Coverage criteria and test requirement reduction for component-based web application

In order to analyze and test the component-based web application and decide when to stop the testing process, the concept of coverage criteria and test requirement reduction approach are proposed. First, four adequacy criteria are defined and subsumption relationships among them are proved. Then, a translation algorithm is presented to transfer the test model into a web application decision-to-decision graph（WADDGraph）which is used to reduce testing requirements. Finally, different sets of test requirements can be generated from WADDGraph by analyzing subsumption and equivalence relationships among edges based on different coverage criteria, and testers can select different test requirements according to different testing environments. The case study indicates that coverage criteria follow linear subsumption relationships in real web applications. Test requirements can be reduced more than 55% on average based on different coverage criteria and the size of test requirements increases with the increase in the complexity of the coverage criteria.

The Web Application Test Based on Page Coverage Criteria

Software testing coverage criteria play an important role in the whole testing process.The current coverage criteria for web applications are based on program or URL.They are not suitable for black-box test or intuitional to use.This paper defines a kind of test criteria based on page coverage sequences only navigated by web application,including Page_Single,Page_Post,Page_Pre,Page_Seq2,Page_SeqK.The test criteria based on page coverage sequences made by interactions between web application and browser are being under consideration after that.In order to avoid ambiguity of natural language,these coverage criteria are depicted using Z formal language.The empirical result shows that the criteria complement traditional coverage and fault detection capability criteria.

Automated Test Case Generation from Requirements: A Systematic Literature Review

Software testing is an important and cost intensive activity in software development.The major contribution in cost is due to test case generations.Requirement-based testing is an approach in which test cases are derivative from requirements without considering the implementation’s internal structure.Requirement-based testing includes functional and nonfunctional requirements.The objective of this study is to explore the approaches that generate test cases from requirements.A systematic literature review based on two research questions and extensive quality assessment criteria includes studies.The study identies 30 primary studies from 410 studies spanned from 2000 to 2018.The review’s nding shows that 53%of journal papers,42%of conference papers,and 5%of book chapters’address requirementsbased testing.Most of the studies use UML,activity,and use case diagrams for test case generation from requirements.One of the signicant lessons learned is that most software testing errors are traced back to errors in natural language requirements.A substantial amount of work focuses on UML diagrams for test case generations,which cannot capture all the system’s developed attributes.Furthermore,there is a lack of UML-based models that can generate test cases from natural language requirements by rening them in context.Coverage criteria indicate how efciently the testing has been performed 12.37%of studies use requirements coverage,20%of studies cover path coverage,and 17%study basic coverage.

Effectiveness Assessment of the Search-Based Statistical Structural Testing

Search-based statistical structural testing(SBSST)is a promising technique that uses automated search to construct input distributions for statistical structural testing.It has been proved that a simple search algorithm,for example,the hill-climber is able to optimize an input distribution.However,due to the noisy fitness estimation of the minimum triggering probability among all cover elements(Tri-Low-Bound),the existing approach does not show a satisfactory efficiency.Constructing input distributions to satisfy the Tri-Low-Bound criterion requires an extensive computation time.Tri-Low-Bound is considered a strong criterion,and it is demonstrated to sustain a high fault-detecting ability.This article tries to answer the following question:if we use a relaxed constraint that significantly reduces the time consumption on search,can the optimized input distribution still be effective in faultdetecting ability?In this article,we propose a type of criterion called fairnessenhanced-sum-of-triggering-probability(p-L1-Max).The criterion utilizes the sum of triggering probabilities as the fitness value and leverages a parameter p to adjust the uniformness of test data generation.We conducted extensive experiments to compare the computation time and the fault-detecting ability between the two criteria.The result shows that the 1.0-L1-Max criterion has the highest efficiency,and it is more practical to use than the Tri-Low-Bound criterion.To measure a criterion’s fault-detecting ability,we introduce a definition of expected faults found in the effective test set size region.To measure the effective test set size region,we present a theoretical analysis of the expected faults found with respect to various test set sizes and use the uniform distribution as a baseline to derive the effective test set size region’s definition.