Kai-Hsiung Chang

A rule-based software test data generator

Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further. >

On computer supported collaborative writing tools for distributed environments

Traditional computerized writing tools designed for single user access often create barriers to group collaboration. Usually, participants have to work in an interleaved fashion to prevent inconsistency. Oral communication is normally used for coordinating group activities. With the recent development of computer networks and widespread deployment of networked workstations, automating the group writing process for geographically distributed users has become feasible. This paper introduces a Distributed Collaborative Writing Aid (DCWA) developed for networked workstations. The DCWA can help users cooperate on a writing task (such as programming, report writing, note taking, etc.) logically, conveniently , and efficiently. Among many important open problems, the paper addresses issues related to the four major components in the DCWA. These are group organization, multicasting within groups, distributed database, and user interface.

A heuristic approach for test case generation

Test case 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 expended becomes unacceptably large. A rule-based framework that will automatically generate test data to achieve maximal branch coverage is presented. The rationale of the heuristic rules and the strategy for the test case generation are also described. The result of this approach shows its potential for improving software testing. The rule-based approach allows this framework to be extended to include additional testing requirements and test case generation knowledge.

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.

An agent-oriented multiagent planning system

this paper describes a multiagent planning system, MuPAC, that formulates cooperative plans efficiently. It contains three features: meta-level planning, breakable and unbreakable action representations, and an integrated agent screening and assignment procedure. The meta-level planning transforms an original goal statement into a skeletal plan, which is easier to follow and helps reduce the chance of conflicts at low-level actions. The breakable/unbreakable action representation specifies specific agent-action requirements. It also specifies concurrency and cooperation possibilities among actions. It makes plan generation and agent assignment straight forward, thus reducing the reasoning time of finding parallelism and cooperation among agents. The integrated agent screening and assignment procedure formulates plans following the skeletal plan. The performance of MuPAC has been discussed along four aspects: planning efficiency, planning flexibility, agent cooperation, and plan quality. Results have shown that significant improvement has been achieved.

Expert system assisted test data generation for software branch coverage

Abstract 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.

Software Safety Issues For The Space Station Flight Telerobotic Servicer

NASA has committed to the design and implementation of a Space Station Flight Telerobotic Servicer (FTS) to assist the astronauts in assembly, maintenance, servicing, and inspection tasks on the Space Station and the Space Shuttle. One of the requirements of the FTS is safety. Safety is not solely dependent on the visible hardware components such as manipulators and hydraulic systems. It is also dependent on the underlying software which controls every action of these hardware components. An acceptable level of safety can only be reached by analyzing and implementing safety issues through the conceptualization, design, construction, and operation phases of the FTS. This article discusses three issues that are critical to the FTS safety. These include software design philosophy, software operating models, and a safety subsystem.

Software safety for the space station flight telerobotic servicer (FTS)

Abstract Chang, K.-H. and Cross, J.H., 1988. Software safety for the space station flight telerobotic servicer (FTS). Journal of Occupational Accidents, 10: 179–189. NASA has committed to the design and implementation of a Space Station Flight Telerobotic Servicer (FTS) to assist the astronauts in assembly, maintenance, servicing, and inspection tasks on the Space Station and the Space Shuttle. One of the major requirements of FTS is safety. An acceptable level of safety can only be reached by analyzing and implementing safety issues through the conceptualization, design, construction, and operation phases of the FTS. This safety requirement is not solely dependent on the visible hardware components such as manipulators and hydraulic systems. It is also dependent on the underlying software which controls every action of these hardware components. This article discusses three issues that are crucial to robot software safety. These issues include software design philosophy, software operation modes, and a safety subsystem.