Software Engineering Research Paper Summery A TEST GENERATION METHOD BASED ON STATE DIAGRAM

Note : This is only summery of above paper

by : NICHA KOSINDRDECHA, 2JIRAPUN DAENGDEJ

In generally software testing phase takes 40-70% of the fourth dimension and cost during the software development life cycle. Thither are many researchers who found many test case generation methods to lessen the price and time, there are still a number of important research publication. The motivation for this study is to chomp a great quantity of time and cost to automatically generate tests from the diagram, with a large size of test and less test code coverage. We presented an effective test sequence generation technique to minimize time, cost, size of the tests while maximizing test coverage. Our anticipated technique target to see and generate tests from the state chart diagram. The diagram mostly used to excuse the conduct of the system, also discuss and determine the best effective test generation methods that derive tests from the diagram. Concluding that existing techniques since 1990, this paper introduces a new “3S” classification of test case generation techniques, which are: specification base technique, sketch diagram base technique and source based technique. Also, this paper's purpose a new “2S” classification of existing test data generation as follows: specification based technique and source code based technique. Specification base approach used input and production with pre-condition that is generated from requirement specification. The source code based technique aims to design test data using control flow graph and source code as well. As a result this work found that TGFMMD method is the best to produce the smaller size of test cases, with minimum total time and hatch all 100% nodes in the state chart diagram

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Software Engineering Static Analysis Implementation in Automated test Generation its code flowchart

Static Analysis 

code step 1 : suppose we have code like this 

int twic (int v) {

return 2*v;

}

void testme (int x  int y) {

z= twic(y);

if (z==x) {

if(x>y+10) {

error}

}

}

Step 2 : Make a flow graph of the program 

Step 3: Write them into mathematically form

after step 2 you have to write your diagram into math form like

suppose  sign like your code

$(sigma type sign) : {x->xo  y->yo}       path condition Pc : true

if yes    $ : {x->xo  y->yo   z->2*yo}                   (pc : true)^(2*yo=xo)

if false  $ : {x->xo  y->yo   z->2*yo}                   (pc : true)^(2*yo!=xo)

Inner loop if True

$ : {x->xo  y->yo   z->2*yo}                   (pc : true)^(2*yo=xo)^xo>yo+10

Inner loop if False

$ : {x->xo  y->yo   z->2*yo}                   (pc : true)^(2*yo=xo)^xo<=yo+10

at the end valuse after solution 

xo=2

yo=1

and hence .

Contact Me for any help 

cheers !

              

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Software Engineering Research Paper Summery "Leveraging Existing Tests in Automated Test Generation for Web Applications"

 Leveraging Existing Tests in Automated Test Generation for Web Applications

Authors: Amin Milani Fard, Mehdi Mirzaaghaei, Ali Mesbah

Note : This data is only summery of above paper.comment for any suggestion 

We want to automate testing for web application because today software application is written as a WWW based application to be hunted down on internet browsers. The usefulness of these testing applications is varied from company to company. Thither are many advantage to test automation. One of related to reputability of the trials and execution speed of test. Mostly web application’s test based on a crawler to designate the active states of the application, this approach is automated and smooth, and simply there is lack of field knowledge required for its winner. Many developers currently write test cases in frameworks like Selenium, but there is also disadvantage for that this way needs much manual effort.Crawling base techniques automate the testing in a great direction, but they are defined in three fields. 1-Input values, good values are essential for proper reporting of test space of the diligence 2-paths to explore, market web apps have a big space volume, and it is difficult to handle every section of the application. Not knowing which routes are important to explore the results in obtaining a partial reporting of a specific part of the application 3- Assertion, any generated test case needs to affirm the application behavior.

 Notwithstanding the automatic generating assertion without human knowledge is experienced to be challenging, as a result many web applications used standard rule to avoid these troubles.In this paper author proposed that mine the human knowledge standing in yourself written test cases, and combine that incidental information with the power of automated crawling and cover the test suit for the unchecked part of web applications beneath test. Author present its technique and tool called Testilizer, Testilizer used a Selenium test case Tc and the Url of the application, that automatically supposes a model from Tc and feeds that model to a crawler to enlarge by discovering exposed paths and states, makes assertions for newly noticed states based on the pattern learn from Tc, and finally generates new test instances.

 Testilizer can generate test cases, however, failure may be happening due to requirements like efficiency, effectiveness and threats to validity. That work is interesting by the fact that human written test cases is appreciated source of domain information, which can be utilized to accommodate some of the challenges in automated web application test generation.The Dom state is fundamentally an abstracted version of the Dom tree of a web application that displayed in a web browser at runtime. This abstraction conducted through classification function, the performance of which is discussed in the report.Our tool utilizes the given test suite to generate effective test cases by exploring alternative paths of the application and regenerate assertions for new detected stats. For upcoming work, we plot to evaluate the success of other states space exploring approaches like a variation of test paths and analyze the relationship between the strength of the original test suite and generated test suite.

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Software Engineering Research Paper Summery of Combined Static and Dynamic Automated Test Generation for MS and PHD

Summery of Combined Static and Dynamic Automated Test Generation for MS and PHD

Area: Software System Quality Assurance

By Sai Zhang, David Saff, Yingyi Bu

The motivation for automated test in today’s fast moving world, there is a challenge for any society to constantly defend and improve the character and efficiency of software system evolution In many software projects, software testing is ignored, there are many factors behind this like cost and time and so on that may result in deficiency of product quality and customer dissatisfaction and in the end to increase the overall software quality cost. Poor test approach, misjudge the effort of test case generation, delay in testing and following test maintenance are the main reason behind for cost mostly.

Mostly A unit test consists of a flow of approaches calls that create and modify objects, then use them as a parameter to a method under test. It is challenging task to automatically generate sequences that are original correct. This paper purposes a combined static and dynamic, automated test generation to address these problems for code without proper specification. Our first tactic uses dynamic analysis to suppose a call sequence from a sample program execution, then we use static analysis to recognize method craving relations based on the subjects they may say and compose. At the end, we combine the both dynamic model and the statically identified dependence information lead a random test generator to create a legal behaviorally test.

There are many several past research tools that follow an approach similar to us, but they neglect the two or three stages of our approach. Randoop, Palul and RecGen are different testing tools that are used in past. Paul presents the dynamic random approaches. RecGen uses a static does not have dynamic form and applies a static analysis to implement random test generation. Randoop is a pure random test generation tool.Compared to old approaches, Palus increases the structural coverage of generating test and improve their ability to detect errors. We applied it on half a dozen popular open source applications. The test results by Palus attained much higher structural coverage and found more unknown bugs than the other overtures.

Palus approach consists of four component names are, a load time instrumentation and dynamic model component, a static method analysis and a guided random test generation component. We present later a detailed introduction of all components

Related work for automated test generation techniques for OOP have been projected in the final decade. Like JCrasher creates test inputs by using a parameter graph to find method calls whose returns values can serve as input parameter. MSeqGen mines client code bases statically and extracts a frequent pattern as implicit programing rules that are practiced to support in generating tests. Another two alternatives approaches to create test input objects are with direct heap handling and using capture reply techniques.

For future work we are concerned with exploring two research directions. Mainly we plan to use different models like ADABU to guide an automated test generation.. Second, we are interested to train machine learning techniques to complement the dynamically inferred model we introduced here in the paper. Recently there is some work are done on machine learning techniques and proceed along.

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