Testing Object-oriented Software Research Articles

A cost-effective adaptive random testing algorithm for object-oriented software testing

The rapid development of object oriented programming (OOP) technology has made it one of the mainstream programming technologies that has been widely used in the design and development of object oriented software (OOS). The inheritance, encapsulation and polymorphism properties of object-oriented language can improve the reusability, scalability and interoperability of software while increasing the difficulty of testing OOS. Researchers have proposed a variety of testing methods to test OOS among which random testing (RT) has been widely used due to its simplicity and ease of use. An OMISS-ARTsum algorithm is proposed in this paper that uses improved OMISS random test FSCS-ART with max-sum standard, which is an implementation version of fixed-sized-candidate-set ART. The OMISS-ARTsum algorithm calculates the total distance between a candidate test case and the executed test case set before the next test case is selected from the set of candidate test cases. Unlike the traditional max-sum based FSCS-ART algorithm, OMISS-ARTsum does not calculate the distance between each executed test case and the candidate case and then sum up the total distance, but uses the method of summing up all the executed test cases and the candidate cases. The information of executing test cases is saved as a whole and the distance between the executed test case set and candidate cases is calculated at the same time. Experiment shows that compared to the OMISS-ART algorithm, the proposed OMISS-ARTsum algorithm can reduce the time overhead.

Toward a K-means clustering approach to adaptive random testing for object-oriented software

Toward a K-means clustering approach to adaptive random testing for object-oriented software

A Modified Similarity Metric for Unit Testing of Object-Oriented Software Based on Adaptive Random Testing

Finding an effective method for testing object-oriented software (OOS) has proven elusive in the software community due to the rapid development of object-oriented programming (OOP) technology. Although significant progress has been made by previous studies, challenges still exist in relation to the object distance measurement of OOS using Adaptive Random Testing (ART). This is partly due to the unique features of OOS such as encapsulation, inheritance and polymorphism. In a previous work, we proposed a new similarity metric called the Object and Method Invocation Sequence Similarity (OMISS) metric to facilitate multi-class level testing using ART. In this paper, we broaden the set of models in the metric (OMISS) by considering the method parameter and adding the weight in the metric to develop a new distance metric to improve unit testing of OOS. We used the new distance metric to calculate the distance between the set of objects and the distance between the method sequences of the test cases. Additionally, we integrate the new metric in unit testing with ART and applied it to six open source subject programs. The experimental result shows that the proposed method with method parameter considered in this study is better than previous methods without the method parameter in the case of the single method. Our finding further shows that the proposed unit testing approach is a promising direction for assisting software engineers who seek to improve the failure-detection effectiveness of OOS testing.

Ant Lion optimizer for state based object oriented testing

Object-oriented paradigm is the most widely exploited design paradigm in the IT industry. The great functionalities of object-orientation not only improve the developed software but also introduce a wide variety of problems in testing. For instance, not only the object but also the state of object impacts testing. Various other serious issues of testing come along with object orientation. Thus, this has always been a major concern of software testers. Hence, it is very important to optimize this whole process of object-oriented software testing. Numerous meta-heuristic algorithms have been exploited in the past to accomplish this goal. In this paper, we are presenting a novel nature-inspired algorithm, AntLion Optimization (ALO) to generate optimal test paths for object-oriented software. Here, we are accompanying model based testing instead of code based testing as, this helps in reducing the testing effort and cost by identifying the error and bugs in the design phase itself. The main goal of model based software testing is to cover all the transitions present in the system i.e. full path coverage must be there. ALO is a novel meta-heuristic algorithm based on the random movement of ants in search of food, constructing traps by antlions, tricking the ants in trap, catching preys and reconstruction of traps. We introduces a random factor in the fitness function to capture the random motion of ants in the search space in search of food. This algorithm has been applied on three object-oriented software applications and the result guarantees complete path coverage which is a primary goal of software testing.

A Technique for Regression Testing of Object Oriented Software

The main challenge in testing an OOS is that there are large number of test cases which are not feasible to execute all of them within constrained time and budget. This paper proposes some factors which can be used to prioritize the test cases in order to have an effective testing. The considered factors are based on the testing history and structured analysis of the software. These factors may be nature of bug, capability of a test case, execution time, business impact, coverage of code in terms of classes(old and new classes), etc. Every factor has been assigned a positive weight which shows the criticality of the factor and ability to introduce the errors in the software. The prioritized set of test cases thus obtained is helpful to discover maximum bugs as early as possible.

Utilizing Object Oriented Software Testing Tools in Microsoft Corporation

The paper seeks to access the utilization of object oriented software testing tools and its ability to improve the efficiency of new software production in Microsoft Corporation. In recent times, new software is becoming increasingly complex with a whole lot of risks associated with failure when being utilized. This has indicated that far greater importance has to be placed on testing to guarantee the software works properly as well as corresponds with the customer requirement. This document looks at software testing of new software being produced in Microsoft Corporation using several software testing tools and techniques that can in turn help improve the efficiency and cogency of the software testing process as well as the quality of new software that are produced in the company. The results show that object oriented software testing tools actually work on the new software produced by Microsoft Corporation. Basic problems that are needed to be addressed when applying various testing tools during testing process demonstrated the need and effectiveness for the utilization of object oriented testing tools. Furthermore, suggestions were made in respect to the necessary refinements to the existing ways in which Microsoft test their new software in respect of getting the best out of the organization.

Integration Testing Prior to Unit Testing: A Paradigm Shift in Object Oriented Software Testing of Agile Software Engineering

Objectives: The main objective of the paper is to investigate the paradigm shift in software testing with hypothesis testing should precede unit testing for cultural transformation resulting in economic governance. Methods: The research method employed is real time as the authors involved in the development process in two reputed software companies. We considered five projects namely Vehicle Monitoring System (VMS), Easy Subcontracting (EZSUB), Key to Engineering (K2ENGG), Electronic Material List (EMLIST), and Feedback Database (FBDB). They are developed in Agile methodology. We observed the testing time with traditional approach and also the proposed approach which puts integration testing prior to unit testing. Findings: Our research in association with leading software development companies revealed that integration testing prior to unit testing has significant impact on accelerating and transforming to increased agility. Thus the hypothesis is tested and proved to be positive. This new approach in testing will go a long way in achieving agility at scale with increased success rate. Our findings can be summarized as follows. Integration testing prior to unit testing can take software enterprises towards agility at scale. The new paradigm shift can cause cultural transformation from traditional approach to economic governance through agile methods. It also could improve in various parameters such as time-to deliver products, efficiency in software development and delivery process, increased personnel morale and increased client satisfaction besides achieving high success rate in the context focusing agility at scale. The proposed approach resulted in performance improvement in all five projects. The average percentage increase in productivity and delivery for VMS is 27.62%, EZSUB 27.74%, K2ENGG 31.29%, EMLIST 30.83% and FBDB 33.33%. Application: To our knowledge it is our first empirical study that threw light on the paradigm shift in object oriented software testing with different case studies.

Comparative Analysis of Traditional and Object-Oriented Software Testing

Software testing is an important phase of the software development life cycle. Testing is the process of executing the program with the goal of finding errors. The purpose of testing is not only to find the bugs in software but also to improve the quality of software. This paper compares traditional and object-oriented software testing. Today, object-oriented concepts are used throughout software engineering. Testing of object-oriented software is different from testing of traditional software. Object-oriented software testing offers new challenges to the software testing team, because the object-oriented approach supports several new and powerful features. This paper focuses on the need for adopting an object-oriented software-testing approach and the challenges that occur in object-oriented testing.

Integrating Evolutionary Testing with Reinforcement Learning for Automated Test Generation of Object‐Oriented Software

Recent advances in evolutionary test generation greatly facilitate the testing of Object-oriented (OO) software. Existing test generation approaches are still limited when the Software under test (SUT) includes Inherited class hierarchies (ICH) and Non-public methods (NPM). This paper presents an approach to generate test cases for OO software via integrating evolutionary testing with reinforcement learning. For OO software with ICH and NPM, two kinds of particular isomorphous substitution actions are presented and a Q-value matrix is maintained to assist the evolutionary test generation. A prototype called EvoQ is developed based on this approach and is applied to generate test cases for actual Java programs. Empirical results show that EvoQ can efficiently generate test cases for SUT with ICH and NPMand achieves higher branch coverage than two state-of-the-art test generation approaches within the same time budget.

A Novel Approach of Mutation Testing of Object-Oriented Programs

Mutation testing is a powerful but complicated and computationally expensive testing method. Testing of object-oriented software has a number of features that make it different from conventional software testing. The factors like inheritance, encapsulation, polymorphism, which are the specialized phenomena of object- oriented software bring in the point of different. Mutation testing is a fault-based testing technique that has the advantage of easy automation, and can check the thoroughness of testing performed using other testing approaches. Mutation operators are an important consideration while designing the mutation testing methodologies. This paper presents mutation operators, testing techniques, available tools and the current research directions.

Object-Oriented Evolutionary Testing

In Object-Oriented Evolutionary Testing, metaheuristics are employed to select or generate Test Data for Object-Oriented software. The application of search-based strategies to the Software Testing of Object-Oriented Software is fairly recent and is yet to be investigated comprehensively; this article aims to explore, review and contextualize relevant literature and research in this area, while pinpointing open problems and setting grounds for future work.

Equality to Equals and Unequals: A Revisit of the Equivalence and Nonequivalence Criteria in Class-Level Testing of Object-Oriented Software

Algebraic specifications have been used in the testing of object-oriented programs and received much attention since the 1990s. It is generally believed that class-level testing based on algebraic specifications involves two independent aspects: the testing of equivalent and nonequivalent ground terms. Researchers have cited intuitive examples to illustrate the philosophy that even if an implementation satisfies all the requirements specified by the equivalence of ground terms, it may still fail to satisfy some of the requirements specified by the nonequivalence of ground terms. Thus, both the testing of equivalent ground terms and the testing of nonequivalent ground terms have been considered as significant and cannot replace each other. In this paper, we present an innovative finding that, given any canonical specification of a class with proper imports, a complete implementation satisfies all the observationally equivalent ground terms if and only if it satisfies all the observationally nonequivalent ground terms. As a result, these two aspects of software testing cover each other and can therefore replace each other. These findings provide a deeper understanding of software testing based on algebraic specifications, rendering the theory more elegant and complete. We also highlight a couple of important practical implications of our theoretical results.

EATOOS-Testing Tool for Unit Testing of Object Oriented Software

the advent of Object Oriented programming, most of the software being built is using object oriented programming languages. The major challenge lies with testing the software and it is a known fact that testing consumes around 40% of the time in the total software development process. If more number of errors are uncovered in the unit testing phase itself then the probability of propagation of errors to other components or phases gets reduced drastically. Similarly object oriented software also needs to be tested thoroughly at unit level. Unit level testing in OO software refers to the individual classes or group of classes which need to be tested. In the current work an attempt has been made to come up with an automated testing tool for unit testing of object oriented classes developed in java. It offers a single click automation solution for unit testing of OO software by providing the flexibility for the tester to choose the methods of his choice to test.

Comparison between Object-Oriented Software Testing and Traditional Software Testing

Object-oriented technology has been widely used in the area of computer software. However, traditional software testing techniques cannot perform effectively on object-oriented software. The differences between object-oriented software testing and traditional software testing are compared and elaborated from three aspects: testing model, testing software and testing cases.

Generation Technology of Test Cases of Object-Oriented Software

This paper analyzed the basic object-oriented concepts from the perspective of testing. The effects of the characteristics of object-oriented software on the software testing were discussed. The class testing method of object-oriented software was put forward. This method includes tests based on the state transition diagram and data flow testing on class. A integration testing of object-oriented software was put forward based on the event-driven characteristics of object-oriented software, and a data-generating method of software test based on genetic algorithm was provided. The test case generating technology of object-oriented software was discussed, which utilized an intercalation method of branch function and regarded the genetic algorithm as the core search algorithm.

A Analysis and Research on the Methods of Object Oriented Software Testing

This paper proposes a genetic algorithm-based method to generate test cases. This method provides information for test case generation using state machine diagrams. Its feature is realizing automation through fewer generated test cases. In terms of automatic generation of test data based on path coverage, the goal is to build a function that can excellently assess the generated test data and guide the genetic algorithms to find the targeting parameter values.

Research of State-Base Object-Oriented Software Testing

This paper has explored the characteristic of objected-oriented programming languages and its impact on software testing. Has summarized the main contents of object-oriented software testing, hierarchical testing and approaches for designing the test case. Has discussing the current situation and the future development of object-oriented software testing technology.

Some Observations on Object Oriented Software Testing Effort

Estimation and measurement is an important field of software engineering. There are several factors available in real word that can be measured directly, but few or no software engineering attributes or tasks are so simple that can measure directly. Due to development of OO paradigm it is also become cumbersome to measure different attributes of software development directly. All attributes and activities are depending on several other attributes or factors. To measure these activities we have to take consideration of different types of metrics. In context of OO software, measuring the testing effort is the activity which is least bother by researchers. In this work we have proposed model for measuring OO software testing effort by taking different affecting factors into consideration.Keywords: OO Software Testing, measurement, metrics, effortNigerian Journal of Technological Research, vol 7(1) 2012

Multi-Objective Genetic Algorithm Using Class-Based Elitist Approach

An approach named Class -Based Elitist Genetic Algorithm is presented in this paper. The test data is being generated for object-oriented programs using evolutionary techniques. A class -based algorithm derived from class control-flow graph (CCFG) is used fo r testing object-oriented software. Evolutionary techniques have been used for solving most of the software engineering problems. Evolutionary testing technique which is based on theory of evolution like reproduction, mutation, recombination, and selection is used to generate test cases in CBEGA. Evolutionary Algorithm applies these techniques repeatedly toa set of individuals called population to obtain optimal solution in a global search space with minimum search time. Multi-objective optimization involves optimizing a number of objectives simultaneously like time, cost and fault detection capability. The objectives considered here for optimization are maximum path coverage, minimum test suite size, and minimum execution time. For experiments, the data are taken from Siemens’ test suite which shows better path coverage results like 9 6% in CBEGA and are co mpared with simple GA which gives only 88% path coverage for a set of sample java classes.

Unit Test Case Design Metrics in Test Driven Development

Testing is a validation process that determines the conformance of the software’s implementation to its specification. It is an important phase in unit test case design and is even more important in object-oriented systems. We want to develop test case designing criteria that give confidence in unit testing of object-oriented system. The main aim testing can be viewed as a means of assessing the existing quality of the software to probe the software for defect and fix them. We also want to develop and executing our test case automatically since this decreases the effort (and cost) of software development cycle (maintenance), and provide re-usability in Test Driven Development framework. We believe such approach is necessary for reaching the levels of confidence required in unit testing. The main goal of this paper is to assist the developers/testers to improve the quality of the ATCUT by accurately design the test case for unit testing of object-oriented software based on the test results. A blend of unit testing assisted by the domain knowledge of the test case designer is used in this paper to improve the design of test case. This paper outlines a solution strategy for deriving Automated Test Case for Unit Testing (ATCUT) metrics from object-oriented metrics via TDD concept.