parallel Algorithms for Generating Harmonised State Identifiers and Characterising Sets

DLint: dynamically checking bad coding practices in JavaScript

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