Automated cost-effective test strategies are needed to provide reliable, secure, and usable Web applications. As a software maintainer updates an application, test cases must accurately reflect usage to expose faults that users are most likely to encounter. User-session-based testing is an automated approach to enhancing an initial test suite with real user data, enabling additional testing during maintenance as well as adding test data that represents usage as operational profiles evolve. Test suite reduction techniques are critical to the cost effectiveness of user-session-based testing because a key issue is the cost of collecting, analyzing, and replaying the large number of test cases generated from user-session data. We performed an empirical study comparing the test suite size, program coverage, fault detection capability, and costs of three requirements-based reduction techniques and three variations of concept analysis reduction applied to two Web applications. The statistical analysis of our results indicates that concept analysis-based reduction is a cost-effective alternative to requirements-based approaches.

Low reliability in Web-based applications can result in detrimental effects for business, government, and consumers as they become increasingly dependent on the Internet for routine operations. A short time to market, large user community, demand for continuous availability, and frequent updates motivate automated, cost-effective testing strategies. To investigate the practical tradeoffs of different automated strategies for key components of the Web-based software testing process, we have designed a framework for Web-based software testing that focuses on scalability and evolving the test suite automatically as the application's operational profile changes. We have developed an initial prototype that not only demonstrates how existing tools can be used together but provides insight into the cost effectiveness of the overall approach. This paper describes the testing framework, discusses the issues in building and reusing tools in an integrated manner, and presents a case study that exemplifies the usability, costs, and scalability of the approach.

Many different testing techniques have been proposed by researchers, but essentially only two main testing philosophies exist, black box and white box. There exist a number of different testing methods for structural testing of procedural languages. However, the features of object-oriented languages are not addressed by such techniques. The article explores a new structural testing technique for object-oriented systems by developing a testing methodology based on object manipulations and driven by the context of the program under test.

Often the code regions that are assigned for a maintenance task do not follow the modularization of the original application program, but instead include parts of code from many different units scattered throughout the application. In this paper, we investigate an approach to testing which we call concern-based testing, which leverages existing tools to help software maintainers identify the relevant code for their assigned task, their concern. The main contribution is a demonstration of the possible savings in test suite execution overhead and the increased precision in coverage information that can be obtained for a software maintainer if testing tasks are performed with respect to concerns. Based on a concern graph representation of the concern, a framework for guiding selective instrumentation for scalable coverage analysis is also presented.

This paper describes a program representation and algorithms for realizing a novel structural testing methodology that not only focuses on addressing the complex features of object-oriented languages, but also incorporates the structure of object-oriented software into the approach. The testing methodology is based on the construction of contextual def-use associations, which provide context to each definition and use of an object. Testing based on contextual def-use associations can provide increased test coverage by identifying multiple unique contextual def-use associations for the same context-free association. Such a testing methodology promotes more thorough and focused testing of the manipulation of objects in object-oriented programs. This paper presents a technique for the construction of contextual def-use associations, as well as detailed examples illustrating their construction, an analysis of the cost of constructing contextual def-use associations with this approach, and a description of a prototype testing tool that shows how the theoretical contributions of this work can be useful for structural test coverage.

Developed primarily for optimization of functional and object-oriented software, escape analysis discerns information to determine whether the lifetime of data exceeds its static scope. We demonstrate how to apply escape analysis to software engineering tasks. In particular we present novel software testing and retesting techniques for object-oriented software which utilize escape analysis. We exploit a combined pointer and escape analysis that is able to identify how individual objects allocated in one region of a program interact with other regions of a program. The analysis framework increases flexibility and scalability as testing coverage can be targeted to a specific arbitrary region of a program, followed by integration testing that can be focused on particular sets of objects escaping the region. We demonstrate how regression testing can be performed utilizing this framework. We believe such a flexible framework becomes increasingly beneficial as applications become more component-oriented.

A program's call graph is an essential underlying structure for performing the various interprocedural analyses used in software development tools for object-oriented software systems. For interactive software development tools and software maintenance activities, the call graph needs to remain fairly precise and be updated quickly in response to software changes. The paper presents incremental algorithms for updating a call graph that has been initially constructed using the Cartesian Product Algorithm, which computes a highly precise call graph in the presence of dynamically dispatched message sends. Templates are exploited to reduce unnecessary reanalysis as software component changes occur. The preliminary empirical results from our implementation within a Java environment are encouraging. Significant time savings were observed for the incremental algorithm in comparison with an exhaustive analysis, with no loss in precision.

This paper presents a novel formulation of definitions, uses, and def-use associations for objects in object-oriented programs by exploiting the relations that occur between classes and their instantiated objects due to aggregation. Contextual def-use associations are computed by generating a partial call sequence for each def and use based on object aggregation relations. By extending an escape points-to graph representation of the program, we have developed and implemented three strategies for achieving different levels of context for contextual def-use associations. Our experiments reveal that with all three strategies, multiple unique contextual def-use associations related to the same traditional (context-free) association are often generated. Contextual def-use associations are particularly useful for increasing test coverage and focusing the testing on critical method invocation sequences of object-oriented programs.

This paper presents a strategy for structural testing of object-oriented software systems with possibly unknown clients and unknown information about invoked methods. By exploiting the combined points-to and escape analysis developed for compiler optimization, our testing paradigm does not require a whole program representation to be in memory simultaneously for testing analysis. Potential effects from outside the component under test are easily identified and reported to the tester. As client and server methods become known, the graph representation of object relationships is easily extended, allowing the computation of test tuples to be performed in a demand-driven manner, without requiring unnecessary computation of test tuples based on predictions of potential clients.

Object-oriented program design promotes the reuse of code not only through inheritance and polymorphism, but also through building server classes which can be used by many different client classes. Research on static analysis of object-oriented software has focused on addressing the new features of classes, inheritance, polymorphism, and dynamic binding. This paper demonstrates how exploiting the nature of object-oriented design principles can enable development of scalable static analyses. We present an algorithm for computing def-use information for a single class's manipulation of objects of other classes, which requires that only partial representations of server classes be constructed. This information is useful for data flow testing and debugging.

One significant challenge in bringing the power of parallel machines to application programmers is providing them with a suite of software tools similar to the tools that sequential programmers currently utilize. In particular, automatic or semi-automatic testing tools for parallel programs are lacking. This paper describes our work in automatic generation of all-du-paths for testing parallel programs. Our goal is to demonstrate that, with some extension, sequential test data adequacy criteria are still applicable to parallel program testing. The concepts and algorithms in this paper have been incorporated as the foundation of our DELaware PArallel Software Testing Aid, della pasta.