Software Testing Methods Research Articles

Software Testing and Evaluation on Auto-Loading Control System

Auto-loading system is as an important part of weapons and equipment, its work reliability determines the combat effectiveness and their own safety of weapon systems. As the core of the automatic loading system control, the control software’s reliability of automatic loading system is especially important. In introducing the importance of software testing, from the basic method of software testing starts, design methods is detailing on test and a case of black box test of the automatic loading system, and finally, combined with the equip software testing, software evaluation model was constructed, Results consistent with test results from platform, shooting range, altitude, cold regions, thermal zone, they are proved the software testing and evaluation are valid.

Numerical Experiment on Size Effect for SFRC Splitting Fracture

Based on the MFPA2D software system and test method of the wedge splitting fracture in the Lab., a numerical model was established. The numerical experiments on wedge splitting fracture with plain concrete and SFRC (steel fiber reinforced concrete) were carried on. The calculation results about plain concrete with different dimensions and ligament length proved the numerical model is effectively on numerical calculation, and have a good agreement with the results of the test results. Then, the process of crack initiation, propagation of SFRC specimens with different dimensions and fitting formula about size effect were given. The results indicated that the size effect existed in the splitting fracture energy of SFRC.

Software testing method based on data processing model

Firstly,a software testing method based on data processing model was proposed to overcome those deficiencies of the traditional testing methods applied to data processing software.Secondly,the selection method of testing data based on the diagrams was put forward to avoid any blindness of testing data selection.Finally,using them in coordinate transformation software testing,the results show that the proposed method is feasible and efficient for software testing.

A New Approach to Automated Test Data Generation in Mutation Testing

Mutation testing is an effective software testing method,which generates mutants by applying mutation operators to simulate software defects systematically,and then a test suit is constructed to kill these mutants.It will improve the efficiency and effectiveness in mutation testing to generate test data to kill mutants automatically.The existing approaches generate test datum for killing a single mutant.According to the observation that the conditions of killing multiple same-location mutants are of similar,a new approach is proposed in this paper,which combines these same-location mutants′ conditions,then test datum which may kill more mutants is generated.A prototype is developed,on which experiments are carried out to validate the effectiveness of the proposed approach.

Mutation Based Testing of P Systems

Although testing is an essential part of software development, until re- cently, P system testing has been completely neglected. Mutation testing (mutation analysis) is a structural software testing method which involves modifying the pro- gram in small ways. In this paper, we provide a formal way of generating mutants for systems specified by context-free grammars. Furthermore, the paper shows how the proposed method can be used to construct mutants for a P system specification.

Input-profile-based software failure probability quantification for safety signal generation systems

The approaches for software failure probability estimation are mainly based on the results of testing. Test cases represent the inputs, which are encountered in an actual use. The test inputs for the safety-critical application such as a reactor protection system (RPS) of a nuclear power plant are the inputs which cause the activation of protective action such as a reactor trip. A digital system treats inputs from instrumentation sensors as discrete digital values by using an analog-to-digital converter. Input profile must be determined in consideration of these characteristics for effective software failure probability quantification. Another important characteristic of software testing is that we do not have to repeat the test for the same input value since the software response is deterministic for each specific digital input. With these considerations, we propose an effective software testing method for quantifying the failure probability. As an example application, the input profile of the digital RPS is developed based on the typical plant data. The proposed method in this study is expected to provide a simple but realistic mean to quantify the software failure probability based on input profile and system dynamics.

Failure Size Proportional Models and an Analysis of Failure Detection Abilities of Software Testing Strategies

This paper combines two distinct areas of research, namely software reliability growth modeling, and efficacy studies on software testing methods. It begins by proposing two software reliability growth models with a new approach to modeling. These models make the basic assumption that the intensity of failure occurrence during the testing phase of a piece of software is proportional to the s-expected probability of selecting a failure-causing input. The first model represents random testing, and the second model represents partition testing. These models provide the s-expected number of failures over a period, which in turn is used in analyzing the failure detection abilities of testing strategies. The specific areas of investigation are *) conditions that enable partition testing yielding optimal results, and) comparison between partition testing and random testing in terms of efficacy

Software testing and preventive quality assurance for metrology

Software controlled measuring systems can be approved with the help of different kinds of conformity assessment techniques based either on the final product, the product design or corresponding development and production processes. To validate the software as an integral part of the measuring system, different approaches of software quality assurance have to be applied for different conformity assessment procedures. There are two essential categories of software quality assurance, both of which supplement each other. On the one hand side, analytical methods of software testing, static analysis, and code inspection are used in the scope of conformity assessments of final or intermediate products. On the other hand, preventive audits of software development processes are applied to evaluate and improve appropriate software processes and to consequently support process related conformity assessment procedures. Depending on the validation objectives, validation methods, audit areas, and the appropriate requirements have to be selected and refined. A major problem of validation efforts, namely the process of defining and refining testable requirements, can be solved with the help of international software standards. In Germany, the accredited software testing laboratory at PTB supports software quality in metrology.

Analysis of Software Test Item Generation?? Comparison Between High Skilled and Low Skilled Engineers

Recent software system contain many functions to provide various services. According to this tendency, it is difficult to ensure software quality and to eliminate crucial faults by conventional software testing methods. So taking the effect of test engineer's skill on test item generation into consideration, we propose a new test item generation method, which supports the generation of test items for illegal behavior of the system. The proposed method can generate test items based on use-case analysis, deviation analysis for legal behavior, and faults tree analysis for system fault situations. From the results of the experimental applications of our method, we confirmed that test items for illegal behavior of a system were effectively generated, and also the proposed method could effectively assist test item generation by an engineer with low-level skill.

Model motors [software development for automotive applications

This article discusses software development methods for automotive applications. The emphasis is on software quality and reliability as well as speed of development. Development tools and methods such as agile development and extreme programming are described in detail along with software testing methods. Application areas examined include, engine control, steering systems, GPS navigation, and in-car entertainment.

Experience With Teaching Black-Box Testing in a Computer Science/Software Engineering Curriculum

Software testing is a popular and important technique for improving software quality. There is a strong need for universities to teach testing rigorously to students studying computer science or software engineering. This paper reports the experience of teaching the classification-tree method as a black-box testing technique at the University of Melbourne, Melbourne, Australia, and Swinburne University of Technology, Melbourne, Australia. It aims to foster discussion of appropriate teaching methods of software testing.

The Cost of Poor Testing: A U.S. Government Study (Part 2)

Last month we introduced the U.S. National Institute of Standards and Technology (NIST) study, which attempts to quantify the cost of poor testing. We provided an overview of the study, the national estimates that comprised its conclusions, and a summary. This month we are drilling down into the study to provide the supporting work on software testing methods and tools, along with a detailed look at inadequate infrastructures for testing – infrastructure being the combination of processes, tools, policies and organizations. The purpose of this article is twofold: to provide you with enough details to analyze and improve your own operations and also to provide you with “ammunition” to convince your senior management of the utility and advisability of improving your testing infrastructure and program.

Comparing partition and random testing via majorization and schur functions

The comparison of partition and random sampling methods for software testing has received considerable attention in the literature. A standard criterion for comparisons between random and partition testing based on their expected efficacy in program debugging is the probability of detecting at least one failure causing input in the program's domain. We investigate the relative effectiveness of partition testing versus random testing through the powerful mathematical technique of majorization, which was introduced by Hardy et al. (1952). The tools of majorization and the concepts of Schur (convex and concave) functions (1923) enable us to derive general conditions under which partition testing is superior to random testing and, consequently, to give further insights into the value of partition testing strategies.

Space systems general-purpose processor

The requirements for this processor were established using the experience of the hardware and software designers in the APL Space Department. The use of commercial hardware and software products, combined with an error- and fault-tolerant architecture, resulted in a low-cost design without adversely affecting overall reliability. The processor's architecture and mechanical design, and hardware and software test and validation methods are described.

Testing real-time systems using genetic algorithms

The development of real-time systems is an essential industrial activity whose importance is increasing. The most important analytical method to assure the quality of real-time systems is dynamic testing. Testing is the only method which examines the actual run-time behaviour of real-time software, based on an execution in the real application environment. Dynamic aspects like the duration of computations, the memory actually needed, or the synchronization of parallel processes are of major importance for the correct function of real-time systems and have to be tested. A comprehensive investigation of existing software test methods shows that they mostly concentrate on testing for functional correctness. They are not suited for an examination of temporal correctness which is essential to real-time systems. Very small systems show a wide range of different execution times. Therefore, existing test procedures must be supplemented by new methods, which concentrate on determining whether the system violates its specified timing constraints. In general, this means that outputs are produced too early or their computation takes too long. The task of the tester is to find the inputs with the longest or shortest execution times to check whether they produce a temporal error. If the search for such inputs is interpreted as a problem of optimization, genetic algorithms can be used to find the inputs with the longest or shortest execution times automatically. The fitness function is the execution time measured in processor cycles. Experiments using genetic algorithms on a number of programs with up to 1511 LOC and 843 integer input parameters have successfully identified new longer and shorter paths than had been found using random testing or systematic testing. Genetic algorithms are able therefore to check large programs and they show considerable promise in establishing the validity of the temporal behaviour of real-time software.

Some critical remarks on a hierarchy of fault-detecting abilities of test methods [and reply

In a recent article by P.G. Frankl and E.J. Weyuker (see ibid., vol.19, no.3, p.962-75, 1993), results are reported that appear to establish a hierarchy of software test methods based on their respective abilities to detect faults. The methods used by Frankl and Weyuker to obtain this hierarchy constitute a new and important addition to their arsenal of tools. These tools were developed specifically to establish simple, useful comparisons of test data generation methods. This is the latest step in an ambitious test method classification program undertaken by the Frankl and Weyuker and their collaborators. The article discusses the method and goes on to present a reply to the critique. >

A Test Method for System Software

In this paper a software test method based on “black box” feature of system software is provided, and the related evaluation method is built, too. Thus, it supplies a basis for quantitative evaluation to test system software.

Quality assessment of software prototypes

Abstract This paper introduces a concept for the assessment of prototypes. On the basis of the international standard ISO/IEC CD 12119 it shows that there are differences as well as similarities between traditional methods of software testing and the assessment of software prototypes. Prototype assessments consist mainly of user-driven and ergonomic (usability related) assessments. The degree to which user requirements are realised is also an important assessment item. To perform correctness assessments a proper installation is essential. Without this errors cannot be assigned properly. Furthermore, it is also vital to have reliable documentation available for correctness assessments. Verbal information is insufficient, especially where no or poor general documentation is available. The assessment should be outlined on a black-box basis because the final implementation of the program will normally use a different program language. To maintain the advantage of short reaction times during prototype development it is also important to avoid too long assessment intervals.

A framework for intelligent test data generation

Test data generation using traditional software testing methods generally requires considerable manual effort and generates only a limited number of test cases before the amount of time expanded becomes unacceptably large. A rule-based framework that will automatically generate test data to achieve maximal branch coverage is presented. The design and discovery of rules used to generate meaningful test cases are also described. The rule-based approach allows this framework to be extended to include additional testing requirements and test case generation knowledge.

Expert system assisted test data generation for software branch coverage

With the increased production of complex software systems, verification and validation (V & V) has evolved into a set of activities that span the entire software life cycle. Among these various activities, software testing plays a major role in V&V. Conventional software testing methods generally require considerable manual effort which can generate only a limited number of test cases before the amount of time expended becomes unacceptably large. In this paper, we present a new approach to generating test cases based on artificial intelligence methods. By analyzing the branch coverage of previous test cases, an expert system is able to generate new test cases which provide additional coverage. Heuristic rules are used to modify previous test cases in order to achieve the desired branch coverage. This approach to software testing has the potential for greatly reducing the overall costs associated with branch coverage testing.