67,136 research outputs found
SAT-based Automatic Test Pattern Generation
Due to the rapidly growing size of integrated circuits, there is a need for new algorithms for Automatic Test Pattern Generation (ATPG). While classical algorithms reach their limit, there have been recent advances in algorithms to solve Boolean Satisfiability (SAT). Because Boolean SAT solvers are working on Conjunctive Normal Forms (CNF), the problem has to be transformed. During transformation, relevant information about the problem might get lost and therefore is not available in the solving process.
In the following we briefly motivate the problem and provide the latest developments in the field. The technique was implemented and experimental results are presented. The approach was combined with the ATPG framework of NXP Semiconductors. Significant improvements in overall performance and
robustness are demonstrated
SAT-based Automatic Test Pattern Generation
Abstract. Due to the rapidly growing size of integrated circuits, there is a need for new algorithms for Automatic Test Pattern Generation (ATPG). While classical algorithms reach their limit, there have been recent advances in algorithms to solve Boolean Satisfiability (SAT). Because Boolean SAT solvers are working on Conjunctive Normal Forms (CNF), the problem has to be transformed. During transformation, relevant information about the problem might get lost and therefore is not available in the solving process. In the following we briefly motivate the problem and provide the latest developments in the field. The technique was implemented and experimental results are presented. The approach was combined with the ATPG framework of NXP Semiconductors. Significant improvements in overall performance and robustness are demonstrated
A Comprehensive Test Pattern Generation Approach Exploiting SAT Attack for Logic Locking
The need for reducing manufacturing defect escape in today's safety-critical
applications requires increased fault coverage. However, generating a test set
using commercial automatic test pattern generation (ATPG) tools that lead to
zero-defect escape is still an open problem. It is challenging to detect all
stuck-at faults to reach 100% fault coverage. In parallel, the hardware
security community has been actively involved in developing solutions for logic
locking to prevent IP piracy. Locks (e.g., XOR gates) are inserted in different
locations of the netlist so that an adversary cannot determine the secret key.
Unfortunately, the Boolean satisfiability (SAT) based attack, introduced in
[1], can break different logic locking schemes in minutes. In this paper, we
propose a novel test pattern generation approach using the powerful SAT attack
on logic locking. A stuck-at fault is modeled as a locked gate with a secret
key. Our modeling of stuck-at faults preserves the property of fault activation
and propagation. We show that the input pattern that determines the key is a
test for the stuck-at fault. We propose two different approaches for test
pattern generation. First, a single stuck-at fault is targeted, and a
corresponding locked circuit with one key bit is created. This approach
generates one test pattern per fault. Second, we consider a group of faults and
convert the circuit to its locked version with multiple key bits. The inputs
obtained from the SAT tool are the test set for detecting this group of faults.
Our approach is able to find test patterns for hard-to-detect faults that were
previously failed in commercial ATPG tools. The proposed test pattern
generation approach can efficiently detect redundant faults present in a
circuit. We demonstrate the effectiveness of the approach on ITC'99 benchmarks.
The results show that we can achieve a perfect fault coverage reaching 100%.Comment: 12 pages, 7 figures, 5 table
SAT-Based Combinational and Sequential Dependency Computation
We present an algorithm for computing both functional dependency and unateness of combinational and sequential Boolean func- tions represented as logic networks. The algorithm uses SAT-based tech- niques from Combinational Equivalence Checking (CEC) and Automatic Test Pattern Generation (ATPG) to compute the dependency matrix of multi-output Boolean functions. Additionally, the classical dependency definitions are extended to sequential functions and a fast approximation is presented to efficiently yield a sequential dependency matrix. Exten- sive experiments show the applicability of the methods and the improved robustness compared to existing approaches
Application of Max-SAT-based ATPG to optimal cancer therapy design
BACKGROUND: Cancer and other gene related diseases are usually caused by a failure in the signaling pathway between genes and cells. These failures can occur in different areas of the gene regulatory network, but can be abstracted as faults in the regulatory function. For effective cancer treatment, it is imperative to identify faults and select appropriate drugs to treat the faults. In this paper, we present an extensible Max-SAT based automatic test pattern generation (ATPG) algorithm for cancer therapy. This ATPG algorithm is based on Boolean Satisfiability (SAT) and utilizes the stuck-at fault model for representing signaling faults. A weighted partial Max-SAT formulation is used to enable efficient selection of the most effective drug. RESULTS: Several usage cases are presented for fault identification and drug selection. These cases include the identification of testable faults, optimal drug selection for single/multiple known faults, and optimal drug selection for overall fault coverage. Experimental results on growth factor (GF) signaling pathways demonstrate that our algorithm is flexible, and can yield an exact solution for each feature in much less than 1 second
IntRepair: Informed Repairing of Integer Overflows
Integer overflows have threatened software applications for decades. Thus, in
this paper, we propose a novel technique to provide automatic repairs of
integer overflows in C source code. Our technique, based on static symbolic
execution, fuses detection, repair generation and validation. This technique is
implemented in a prototype named IntRepair. We applied IntRepair to 2,052C
programs (approx. 1 million lines of code) contained in SAMATE's Juliet test
suite and 50 synthesized programs that range up to 20KLOC. Our experimental
results show that IntRepair is able to effectively detect integer overflows and
successfully repair them, while only increasing the source code (LOC) and
binary (Kb) size by around 1%, respectively. Further, we present the results of
a user study with 30 participants which shows that IntRepair repairs are more
than 10x efficient as compared to manually generated code repairsComment: Accepted for publication at the IEEE TSE journal. arXiv admin note:
text overlap with arXiv:1710.0372
Metamodel Instance Generation: A systematic literature review
Modelling and thus metamodelling have become increasingly important in
Software Engineering through the use of Model Driven Engineering. In this paper
we present a systematic literature review of instance generation techniques for
metamodels, i.e. the process of automatically generating models from a given
metamodel. We start by presenting a set of research questions that our review
is intended to answer. We then identify the main topics that are related to
metamodel instance generation techniques, and use these to initiate our
literature search. This search resulted in the identification of 34 key papers
in the area, and each of these is reviewed here and discussed in detail. The
outcome is that we are able to identify a knowledge gap in this field, and we
offer suggestions as to some potential directions for future research.Comment: 25 page
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