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Search-based software testing has achieved great attention recently, but the efficiency is still the bottleneck of it. This paper focuses on improving the efficiency of generating test data for multiple paths. Genetic algorithms are chosen as the heuristic algorithms in search-based software testing in this paper. First, we propose an improved grouping strategy of target paths to balance the load...
Regression testing is a process used to measure the validity of the system during software maintenance. Regression testing process is very expensive and must be introduced each time a modification occurs in software to ensure that the system still work and that the new modification doesn't cause any bugs, this process depends on selecting test cases from a test suite. Selection of test cases is very...
In software project management, software effort estimation is an important task. Software effort estimation will be helpful for finding the estimation of cost, duration of the project. In the recent time, many types of model are coming but among all, COCOMO model is widely used model. In past lots of Research have been done for correct and Accurate Effort Estimation. Many Algorithm has been applying...
Software product line evolution is a decision-making problem where it is determined that which features are the best candidates for the different product. In this paper, we analysis two popular optimization technique for finding qualified features for next release. In this case, the qualification of features is determined by the product value, product integrity, and AND dependencies between features...
Path testing is one of the powerful coverage criteria in white box testing. In path testing every logical path has to be executed at least once but it is extremely difficult to execute or test the entire path for given program. So instead of executing all the paths a set of independent path are executed which are called as basis set path. In this paper we proposed novel approach for the utilization...
Software Reliability is an important feature of software quality, like other quality attribute as functionality, usability, performance, serviceability, maintainability, documentation etc. This Software reliability optimization is very important in software development field. Lots of software reliability models have been specified in last few years. This paper reviews the different Evolutionary algorithms...
The goal of test suite prioritization is maximizing fault detection and code coverage rate. Several nature inspired optimization algorithms such as Swarm Intelligence (SI) have been studied for the optimization of such problems. The studies revealed the benefits of Artificial Bee Colony (ABC) over other algorithms. ABC and its variations were implemented in software testing areas, test suite prioritization...
In order to solve the problems of traditional Fuzzing technique for software vulnerability detection, a novel method based on code coverage and test cost is proposed. Firstly, static analysis is applied to calculate the code coverage information, including basic block coverage and new block coverage. In addition, test path diversity information is introduced to elevate path coverage, which is achieved...
Software effort estimation is amongst the most important tasks in software project management as many decisions like cost estimation, deadline of submitting of project and timely planning a project are dependent on it. Many models are available for effort estimation and most widely used is COCOMO Model. A lot of research work has been done for the correct and accurate use of effort estimation models...
The analysis of test case generation based on particle swarm algorithm introduced the group self-activity feedback (SAF) operator and Gauss mutation (G) changing inertia weight to improve the performance of particle swarm optimization (PSO). Using the improved algorithm in software test case, experiments show that the introduction of a single path fitness function structure and multi-path fitness...
Regression Testing is an inevitable and very costly maintenance activity that is implemented to make sure the validity of modified software in a time and resource constrained environment. Execution of entire test suite is not possible so it is necessary to apply techniques like Test Case Selection and Test Case Prioritization to select and prioritize a minimum set of test cases, fulfilling some chosen...
Bat Algorithm is one of the successful metaheuristic algorithms, which is used prominently for the purpose of optimization. But its inherent feature of non-changing parameters with the various iterations makes it less appropriate for optimization of software cost estimation techniques like COCOMO. So the current study proposes a hybrid model for the improvement of Bat algorithm by enhancing the search...
In a modern software system, when a program fails, a crash report which contains an execution trace would be sent to the software vendor for diagnosis. A crash report which corresponds to a failure could be caused by multiple types of faults simultaneously. Many large companies such as Baidu organize a team to analyze these failures, and classify them into multiple labels (i.e., multiple types of...
Software product line evolution involves decisions like finding which products are better candidates for realizing new feature requests. In this paper, we propose a solution for finding trade-off evolution alternatives for products while balancing between overall value and product integrity. The purpose of this study is to support product managers with feature selection for an existing product line...
This paper discusses the design and subsequent analysis of software implementing a configurable genetic algorithm. The genetic algorithm is primarily targeted towards the solving of Sudoku puzzles. Sudoku is regarded as an ideal test-bed for algorithm development due to the fact that it is a constrained optimisation problem that belongs to the NP-complete class of computational problems. The aim of...
It is very practical significance to seek an effective path-oriented test data automatic generation method. The genetic algorithm, ant colony algorithm is commonly used to generate test data, and the both can improve the efficiency of test data generation. But, for both algorithms, there was a little limitation to target path in path testing for being prone to local optimal solution. Some researchers...
Hardware/software partitioning is a crucial problem in hardware/software co-design. In this paper, we deeply investigate genetic algorithm (GA) for hardware/software partitioning, our co-design targets a heterogeneous multicore system on chip (SoC) which consists of several different types of processing engines(PE), Communicating structure adopts NOC, We use GA for four task graphs to simulate the...
To assess the quality of test suites, mutation analysis seeds artificial defects (mutations) into programs; a nondetected mutation indicates a weakness in the test suite. We present an automated approach to generate unit tests that detect these mutations for object-oriented classes. This has two advantages: First, the resulting test suite is optimized toward finding defects modeled by mutation operators...
Rough Set Theory is used to make uncertainty description of the real world, and attribute reduction is one of the core theories of Rough Set Theory. This article elaborates on the rough set theory, studies attribute reduction algorithm combined with the genetic algorithm, and finally demonstrate the feasibility and effectiveness by using the ROSETTA software.
Many Search Based Software testing (SBST) have been proposed and experiments show that they can generate effective test data. However, a meta-heuristic search (MHS) algorithm in these techniques incurs considerable computation cost to evaluate fitness values, which results in huge test case generation cost. In this paper, we propose a more effective fitness evaluation technique based on Fitness Evaluation...
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