Guideline of Test Suite Construction for GUI Software Centered on Grey-Box Approach

In this paper, the test suite construction for GUI (Graphical User Interface) software may be executed centered on grey-box approach with the prior test design of window access controls for unit testing, including front-end method of white box and follow-up black box method for integration testing. Moreover, two key opinions are proposed for the test suite construction for GUI software, the first one is that the “Triple-step method” should be used for unit testing with the prior disposing of data boundary value testing of input controls, and another one is that the “Grey-box approach” should be applied in integration testing for GUI software with necessary testing preparation in the precondition. At the same time, the testing of baseline version and the incremental testing should be considered for the test case construction to coordinate with the whole evolution of software product today. Additionally, all our opinion and thought are verified and tested with a typical case of GUI software—PQMS (Product Quality Monitoring Software/System), and results indicate that these methods and specific disposing are practical and effective.

Improved Test Case Selection Algorithm to Reduce Time in Regression Testing

Regression testing(RT)is an essential but an expensive activity in software development.RT confirms that new faults/errors will not have occurred in the modified program.RT efficiency can be improved through an effective technique of selected only modified test cases that appropriate to the modifications within the given time frame.Earlier,several test case selection approaches have been introduced,but either these techniques were not sufficient according to the requirements of software tester experts or they are ineffective and cannot be used for available test suite specifications and architecture.To address these limitations,we recommend an improved and efficient test case selection(TCS)algorithm for RT.Our proposed technique decreases the execution time and redundancy of the duplicate test cases(TC)and detects onlymodified changes that appropriate to themodifications in test cases.To reduce execution time for TCS,evaluation results of our proposed approach are established on fault detection,redundancy and already executed test case.Results indicate that proposed technique decreases the inclusive testing time of TCS to execute modified test cases by,on average related to a method of Hybrid Whale Algorithm(HWOA),which is a progressive TCS approach in regression testing for a single product.

Multi-Objective Modified Particle Swarm Optimization for Test Suite Reduction(MOMPSO)

Software testing plays a pivotal role in entire software development lifecycle.It provides researchers with extensive opportunities to develop novel methods for the optimized and cost-effective test suite Although implementation of such a cost-effective test suite with regression testing is being under exploration still it contains lot of challenges and flaws while incorporating with any of the new regression testing algorithm due to irrelevant test cases in the test suite which are not required.These kinds of irrelevant test cases might create certain challenges such as code-coverage in the test suite,fault-tolerance,defects due to uncovered-statements and overall-performance at the time of execution.With this objective,the proposed a new Modified Particle Swarm optimization used for multi-objective test suite optimization.The experiment results involving six subject programs show that MOMPSO method can outer perform with respect to both reduction rate(90.78%to 100%)and failure detection rate(44.56%to 55.01%).Results proved MOMPSO outperformed the other stated algorithms.

Reusing Test Cases Based on the Function Point

Reusing test cases from existing test case library is quite common in the software testing field. Testing practice tells us that there is a strong relationship between the granularity of a function unit under testing and that of the test case. A function unit with small granularity usually results in the test cases with the same small granularity. Therefore a test case defined as the function point,i. e.,the smallest size function unit,was provided for the first time.Though test cases with smaller granularity usually have better reusability,the cost of accurately reusing and integrating such test cases is also higher. In order to balance the test case reusability and the cost of test case reuse,a novel test case reuse model based on the function point was proposed in this paper. In this model,a reusable test case for specification-based testing was defined and some reuse strategies and three formal reuse methods were given. Finally,the complete automatic software process was realized by a reusing generation tool. The new method has improved reuse accuracy,while greatly enhances the software productivity.

Software Testing Method Based on Model Comparison

A model comparison based software testing method （MCST） is proposed. In this method, the requirements aria programs or software under test are transformed into the ones in the same form, and described by the same model describe language （MDL）. Then, the requirements are transformed into a specification model and the programs into an implementation model. Thus, the elements and structures of the two models are compared, and the differences between them are obtained. Based on the diffrences, a test suite is generated. Different MDLs can be chosen for the software under test. The usages of two classical MDLs in MCST, the equivalence classes model and the extended finite state machine （EFSM） model, are described with example applications. The results show that the test suites generated by MCST are more efficient and smaller than some other testing methods, such as the pathcoverage testing method, the object state diagram testing method, etc.

SPIDER:Speeding up Side-Channel Vulnerability Detection via Test Suite Reduction

Side-channel attacks allow adversaries to infer sensitive information,such as cryptographic keys or private user data,by monitoring unintentional information leaks of running programs.Prior side-channel detection methods can identify numerous potential vulnerabilities in cryptographic implementations with a small amount of execution traces due to the high diffusion of secret inputs in crypto primitives.However,because non-cryptographic programs cover different paths under various sensitive inputs,extending existing tools for identifying information leaks to non-cryptographic applications suffers from either insufficient path coverage or redundant testing.To address these limitations,we propose a new dynamic analysis framework named SPIDER that uses fuzzing,execution profiling,and clustering for a high path coverage and test suite reduction,and then speeds up the dynamic analysis of side-channel vulnerability detection in non-cryptographic programs.We analyze eight non-cryptographic programs and ten cryptographic algorithms under SPIDER in a fully automated way,and our results confirm the effectiveness of test suite reduction and the vulnerability detection accuracy of the whole framework.

Modified condition decision coverage criteria for test suite prioritization using particle swarm optimization

Purpose–Test suite prioritization technique is the process of modifying the order in which tests run to meet certain objectives.Early fault detection and maximum coverage of source code are the main objectives of testing.There are several test suite prioritization approaches that have been proposed at the maintenance phase of software development life cycle.A few works are done on prioritizing test suites that satisfy modified condition decision coverage(MC/DC)criteria which are derived for safety-critical systems.The authors know that it is mandatory to do MC/DC testing for Level A type software according to RTCA/DO178C standards.The paper aims to discuss this issue.Design/methodology/approach–This paper provides a novel method to prioritize the test suites for a system that includes MC/DC criteria along with other important criteria that ensure adequate testing.Findings–In this approach,the authors generate test suites from the input Java program using concolic testing.These test suites are utilized to measure MC/DC%by using the coverage calculator algorithm.Now,use MC/DC%and the execution time of these test suites in the basic particle swarm optimization technique with a modified objective function to prioritize the generated test suites.Originality/value–The proposed approach maximizes MC/DC%and minimizes the execution time of the test suites.The effectiveness of this approach is validated by experiments on 20 moderate-sized Java programs using average percentage of fault detected metric.

SIP Conformance Testing Based on TTCN-2

The session initiation protocol (SIP) is a signaling protocol for Internet telephony, multimedia conferencing, presence, event notification, and instant messaging. With the gaining popularity, more and more SIP implementations have been developed and deployed. How to guarantee the conformance of those SIP implementations is the key point of interconnection and interoperation among them. This paper proposes the test method and architecture for the SIP protocol based on the IPv6 tester system. Tree and tabular combined notation (TTCN-2) is adopted to describe the test suite. With an enhanced reference implementation, the data-processing ability to the original test system has been greatly improved. In the following test practices, some errors have been found in the SIP entities under test. It is proved that the proposed test method and architecture are effective to verify the conformance of the SIP entities, and the result of the conformance test may provide helpful reference to the development of SIP products.

A Usable Selection Range Standard Based on Test Suite Reduction Algorithms

In this paper, we analyze the features and distinctions of 6 classical algorithms： greedy algorithm （G）, greedy evolution algorithm （GE）, heuristics algorithm （H）, greedy heuristic G （GRE）, integer linear programming algorithm （ILP） and genetic algorithm （GA） to ensure the main influencing factors-the performance of algorithms and the running time of algorithms. What＇s more, we would not only present a research design that aims at gaining deeper understanding about the algorithm classification and its function as well as their distinction, but also make an empirical study in order to obtain a practical range standard that can guide the selection of reduction algorithms. When the size of a test object （product of test requirements and test cases） is smaller than 2000×2000, G algorithm is the commonly recommended algorithm. With the growth of test size, the usage of GE and GRE becomes more general.

Balancing Frequencies and Fault Detection in the In-Parameter-Order Algorithm

The In-Parameter-Order （IPO） algorithm is a widely used strategy for the construction of software test suites for combinatorial testing （CT） whose goal is to reveal faults triggered by interactions among parameters. Variants of IPO have been shown to produce test suites within reasonable amounts of time that are often not much larger than the smallest test suites known. When an entire test suite is executed, all faults that arise from t-way interactions for some fixed t are surely found. However, when tests are executed one at a time, it is desirable to detect a fault as early as possible so that it can be repaired. The basic IPO strategies of horizontal and vertical growth address test suite size, but not the early detection of faults. In this paper, the growth strategies in IPO are modified to attempt to evenly distribute the values of each parameter across the tests. Together with a reordering strategy that we add, this modification to IPO improves the rate of fault detection dramatically （improved by 31% on average）. Moreover, our modifications always reduce generation time （2 times faster on average） and in some eases also reduce test suite size.

A Fast Pseudorandom Number Generator with BLAKE Hash Function

This paper presents a fast pseudorandom generation algorithm,which is based on the BLAKE hash function and can pass the random test of the NIST（National Institute of Standards and Technology） Statistical Test Suite.Through theoretical analysis and experimental imitation,our new algorithm is proven to be more secure and efficient than G-SHA1.Simultaneously,we introduce and discuss the BLAKE in detail.Its security shows that can be utilized to generate pseudorandom bit sequences,which the experimental results show the BLAKE hash function has excellent pseudorandomness.Therefore,we believe the BLAKE is one of the most potential candidate algorithms of SHA-3 program.