“…In the latter case, the search process fails to find the solution even if the positive minimum of the conditional expression is located. Such paths are called "infeasible paths" [9].…”
Abstract-Automated software test data generation is a complex and one of the most challenging task. Generation of test data manually is tedious and error-prone. The base algorithm, which has been improved in this paper involves redundant and un-necessary execution cycles. In this paper, we have proposed an efficient search procedure that reduces the time complexity of test data generation significantly. Our experiments conducted on varying sizes of source code showing ratio of execution time of automated test data generation using Basic Search Procedure and our Improved Search Procedure conclude that, with the increase of source code size, test data generation takes place in lesser time using our improved search procedure.
“…In the latter case, the search process fails to find the solution even if the positive minimum of the conditional expression is located. Such paths are called "infeasible paths" [9].…”
Abstract-Automated software test data generation is a complex and one of the most challenging task. Generation of test data manually is tedious and error-prone. The base algorithm, which has been improved in this paper involves redundant and un-necessary execution cycles. In this paper, we have proposed an efficient search procedure that reduces the time complexity of test data generation significantly. Our experiments conducted on varying sizes of source code showing ratio of execution time of automated test data generation using Basic Search Procedure and our Improved Search Procedure conclude that, with the increase of source code size, test data generation takes place in lesser time using our improved search procedure.
“…A.Beer thought that the simple equivalence partitioning method was insufficient in many cases, and presented a test cases generation method combining the equivalence partitioning, boundary value analysis and cause-effect analysis [1]. Jeng et al partitioned a system's input domain D into a finite set of subdomains D 1 , · · · , D n according to the specification, such that the system's behaviours were uniform on each D i , and then produced test inputs that were close to the boundaries of the subdomains with the aim of finding shifts in boundaries [27,13].…”
Section: Related Workmentioning
confidence: 99%
“…Howden and Foster [11,7] gave careful analyses of the error sensitivity of boundary values testing. Some studies on retrospective fault data showed that boundary value testing outperforms all the other methods, by comparing statement coverage, branch coverage, random testing, boundary value testing and several other testing approaches to find these faults [1,20]. Standards such as IEC61508 permit the use of boundary values to reduce the number of test cases.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, a key problem in software testing is how to develop test cases from the input domain to detect as many faults as possible with a minimum cost. 1 On sabbatical leave to King's College London.…”
Section: Introductionmentioning
confidence: 99%
“…There are a large number of test cases generation strategies, such as random testing [4,8], equivalence partitioning [1,23], boundary value testing [9,16,22], path testing [15,8], and domain testing [12,29].…”
In this paper, we study the hidden dependencies that are a special kind of data flows. They play an important role in software maintenance and evolution because they propagate changes among the classes and they are hard to detect. We propose a technique that finds hidden dependencies ation that is filtered using dynamically generated preconditions and postconditions. We show that these hidden dependencies exist even in well-structured software, like the open source programs JUnit, Drawlets, and Apache FtpServer. We also discuss the precision of this technique.
Software evolution;; program comprehension;; dependency analysis;; execute completely after relation;; invariants
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