Black-box Testing Technique Research Articles

Generating semantically valid test inputs using constrained input grammars

ContextGenerating test cases based on software input interface is a black-box testing technique that can be made more effective by using structured input models such as input grammars. Automatically generating grammar-based test inputs may lead to structurally valid but semantically invalid inputs that may be rejected in early semantic error checking phases of a system under test. ObjectiveThis paper aims to introduce a method for specifying a grammar-based input model with the model’s semantic constraints to be used in the generation of positive test inputs. It is also important that the method can generate effective test suites based on appropriate grammar-based coverage criteria. MethodFormal specification of both input structure and input semantics provides the opportunity to use model instantiation techniques to create model instances that satisfy all specified constraints. The input interface of a subject system can be specified using a high-level specification scheme such as attribute grammars, and a transformation function from this scheme to an instantiable formal modeling language can generate the desired model instances. ResultsWe propose a declarative grammar-based input specification method that is based on a variation of attribute grammars and allows the user to specify input constraints in addition to input structure. The model can be instantiated automatically to generate structurally and semantically valid test inputs. The proposed method has the capability to specify test requirements and coverage criteria and use them to generate valid test suites that satisfy test coverage criteria requirements. ConclusionThe work presented in this paper provides a black-box test generation method for grammar-based software inputs that can automatically generate criteria-covering test suites.

Analysis of various testing techniques

Testing is the process of exercising a program with the explicit goal of detecting errors prior to delivery to the end user. There are a variety of testing techniques available. They are broadly classified into black box techniques and white box testing techniques. Strategies for black box testing are based on the specification of the software component under test. Tests developed using the black box techniques detect errors against the functional requirements of software. On the other hand strategies for white box testing are based on the internal logic of software components. White box test suites are derived from the source code of the software component under test. This paper aims to study various testing techniques and their comparative analysis. The first section of the paper is a qualitative description of various White box and black box testing techniques. The second section of the paper uses C programs to demonstrate the process of testing used by different testing techniques. The paper uses ten C programs for testing. Two cases are used as illustrations in the second section of the paper. The paper presents the results of testing different programs of varying complexity using seven types of testing techniques. The last section presents a comparative analysis of various testing techniques on different parameters and their results.

Preventing DoS attacks in NGN networks with proactive specification-based fuzzing

Next-generation networks introduce an IPbased network foundation and more powerful access technologies. As a result, vulnerabilities in network protocol implementations can be exploited with Internet hacking tools to cause denial-of-service and distributed denial of service situations. Fuzzing is a black-box testing technique originally used by crackers to find exploitable vulnerabilities. In this article, we demonstrate how specification-based fuzzers can be used to discover exploitable vulnerabilities proactively to make networks and devices more robust against DoS and DDoS attacks.

Black Box and White Box Testing Techniques - A Literature Review

There are several methods for automatic test case generation has been proposed in the past. But most of these techniques are structural testing techniques that require the understanding of the internal working of the program. There is less practical coverage of all testing techniques together. In this paper we conducted a literature study on all testing techniques together that are related to both Black and White box testing techniques, moreover we assume a case situation of Insurance premium calculation for driver and we derive the test cases and test data for white box testing methods such as Branch testing, Statement testing, Condition Coverage testing, multiple condition coverage testing, in the similar way we derive the test cases and test data for the black box testing methods such as: Equivalence partitioning and Boundary value analysis.

A Comparative Study of White Box, Black Box and Grey Box Testing Techniques

Software testing is the process to uncover requirement, design and coding errors in the program. It is used to identify the correctness, completeness, security and quality of software products against a specification. Software testing is the process used to measure the quality of developed computer software. It exhibits all mistakes, errors and flaws in the developed software. There are many approaches to software testing, but effective testing of complex product is essentially a process of investigation, not merely a matter of creating and following route procedure. It is not possible to find out all the errors in the program. This fundamental problem in testing thus throws an open question, as to what would be the strategy we should adopt for testing. In our paper, we have described and compared the three most prevalent and commonly used software testing techniques for detecting errors, they are: white box testing, black box testing and grey box testing.

Different Approaches To Black box Testing Technique For Finding Errors

Software testing is the process of analyzing software to find the difference between required and existing condition. Software testing is performed throughout the development cycle of software and it is also performed to build quality software, for this purpose two basic testing approaches are used, they are white box testing and black box testing. One of the software testing technique which I have explain in my paper is Black Box Testing, it is a method of generating test cases that are independent of software internal structure, I have also briefly explore various different approaches to black box testing technique for finding errors. Since black box testing is always based either directly or indirectly on the software specification so it is also called specification based testing.

AN OCL-BASED APPROACH TO DERIVE CONSTRAINT TEST CASES FOR DATABASE APPLICATIONS

The development of database applications in most CASE tools has been insufficient because most of these tools do not provide the software necessary to validate these applications. Validation means ensuring whether a given application fulfils the user requirements. We suggest validation of database applications by using the functional testing technique, which is a fundamental black-box testing technique for checking the software without being concerned about its implementation and structure. Our main contribution to this work is in providing a MDA approach for deriving testing software from the OCL specification of the integrity constraints. This testing software is used to validate the database applications, which are used to enforce these constraints. The generated testing software includes three components: validation queries, test cases and initial data inserted before the testing process. Our approach is implemented as an add-in tool in Rational Rose called OCL2TestSW.

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.

Construction of classification trees via the classification-hierarchy table

The classification-tree method developed by Grochtmann and coworkers is a black box testing technique to assist test engineers to construct test cases systematically from the functional specifications, via the construction of classification trees. This paper supplements their studies by proposing a methodology to construct classification trees systematically from given sets of classifications and their associated classes, via the notion of the classification-hierarchy table. The intuition of the classification-hierarchy table is to capture the hierarchical relationship for every pair of distinct classifications from which classification trees can be constructed.

Linking requirements and design data for automated functional evaluation

This paper presents a methodology for automating the evaluation of complex hierarchical designs using black-box testing techniques. Based on an exploration model for design, this methodology generates evaluation tests using a novel semantic graph data model which captures the relationships between the related design and requirements data. Using these relationships, equivalent tests are generated and systematically applied to simulations of the pieces of a modular design and its requirements. These simulations yield two sets of comparable results, enabling evaluation of partial designs of a complex system early in their design process.

Performing data flow testing on classes

The basic unit of testing in an object-oriented program is a class. Although there has been much recent research on testing of classes, most of this work has focused on black-box approaches. However, since black-box testing techniques may not provide sufficient code coverage, they should be augmented with code-based or white-box techniques. Dataflow testing is a code-based testing technique that uses the dataflow relations in a program to guide the selection of tests. Existing dataflow testing techniques can be applied both to individual methods in a class and to methods in a class that interact through messages, but these techniques do not consider the dataflow interactions that arise when users of a class invoke sequences of methods in an arbitrary order. We present a new approach to class testing that supports dataflow testing for dataflow interactions in a class. For individual methods in a class, and methods that send messages to other methods in a the class, our technique is similar to existing dataflow testing techniques. For methods that are accessible outside the class, and can be called in any order by users of the class, we compute dataflow information, and use it to test possible interactions between these methods. The main benefit of our approach is that it facilitates dataflow testing for an entire class. By supporting dataflow testing of classes, we provide opportunities to find errors in classes that may not be uncovered by black-box testing. Our technique is also useful for determining which sequences of methods should be executed to test a class, even in the absence of a specification. Finally, as with other code-based testing techniques, a large portion of our technique can be automated.

APPLYING CONVENTIONAL UNIT TESTING TECHNIQUES TO ABSTRACT DATA TYPE OPERATIONS

Abstract data types (ADTs) represent the fundamental building blocks of object-oriented software development. There have been a variety of techniques in the literature for testing ADT modules. Virtually all of the proposed techniques have involved testing sequences of ADT operations (e.g., for a stack ADT, test the sequence PUSH; PUSH; POP) to discover defects in their interactions. However, the operations inside an ADT module are really nothing more than conventional procedures and functions. Consequently, it is conceivable that conventional subprogram unit testing techniques can be adapted to test ADT operations. To support such testing techniques, test cases are best designed and expressed in terms of data values. When test cases are integers, for example, expressing a test case is trivial (e.g., ‘253’). However, when test cases are data abstractions (such as stacks), this problem is much more difficult due to the variety of different formats in which a single data abstraction can be legitimately viewed. In this paper, we provide a conceptual framework for applying classical white-box and black-box unit testing techniques to ADT operations. We then use this framework to develop a collection of guidelines for determining the best format for test case design, given different module characteristics and testing techniques.

PRAGMATIC TESTING METHODS FOR EXPERT SYSTEMS

Effective testing of expert systems is an important but difficult task. In this paper we discuss why testing of expert systems is hard. For testing expert systems, testing techniques from conventional software engineering are adapted as a solution to these problems. We discuss the feasibility and application of black-box, white-box, and life-cycle testing techniques to expert systems. Black-box techniques include random, input partition and output partition testing. White-box techniques include path based partition, cause-effect graph, dynamic-flow, data-flow, and ablation testing. The use of these methods is demonstrated by applying the techniques to an industrial expert system. The results obtained are 1) random testing is feasible for expert systems with a small input space, 2) effectiveness of partition testing depends on the partition criteria, however, partition testing points out failure-prone partitions, 3) cause-effect testing is suitable for large expert systems if it is well decomposed, 4) dynamic-flow testing depends on the number of paths in solution and design specifications, 5) data-flow testing is feasible only if define-use pairs are obtained automatically, 6) ablation testing helps in pointing out discrepancies between specification and implementation. The overall result is that the expert systems can be treated as any other software and all the conventional software engineering testing techniques can be used to test expert systems.

Testing object-oriented software (abstract)

Testing of object-oriented software is just as important as testing non-object-oriented software, but the process is fundamentally different because of such factors as information hiding, encapsulation, and inheritance. This tutorial teaches you the terms and concepts of testing software in general, and object-oriented software in particular; how to apply a number of different testing techniques to object-oriented software; how to construct test cases; and an appreciation of what is involved in planning a successful software testing effort. The testing techniques that are covered include both white-box testing such as basis path testing and coverage testing, and black-box testing techniques such as equivalence class partitioning and boundary value analysis. This course is designed for those with experience in object-oriented software engineering who would like to follow a more rigorous approach to testing.