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18
Less hashing, same performance: Building a better bloom filter
 In Proc. the 14th Annual European Symposium on Algorithms (ESA 2006
, 2006
"... ABSTRACT: A standard technique from the hashing literature is to use two hash functions h1(x) and h2(x) to simulate additional hash functions of the form gi(x) = h1(x) + ih2(x). We demonstrate that this technique can be usefully applied to Bloom filters and related data structures. Specifically, on ..."
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Cited by 60 (7 self)
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ABSTRACT: A standard technique from the hashing literature is to use two hash functions h1(x) and h2(x) to simulate additional hash functions of the form gi(x) = h1(x) + ih2(x). We demonstrate that this technique can be usefully applied to Bloom filters and related data structures. Specifically, only two hash functions are necessary to effectively implement a Bloom filter without any loss in the asymptotic false positive probability. This leads to less computation and potentially less need for
Software Model Checking with SPIN
, 2005
"... The aim of this chapter is to give an overview ofthe theoretical foundation and the practical application of logic model checking techniques for the verification of multithreaded software (rather than hardware) systems. The treatment is focused on the logic model checker SPIN, which was designed fo ..."
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Cited by 22 (0 self)
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The aim of this chapter is to give an overview ofthe theoretical foundation and the practical application of logic model checking techniques for the verification of multithreaded software (rather than hardware) systems. The treatment is focused on the logic model checker SPIN, which was designed for this specific domain of application. SPIN implements an automatatheoretic method of verification. Although the tool has been available for over 15years, it continues to ev olve, adopting new optimization strategies from time to time to help it tackle larger verification problems. This chapter explains how the tool works, and
Bloom Filters in Probabilistic Verification
 In Proceedings of the 5th International Conference on Formal Methods in ComputerAided Design (FMCAD
, 2004
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To Store or Not To Store” reloaded: Reclaiming memory on demand
 Formal Methods: Applications and Technology (FMICS + PDMC), volume 4346 of Lecture Notes in Computer Science
, 2006
"... Abstract. Behrmann et al. posed the question whether “To Store or Not To Store ” [3] states during reachability analysis, in order to counter the effects of the wellknown state space explosion problem in explicitstate model checking. Their answer was to store not all but only some strategical stat ..."
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Cited by 14 (1 self)
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Abstract. Behrmann et al. posed the question whether “To Store or Not To Store ” [3] states during reachability analysis, in order to counter the effects of the wellknown state space explosion problem in explicitstate model checking. Their answer was to store not all but only some strategical states. They pay in runtime if the answer too often is “Not To Store”. We propose a different strategy to adaptively trade time for space: “To Store ” as many states as memory limits permit. If free memory becomes scarce, we gradually swap states out to secondary storage. We are careful to minimize revisits, and I/O overhead, and also stay sound, i.e. on termination it is guaranteed that the full state space has been explored. It is also available for counterexample reconstruction. In our experiments we tackled state spaces of industrialscale models with more than 109 explicit states with still modest storage requirements. 1
A Sequential Indexing Scheme for flashbased embedded systems. EDBT, 2009. A: The DMSP experimental project This annex presents an experimental project of secure and portable medicalsocial folder (DMSP in French) [6]. Its goal is to improve the coordinat
 in the Patient’s SPT and in the
"... NAND Flash has become the most popular stable storage medium for embedded systems. As onboard storage capacity increases, the need for efficient indexing techniques arises. Such techniques are very challenging to design due to a combination of NAND Flash constraints (for example the blockerasebef ..."
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Cited by 12 (3 self)
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NAND Flash has become the most popular stable storage medium for embedded systems. As onboard storage capacity increases, the need for efficient indexing techniques arises. Such techniques are very challenging to design due to a combination of NAND Flash constraints (for example the blockerasebeforepagerewrite constraint and limited number of erase cycles) and embedded system constraints (for example tiny RAM and resource consumption predictability). Previous work adapted traditional indexing methods to cope with Flash constraints by deferring index updates using a log and batching them to decrease the number of rewrite operations in Flash memory. However, these methods were not designed with embedded system constraints in mind and do not address them. In this paper, we propose a new alternative for indexing Flashresident data that specifically addresses the embedded context. This approach, called PBFilter, organizes the index structure in a purely sequential way. Key lookups are sped up thanks to two principles called Summarization and Partitioning. We instantiate these principles with data structures and algorithms based on Bloom Filters and show the effectiveness of this approach through a comprehensive performance study. 1.
Simple Summaries for Hashing with Choices
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 2008
"... In a multiplechoice hashing scheme, each item is stored in one of P possible hash table buckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the locations. For applications whe ..."
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Cited by 12 (2 self)
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In a multiplechoice hashing scheme, each item is stored in one of P possible hash table buckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the locations. For applications where this cost is undesirable, Song et al. propose keeping a summary that allows one to determine which of the locations is appropriate for each item, where the summary may allow false positives for items not in hash table. We propose alternative, simple constructions of such summaries that use less space for both the summary and the underlying hash table. Moreover, our constructions are easily analyzable and tunable.
Fighting state space explosion: Review and evaluation
 In Proc. of Formal Methods for Industrial Critical Systems (FMICS’08
, 2008
"... Abstract. In order to apply formal methods in practice, the practitioner has to comprehend a vast amount of research literature and realistically evaluate practical merits of different approaches. In this paper we focus on explicit finite state model checking and study this area from practitioner’s ..."
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Abstract. In order to apply formal methods in practice, the practitioner has to comprehend a vast amount of research literature and realistically evaluate practical merits of different approaches. In this paper we focus on explicit finite state model checking and study this area from practitioner’s point of view. We provide a systematic overview of techniques for fighting state space explosion and we analyse trends in the research. We also report on our own experience with practical performance of techniques. Our main conclusion and recommendation for practitioner is the following: be critical to claims of dramatic improvement brought by a single sophisticated technique, rather use many different simple techniques and combine them. 1
Bloom Filters via dleft Hashing and Dynamic Bit Reassignment
 Proceedings of the Allerton Conference on Communication, Control and Computing
, 2006
"... Abstract — In recent work, the authors introduced a data structure with the same functionality as a counting Bloom filter (CBF) based on fingerprints and the dleft hashing technique. This paper describes dynamic bit reassignment, an approach that allows the size of the fingerprint to flexibly chang ..."
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Cited by 10 (2 self)
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Abstract — In recent work, the authors introduced a data structure with the same functionality as a counting Bloom filter (CBF) based on fingerprints and the dleft hashing technique. This paper describes dynamic bit reassignment, an approach that allows the size of the fingerprint to flexibly change with the load in each hash bucket, thereby reducing the probability of a false positive. This technique allows us to not only improve our dleft counting Bloom filter, but also to construct a data structure with the same functionality as a Bloom filter, including the ability to handle insertions online, that yields fewer false positives for sufficiently large filters. Our results show that our dleft Bloom filter data structure begins achieving smaller false positive rates than the standard construction at 16 bits per element. We explain the technique, describe why it is amenable to hardware implementation, and provide experimental results. I.
Simple Summaries for Hashing with Multiple Choices
"... In a multiplechoice hashing scheme, each item is stored in one of d> = 2 possible hash tablebuckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the d locations. Forapplicat ..."
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Cited by 9 (3 self)
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In a multiplechoice hashing scheme, each item is stored in one of d> = 2 possible hash tablebuckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the d locations. Forapplications where this cost is undesirable, Song et al. propose keeping a summary that allows one to determine which of the d locations is appropriate for each item, where the summary may allowfalse positives for items not in hash table. We propose alternative, simple constructions of such summaries that use less space for both the summary and the underlying hash table. Moreover, ourconstructions are easily analyzable and tunable.
Building a better Bloom filter
 In Proceedings of the 14th Annual European Symposium on Algorithms (ESA
, 2005
"... A technique from the hashing literature is to use two hash functions h1(x) and h2(x) to simulate additional hash functions of the form gi(x) = h1(x) + ih2(x). We demonstrate that this technique can be usefully applied to Bloom filters and related data structures. Specifically, only two hash functio ..."
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Cited by 8 (4 self)
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A technique from the hashing literature is to use two hash functions h1(x) and h2(x) to simulate additional hash functions of the form gi(x) = h1(x) + ih2(x). We demonstrate that this technique can be usefully applied to Bloom filters and related data structures. Specifically, only two hash functions are necessary to effectively implement a Bloom filter without any loss in the asymptotic false positive probability. This leads to less computation and potentially less need for randomness in practice. 1