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My current research in software engineering tackles two general problems: the difficulties arising from tangling of concerns in code and the difficulties of automated testing. In the past I have performed research in software development methods and applied formal methods, and have made contributions to the field of reliability engineering.
In the area of separation of concerns, much research has focused on the development of programming language abstractions for separating concerns by encapsulating them. Examples include procedures, classes, and more recently aspects and hyperspaces. As successful as these approaches are, they are ineffective at encapsulating concerns that interact with the remainder of the code in idiosyncratic ways. An example of such a concern is debugging code, which is highly context-dependent and nonuniform in its integration with surrounding code.
My research approaches this problem in a radically different way. Rather than seeking to refactor such tightly coupled concerns into new modules, I seek to provide the programmer with tools needed to manage the tangling and interaction of concerns. The approach, which I call software plans, provides the programmer with multiple concern-oriented views of a module in much the same say that an architect would work with multiple plans for a building. This work represents a significant departure from the previous language-based approaches, exploring an editor-based approach instead.
In the area of software testing, my research has focused on lowering the cost of testing through automation. Traditional testing approaches such as partition testing can be effective, but scale poorly because of the labor-intensive nature of selecting representative inputs and validating outputs. At the same time, there has been both theoretical and empirical research that demonstrates that partition testing can be less effective than even random testing.
My research seeks to establish the utility of less labor-intensive testing strategies, and to provide tools supporting the generation of structurally-complex test data. My work in bounded exhaustive testing has shown that through automation one can test millions of cases, revealing significant faults that were missed by traditional testing strategies. In other work, I have investigated the automatic generation of complex test data such as well-formed web pages, and the automatic generation of implicitly-defined inputs such as those that result in high memory usage.
My previous PhD work sought to improve the state of the art in the development of software supporting more traditional engineering disciplines such as reliability engineering. I developed an approach for developing engineering tools having high usability, functionality, and trustworthiness at low cost. The key was to combine the use of mass-market applications as components for the user interface with the judicious use of formal methods for the analysis core. In working closely with reliability engineers, I also found opportunities to apply concepts from software engineering and programming languages to problems in their field, making some modest contributions.
The next two sections describe my current research in software plans and bounded exhaustive testing. The next section describes my previous work in software development methods. I conclude with my future research agenda.
For thirty years computer scientists have struggled with the complexity of software, developing new abstractions for achieving separation of concerns through encapsulation. This approach is most successful when concerns interact in narrow, well-defined ways. Unfortunately, many concerns (such as debugging tracing) exhibit complex tangling that is difficult to specify in a manner amenable to automated integration by a compiler. As a result, such concerns are usually left tangled in the code, increasing the difficulties of software development and maintenance.
My research tackles this problem in a novel way—instead of separating concerns by refactoring them into new modules, I treat a module as a multidimensional representation of the concerns that it implements. That is, instead of a single flat code representation, my work in an area I call software plans represents a module as a set of inter-related, concern-oriented views. A software plan is an editable view of a module that presents the relevant subset of the code for the concern being implemented.
This work has the potential to create a new direction for research in separation of concerns in code. My recent work has focused on laying the foundation for more significant advances in this area. For example, we developed a new code representation for software plans, implemented a prototype editor called Spotlight, and developed techniques for reverse-engineering software plans from existing code.
This work is supported by a $328K grant from the United States Air Force Office of Scientific Research. We are starting the second of three years of support.
Traditional testing involves partitioning the input space, selecting a representative, and then deriving the expected output or verifying the actual output. Selection of cases to test is driven by models of the correlation between faults and the design or implementation of the software. As effective as this approach can be, it suffers from a key problem: there is little empirical proof that the fault model is sufficient to reveal all important faults. That is, techniques such as code coverage may reveal unimportant faults while also missing important faults. Both empirical and theoretical research have shown, for example, that partition-based approaches can be worse than random testing if the partitioning is poor.
My research has investigated alternative automated testing strategies such as bounded exhaustive testing, where a subset of the program's input space is identified and all inputs within that space are tested. This approach is attractive because it places few assumptions on the distribution of fault-revealing inputs. In a study I conducted with colleagues at MIT and the University of Virginia, we showed the utility of the approach, revealing faults in a dynamic fault tree evaluation engine by testing millions of trees. We also developed techniques for scaling up the generation of inputs using model checking technologies.
This work also led me to further investigate the problems of automated input generation. In one effort, I developed a tool that takes as input a lex/yacc-style specification and generates a generator for strings in the language. Assuming a programmer uses lex and yacc to create a parser for the input, my tool allows them to use the input files to create a test data generator instead. In other work, a student and I developed an algorithm for automatically identifying the bounds of an "interesting" subset of the input space. We evaluated the algorithm by using it to generate and test near miss trajectories for an aircraft collision-avoidance algorithm.
This work was supported by a $55K subcontract with University of Virginia on a NASA grant. Unfortunately only $37K was disbursed due to NASA budget shortfalls.
If engineering is the application of science to the development of artifacts for the good of mankind, I believe that software engineering's best hope for leveraging science is to employ formal methods—mathematically-based tools, techniques and processes. As a graduate student, my research focused on finding cost-effective ways of employing formal methods for the construction of more reliable software. My primary application area was that of reliability engineering software, where engineers use domain-specific languages to create models and analyze them with respect to properties such as reliability over time.
In my interactions with engineers, I found that the languages they were developing were pushing the boundaries of their ability to specify their correct behavior. Further, the tools they developed lacked a level of usability and quality that users expect. My research addressed these challenges by combining component-based software development techniques and applied formal methods. Formal methods aid in the design and validation of the modeling language, and in the implementation of a trustworthy analysis library. Package-oriented programming, the use of mass-market applications as components, provides the features and usability of tools at low cost. To evaluate this approach, I applied it to an important modeling method, dynamic fault tree analysis. My work was a significant contribution to the Galileo tool used by space station engineers at NASA and now sold by Exelix, Inc.
In working closely with reliability engineers, I have also been able to make some modest contributions to the field of reliability engineering. This work has primarily focused on the utility of using formal specification languages to provide a denotational semantics for reliability modeling languages. More recent work has focused on demonstrating the utility of an intermediate reliability modeling language.
My future work will focus primarily on software plans and testing. Work on software plans is progressing on several fronts. We have recently developed a dynamic approach for reverse-engineering software plans from legacy code and plan to improve the approach by adding static analysis. The software plans approach makes manifest feature interactions that occur in software. We hope to develop analyses for automatically detecting some classes of feature interaction and helping the programmer to resolve them. In other work, we are augmenting our existing lexical code representation with program semantics in order to ease the integration of separately developed software plans. All of these activities and more are supported by an Air Force grant.
With regard to testing, short-term plans include implementing recent optimizations developed in the model checking in my input generation tool. These can potentially improve the generation efficiency by several orders of magnitude. In longer-term work, I plan to create a database of programs, operational profiles, and fault-revealing inputs. Much research in software testing is hampered by our inability to rapidly and quantitatively evaluate testing strategies. By creating such a repository for the public, researchers will have a common benchmark for comparing testing strategies, including their effect on overall program reliability.
Nearly all of my work to date has involved graduate and undergraduate collaborators. I plan to continue to involve students, as well as to continue to establish collaborations with people outside, and hopefully within my department.
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Last changed October 24 2007 22:47:21.
David Coppit,
coppit@cs.wm.edu
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