Symbolic execution is one of the most powerful tools in static analysis for finding bugs. In this technique the source code is not executed by the CPU, but interpreted statement-by-statement by preserving their semantics as much as possible. During the interpretation the possible values of variables are recorded so the analyzer can report when a variable gets to an invalid state. An additional benefit of such a provided bug report is that not only the place of the bug is returned but the control flow is also displayed which results the erroneous program state. Many times the bug path contains statements which are not related to the bug. These irrelevant statements make it harder to understand in the debugging process, how the error can occu...
We introduce a novel technique for checking properties described by finite state machines. The techn...
Bug fix is an important and challenging task in software development and maintenance. Bug fix is als...
University of Minnesota Ph.D. dissertation. 2021. Major: Computer Science. Advisor: Stephen McCamant...
Although they are helpful in many cases, state-of-the-art bug reporting systems may impose excessive...
This paper reports on our experience implementing a technique for sifting through static analysis re...
<p>Over the past 20 years, our society has become increasingly dependent on software. Today, we rely...
Symbolic execution is a powerful program analysis technique that systematically explores multiple pr...
Abstract. Safety-critical software in industry is typically subjected to both dy-namic testing as we...
Software testing is an indispensable part of the soft-ware development process. Mutation analysis is...
There has been a large body of work on local reasoning for proving the absence of bugs, but none for...
We present an algorithm for tests generation tools based on symbolic execution. The algorithm is sup...
textThe last few years have seen a resurgence of interest in the use of symbolic execution--program ...
Coverage-based fuzz testing and dynamic symbolic execution are both popular program testing techniqu...
This work proposes new combinations of static and dynamic analysis for bug detection and program und...
Fuzzing, a technique for negative testing of programs using randomly mutated or gen?erated input dat...
We introduce a novel technique for checking properties described by finite state machines. The techn...
Bug fix is an important and challenging task in software development and maintenance. Bug fix is als...
University of Minnesota Ph.D. dissertation. 2021. Major: Computer Science. Advisor: Stephen McCamant...
Although they are helpful in many cases, state-of-the-art bug reporting systems may impose excessive...
This paper reports on our experience implementing a technique for sifting through static analysis re...
<p>Over the past 20 years, our society has become increasingly dependent on software. Today, we rely...
Symbolic execution is a powerful program analysis technique that systematically explores multiple pr...
Abstract. Safety-critical software in industry is typically subjected to both dy-namic testing as we...
Software testing is an indispensable part of the soft-ware development process. Mutation analysis is...
There has been a large body of work on local reasoning for proving the absence of bugs, but none for...
We present an algorithm for tests generation tools based on symbolic execution. The algorithm is sup...
textThe last few years have seen a resurgence of interest in the use of symbolic execution--program ...
Coverage-based fuzz testing and dynamic symbolic execution are both popular program testing techniqu...
This work proposes new combinations of static and dynamic analysis for bug detection and program und...
Fuzzing, a technique for negative testing of programs using randomly mutated or gen?erated input dat...
We introduce a novel technique for checking properties described by finite state machines. The techn...
Bug fix is an important and challenging task in software development and maintenance. Bug fix is als...
University of Minnesota Ph.D. dissertation. 2021. Major: Computer Science. Advisor: Stephen McCamant...