김윤호 교수

Finding the root cause of a bug requires a significant effort from developers. Automated fault localization techniques seek to reduce this cost by computing the suspiciousness scores (i.e., the likelihood of program entities being faulty). Existing techniques have been developed by utilizing input features of specific types for the computation of suspiciousness scores, such as program spectrum or mutation analysis results. This article presents a novel learn-to-rank fault localization technique

Current testing practice in industry is often ineffective and slow to detect bugs, since most projects utilize manually generated test cases. Concolic testing alleviates this problem by automatically generating test cases that achieve high coverage. However, specialized execution platforms and resource constraints of embedded software hinder application of concolic testing to embedded software. To overcome these limitations, we have developed CONcrete and symBOLic (CONBOL) testing framework to u

Current industrial testing practices often generate test cases in a manual manner, which degrades both the effectiveness and efficiency of testing. To alleviate this problem, concolic testing generates test cases that can achieve high coverage in an automated fashion. One main task of concolic testing is to extract symbolic information from a concrete execution of a target program at runtime. Thus, a design decision on how to extract symbolic information affects efficiency, effectiveness, and ap

As smartphones become popular, manufacturers such as Samsung Electronics are developing smartphones with rich functionality such as a camera and photo editing quickly, which accelerates the adoption of open source applications in the smartphone platforms. However, developers often do not know the detail of open source applications, because they did not develop the applications themselves. Thus, it is a challenging problem to test open source applications effectively in short time. This paper rep

As smartphones become popular, manufacturers such as Samsung Electronics are developing smartphones with rich functionality such as a camera and photo editing quickly, which accelerates the adoption of open source applications in the smartphone platforms. However, developers often do not know the detail of open source applications, because they did not develop the applications themselves. Thus, it is a challenging problem to test open source applications effectively in short time. This paper rep

Automated unit testing reduces manual effort to write unit test drivers/stubs and generate unit test inputs. However, automatically generated unit test drivers/stubs raise false alarms because they often over-approximate real contexts of a target function f and allow infeasible executions of f. To solve this problem, we have developed a concolic unit testing technique CONBRIO. To provide realistic context to f, it constructs an extended unit of f that consists of f and closely relevant functions

Concolic testing is popular in unit testing because it can detect bugs quickly in a relatively small search space. But, in system-level testing, it suffers from the symbolic path explosion and often misses bugs. To resolve this problem, we have developed a focused compositional concolic testing technique, FOCAL, for effective bug detection. Focusing on a target unit failure v (a crash or an assert violation) detected by concolic unit testing, FOCAL generates a system-level test input that valida

Test suite augmentation techniques generate test cases to cover code missed by existing regression test suites. Various augmentation techniques have been proposed, utilizing several test case generation algorithms. Research has shown that different algorithms have different strengths, and that combining them into a single hybrid approach may be cost-effective. In this paper we present a framework for hybrid test suite augmentation that allows test case generation algorithms to be interleaved dyn

The importance of automotive software has been rapidly increasing because software now controls many components in motor vehicles such as window controller, smart-key system, and tire pressure monitoring system. Consequently, the automotive industry spends a large amount of human effort testing automotive software and is interested in automated software testing techniques that can ensure high-quality automotive software with reduced human effort. In this paper, we report our industrial experienc

Software testing techniques have advanced significantly over several decades; however, most of current techniques still test a target program as it is, and fail to utilize valuable information of diverse test executions on many variants of the original program in test generation. This paper proposes a new direction for software testing - Invasive Software Testing (IST). IST first generates a set of target program variants m <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://

For autonomous quadruped robot navigation in various complex environments, a typical SOTA system is composed of four main modules -mapper, global planner, local planner, and command-tracking controller -in a hierarchical manner. In this paper, we build a robust and safe local planner which is designed to generate a velocity plan to track a coarsely planned path from the global planner. Previous works used waypointbased methods (e.g. Proportional-Differential control and pure pursuit) which simpl

Summary Most software testing techniques test a target program as it is and fail to utilize valuable information of diverse test executions on many variants/mutants of the original program in test generation. This paper proposes a new test generation technique DEMINER , which utilizes mutant executions to guide test generation on the original program for high test coverage. DEMINER first generates various mutants of an original target program and then extracts runtime information of mutant execu

Current industrial testing practices often build test cases in a manual manner, which degrades both the effectiveness and efficiency of testing. To alleviate this problem, concolic testing generates test cases that can achieve high coverage in an automated fashion. This paper describes case studies of applying concolic testing to mobile platform C programs that have been developed by Samsung Electronics. Through this work, we have detected new faults in the Samsung Linux Platform (SLP) file mana