27 research outputs found
Design and Implementation of a Tracer Driver: Easy and Efficient Dynamic Analyses of Constraint Logic Programs
Tracers provide users with useful information about program executions. In
this article, we propose a ``tracer driver''. From a single tracer, it provides
a powerful front-end enabling multiple dynamic analysis tools to be easily
implemented, while limiting the overhead of the trace generation. The relevant
execution events are specified by flexible event patterns and a large variety
of trace data can be given either systematically or ``on demand''. The proposed
tracer driver has been designed in the context of constraint logic programming;
experiments have been made within GNU-Prolog. Execution views provided by
existing tools have been easily emulated with a negligible overhead.
Experimental measures show that the flexibility and power of the described
architecture lead to good performance. The tracer driver overhead is inversely
proportional to the average time between two traced events. Whereas the
principles of the tracer driver are independent of the traced programming
language, it is best suited for high-level languages, such as constraint logic
programming, where each traced execution event encompasses numerous low-level
execution steps. Furthermore, constraint logic programming is especially hard
to debug. The current environments do not provide all the useful dynamic
analysis tools. They can significantly benefit from our tracer driver which
enables dynamic analyses to be integrated at a very low cost.Comment: To appear in Theory and Practice of Logic Programming (TPLP),
Cambridge University Press. 30 pages
Debugging Trait Errors as Logic Programs
Rust uses traits to define units of shared behavior. Trait constraints build
up an implicit set of first-order hereditary Harrop clauses which is executed
by a powerful logic programming engine in the trait system. But that power
comes at a cost: the number of traits in Rust libraries is increasing, which
puts a growing burden on the trait system to help programmers diagnose errors.
Beyond a certain size of trait constraints, compiler diagnostics fall off the
edge of a complexity cliff, leading to useless error messages. Crate
maintainers have created ad-hoc solutions to diagnose common domain-specific
errors, but the problem of diagnosing trait errors in general is still open. We
propose a trait debugger as a means of getting developers the information
necessary to diagnose trait errors in any domain and at any scale. Our proposed
tool will extract proof trees from the trait solver, and it will interactively
visualize these proof trees to facilitate debugging of trait errors.Comment: 9 pages, 2 figure
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The uses of process modeling : a framework for understanding modeling formalisms
There is wide-spread recognition of the urgent need to improve software processes in order to improve the performance of software organizations. Process models are essential in achieving understanding and visibility of processes and are important for other uses including the analysis of processes for improvement. It has been increasingly difficult to compare and evaluate the variety of process modeling formalisms that have appeared in recent years without a clear understanding of precisely for what they will be used. The contribution of this paper is to provide an understanding and a fairly comprehensive catalog of the applications of process modeling for which formalisms may be used. The primary mechanism for doing this is a guided tour of the literature on process modeling supplemented by recent industrial experience. In the paper, basic definitions concerning processes, process descriptions and process modeling are reviewed and then uses of process modeling are surveyed under the following headings: communication among process participants, construction of new processes, control of processes, process· analysis, and process support by automation. Comments are offered on paradigms for process modeling formalisms and directions for future work to permit evolution of a discipline of process engineering are given
PECCit: An Omniscient Debugger for Web Development
Debugging can be an extremely expensive and time-consuming task for a software developer. To find a bug, the developer typically needs to navigate backwards through infected states and symptoms of the bug to find the initial defect. Modern debugging tools are not designed for navigating back-in-time and typically require the user to jump through hoops by setting breakpoints, re-executing, and guessing where errors occur. Omniscient debuggers offer back-in-time debugging capabilities to make this task easier. These debuggers trace the program allowing the user to navigate forwards and backwards through the execution, examine variable histories, and visualize program data and control flow. Presented in this thesis is PECCit, an omniscient debugger designed for backend web development. PECCit traces web frameworks remotely and provides a browser-based IDE to navigate through the trace. The user can even watch a preview of the web page as it\u27s being built line-by-line using a novel feature called capturing. To evaluate, PECCit was used to debug real-world problems provided by users of two Content Management Systems: WordPress and Drupal. In these case studies, PECCit\u27s features and debugging capabilities are demonstrated and contrasted with standard debugging techniques
Modular Collaborative Program Analysis
With our world increasingly relying on computers, it is important to ensure the quality, correctness, security, and performance of software systems. Static analysis that computes properties of computer programs without executing them has been an important method to achieve this for decades. However, static analysis faces major chal-
lenges in increasingly complex programming languages and software systems and increasing and sometimes conflicting demands for soundness, precision, and scalability. In order to cope with these challenges, it is necessary to build static analyses for complex problems from small, independent, yet collaborating modules that can be developed in isolation and combined in a plug-and-play manner.
So far, no generic architecture to implement and combine a broad range of dissimilar static analyses exists. The goal of this thesis is thus to design such an architecture and implement it as a generic framework for developing modular, collaborative static analyses. We use several, diverse case-study analyses from which we systematically derive requirements to guide the design of the framework. Based on this, we propose the use of a blackboard-architecture style collaboration of analyses that we implement in the OPAL framework. We also develop a formal model of our architectures core concepts and show how it enables freely composing analyses while retaining their soundness guarantees.
We showcase and evaluate our architecture using the case-study analyses, each of which shows how important and complex problems of static analysis can be addressed using a modular, collaborative implementation style. In particular, we show how a modular architecture for the construction of call graphs ensures consistent soundness of different algorithms. We show how modular analyses for different aspects of immutability mutually benefit each other. Finally, we show how the analysis of method purity can benefit from the use of other complex analyses in a collaborative manner and from exchanging different analysis implementations that exhibit different characteristics. Each of these case studies improves over the respective state of the art in terms of soundness, precision, and/or scalability and shows how our architecture enables experimenting with and fine-tuning trade-offs between these qualities