Program slicing is a method for automatically decomposing programs by analyzing their data flow and control flow. Starting from a subset of a program's behavior, slicing reduces that program to a minimal form which still produces that behavior. The reduced program, called a ``slice,'' is an independent program guaranteed to represent faithfully the original program within the domain of the specified subset of behavior. Some properties of slices are presented. In particular, finding statement-minimal slices is in general unsolvable, but using data flow analysis is sufficient to find approximate slices. Potential applications include automatic slicing tools for debuggng and parallel processing of slices.

Program Slicing

Experience from a dozen years of analyzing software engineering processes and products is summarized as a set of software engineering and measurement principles that argue for software engineering process models that integrate sound planning and analysis into the construction process. In the TAME (Tailoring A Measurement Environment) project at the University of Maryland, such an improvement-oriented software engineering process model was developed that uses the goal/question/metric paradigm to integrate the constructive and analytic aspects of software development. The model provides a mechanism for formalizing the characterization and planning tasks, controlling and improving projects based on quantitative analysis, learning in a deeper and more systematic way about the software process and product, and feeding the appropriate experience back into the current and future projects. The TAME system is an instantiation of the TAME software engineering process model as an ISEE (integrated software engineering environment). The first in a series of TAME system prototypes has been developed. An assessment of experience with this first limited prototype is presented including a reassessment of its initial architecture. >

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The TAME project: towards improvement-oriented software environments

Objective measurement of test quality is one of the key issues in software testing. It has been a major research focus for the last two decades. Many test criteria have been proposed and studied for this purpose. Various kinds of rationales have been presented in support of one criterion or another. We survey the research work in this area. The notion of adequacy criteria is examined together with its role in software dynamic testing. A review of criteria classification is followed by a summary of the methods for comparison and assessment of criteria.

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Software unit test coverage and adequacy

An effective data collection method for evaluating software development methodologies and for studying the software development process is described. The method uses goal-directed data collection to evaluate methodologies with respect to the claims made for them. Such claims are used as a basis for defining the goals of the data collection, establishing a list of questions of interest to be answered by data analysis, defining a set of data categorization schemes, and designing a data collection form. The data to be collected are based on the changes made to the software during development, and are obtained when the changes are made. To ensure accuracy of the data, validation is performed concurrently with software development and data collection. Validation is based on interviews with those people supplying the data. Results from using the methodology show that data validation is a necessary part of change data collection. Without it, as much as 50 percent of the data may be erroneous. Feasibility of the data collection methodology was demonstrated by applying it to five different projects in two different environments. The application showed that the methodology was both feasible and useful.

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A Methodology for Collecting Valid Software Engineering Data

Extensively class tested, this text takes an innovative approach to explaining the process of software testing: it defines testing as the process of applying a few well-defined, general-purpose test criteria to a structure or model of the software. The structure of the text directly reflects the pedagogical approach and incorporates the latest innovations in testing, including techniques to test modern types of software such as OO, web applications, and embedded software.

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Introduction to Software Testing

A compiler-based system DAISTS that combines a data-abstraction implementation language (derived from the SIMULA class) with specification by algebraic axioms is described. The compiler, presented with two independent syntactic objects in the axioms and implementing code, compiles a \"program\" that consists of the former as test driver for the latter. Data points, in the form of expressions using the abstract functions and constant values, are fed to this program to determine if the implementation and axioms agree. Along the way, structural testing measures can be applied to both code and axioms to evaluate the test data. Although a successful test does not conclusively demonstrate the consistency of axioms and code, in practice the tests are seldom successful, revealing errors. The advantage over conventional programming systems is threefold:

Data Abstraction, Implementation, Specification, and Testing

It is demonstrated how model checking can be used to verify safety properties for event-driven systems. SCR tabular requirements describe required system behavior in a format that is intuitive, easy to read, and scalable to large systems (e.g. the software requirements for the A-7 military aircraft). Model checking of temporal logics has been established as a sound technique for verifying properties of hardware systems. An automated technique for formalizing the semiformal SCR requirements and for transforming the resultant formal specification onto a finite structure that a model checker can analyze has been developed. This technique was effective in uncovering violations of system invariants in both an automobile cruise control system and a water-level monitoring system. >

State-based model checking of event-driven system requirements

Principles of software engineering and design

The language in which programs are written can have a substantial effect on the reliability of the resulting programs. This paper discusses an experiment that compares the programming reliability of subjects using a statically typed language and a “typeless” language. Analysis of the number of errors and the number of runs containing errors shows that, at least in one environment, the use of a statically typed language can increase programming reliability. Detailed analysis of the errors made by the subjects in programming solutions to reasonably small problems shows that the subjects had difficulty manipulating the representation of data.

An experimental evaluation of data type conventions

The language in which programs are written can have a substantial effect on their reliability. This paper discusses the design of programming languages to enhance reliability. It presents several general design principles, and then applies them to particular languages constructs. Since the validity of such design principles cannot be logically proved, empirical evidence is needed to support or discredit them. A major experiment to measure the effect of nine specific language-design decisions in one context has been performed. Analysis of the frequency and persistence of errors shows that several decisions had a significant impact on reliability.

J. D. Gannon

Papers

Data Abstraction, Implementation, Specification, and Testing

State-based model checking of event-driven system requirements

Principles of software engineering and design

An experimental evaluation of data type conventions

Language design for programming reliability