Verifiable Secret Sharing (VSS) is a fundamental building block in cryptography. Despite its importance and extensive studies, existing VSS protocols are often complex and inefficient. Many of them do not support dual thresholds, are not publicly verifiable, or do not properly terminate in asynchronous networks. This paper presents a new and simple approach for designing VSS protocols in synchronous and asynchronous networks. Our VSS protocols are optimally fault-tolerant, i.e., they tolerate a 1/2 and a 1/3 fraction of malicious nodes in synchronous and asynchronous networks, respectively. They only require a public key infrastructure and the hardness of discrete logarithms. Our protocols support dual thresholds, and their transcripts are publicly verifiable. We implement our VSS protocols and evaluate them in a geo-distributed setting with up to 256 nodes. The evaluation demonstrates that our protocols offer asynchronous termination and public verifiability with performance that is comparable to that of existing schemes that lack these features. Compared to the existing schemes with similar guarantees, our approach lowers the bandwidth usage and latency by up to 90%.

A recent approach to building consensus protocols on top of Directed Acyclic Graphs (DAGs) shows much promise due to its simplicity and stable throughput. However, as each node in the DAG typically includes a linear number of references to the nodes in the previous round, prior DAG protocols only scale up to a certain point when the overhead of maintaining the graph becomes the bottleneck. To enable large-scale deployments of DAG-based protocols, we propose a sparse DAG architecture, where each node includes only a constant number of references to random nodes in the previous round. We present a sparse version of Bullshark - one of the most prominent DAG-based consensus protocols - and demonstrate its improved scalability. Remarkably, unlike other protocols that use random sampling to reduce communication complexity, we manage to avoid sacrificing resilience: the protocol can tolerate up to f < n/3 Byzantine faults (where n is the number of participants), same as its less scalable deterministic counterpart. The proposed "sparse" methodology can be applied to any protocol that maintains disseminated system updates and causal relations between them in a graph-like structure. Our simulations show that the considerable reduction of transmitted metadata in sparse DAGs results in more efficient network utilization and better scalability.

Block-STM is a parallel execution engine for smart contracts, built around the principles of Software Transactional Memory. Transactions are grouped in blocks, and every execution of the block must yield the same deterministic outcome. Block-STM further enforces that the outcome is consistent with executing transactions according to a preset order, leveraging this order to dynamically detect dependencies and avoid conflicts during speculative transaction execution. At the core of Block-STM is a novel, low-overhead collaborative scheduler of execution and validation tasks.

This paper provides a formal framework for reasoning about randomized distributed algorithms. We generalize the notion of indistinguishability, the most useful tool in deterministic lower bounds, to apply to a probabilistic setting. We use the new notion to prove a lower bound on the probability at which it can be guaranteed that honest parties will not decide on a possibly bogus value. Moreover, we show that the bound is tight by providing a protocol that matches the bound. This completely characterizes the quality of decisions that protocols for a randomized multi-valued Consensus problem can guarantee in an asynchronous environment with Byzantine faults.

We present Bullshark, the first directed acyclic graph (DAG) based asynchronous Byzantine Atomic Broadcast protocol that is optimized for the common synchronous case. Like previous DAG-based BFT protocols [19, 25], Bullshark requires no extra communication to achieve consensus on top of building the DAG. That is, parties can totally order the vertices of the DAG by interpreting their local view of the DAG edges. Unlike other asynchronous DAG-based protocols, Bullshark provides a practical low latency fast-path that exploits synchronous periods and deprecates the need for notoriously complex view-change and view-synchronization mechanisms. Bullshark achieves this while maintaining all the desired properties of its predecessor DAG-Rider [25]. Namely, it has optimal amortized communication complexity, it provides fairness and asynchronous liveness, and safety is guaranteed even under a quantum adversary.

We propose separating the task of reliable transaction dissemination from transaction ordering, to enable high-performance Byzantine fault-tolerant quorum-based consensus. We design and evaluate a mempool protocol, Narwhal, specializing in high-throughput reliable dissemination and storage of causal histories of transactions. Narwhal tolerates an asynchronous network and maintains high performance despite failures. Narwhal is designed to easily scale-out using multiple workers at each validator, and we demonstrate that there is no foreseeable limit to the throughput we can achieve.

Byzantine Agreement (BA) is a key component in many distributed systems. While Dolev and Reischuk have proven a long time ago that quadratic communication complexity is necessary for worst-case runs, the question of what can be done in practically common runs with fewer failures remained open. In this paper we present the first Byzantine Broadcast algorithm with O(n(f+1)) communication complexity in a model with resilience of n = 2t+1, where 0 ≤ f ≤ t is the actual number of process failures in a run. And for BA with strong unanimity, we present the first optimal-resilience algorithm that has linear communication complexity in the failure-free case and a quadratic cost otherwise.

Byzantine Agreement (BA) is a key component in many distributed systems. While Dolev and Reischuk have proven a long time ago that quadratic word complexity is necessary for worst-case runs, the question of what can be done in practically common runs with fewer failures remained open. In this paper we present the first Byzantine Broadcast algorithm with O(n(f+1)) word complexity in a model with resilience of n=2t+1, where 0 ≤ f ≤ t is the actual number of process failures in a run.

The cryptocurrency market is blooming. Tens of new coins emerge every year and their total market cap keeps growing. The research community is trying to keep up by proposing improved mining protocols and attacking existing ones. However, surprisingly as it may sound, most existing works overlook the real-life multi-coin market, by focusing on a system with a single coin. To the best of our knowledge, this paper was the first to consider a system with many coins and strategic miners that are free to choose where to mine. We first formalize the current practice of strategic mining in multi-coin markets as a singleton weighted congestion game and prove that any better-response dynamics in such a game converges to an equilibrium. Then, in our main result, we present a reward design attack that moves the system configuration from any initial equilibrium to a desired one. The attack is executed via temporary manipulation of coin rewards, which leads strategic miners to switch between coins. It applies to any better-response dynamics of the miners. To motivate our attack we show that in any equilibrium there is always at least one miner whose profit is higher in a different one, and thus may benefit from such an attack.

The popularity of permissioned blockchain systems demands BFT SMR protocols that are efficient under good network conditions (synchrony) and robust under bad network conditions (asynchrony). The state-of-the-art partially synchronous BFT SMR protocols provide optimal linear communication cost per decision under synchrony and good leaders, but lose liveness under asynchrony. On the other hand, the state-of-the-art asynchronous BFT SMR protocols are live even under asynchrony, but always pay quadratic cost even under synchrony. In this paper, we propose a BFT SMR protocol that achieves the best of both worlds -- optimal linear cost per decision under good networks and leaders, optimal quadratic cost per decision under bad networks, and remains always live.

We present DAG-Rider, the first asynchronous Byzantine Atomic Broadcast protocol that achieves optimal resilience, optimal amortized communication complexity, and optimal time complexity. DAG-Rider is post-quantum safe and ensures that all values proposed by correct processes eventually get delivered. We construct DAG-Rider in two layers: In the first layer, processes reliably broadcast their proposals and build a structured Directed Acyclic Graph (DAG) of the communication among them. In the second layer, processes locally observe their DAGs and totally order all proposals with no extra communication.

Transactional data structure libraries (TDSL) combine the ease-of-programming of transactions with the high performance and scalability of custom-tailored concurrent data structures. They can be very efficient thanks to their ability to exploit data structure semantics in order to reduce overhead, aborts, and wasted work compared to general-purpose software transactional memory. However, TDSLs were not previously used for complex use-cases involving long transactions and a variety of data structures. In this paper, we boost the performance and usability of a TDSL, towards allowing it to support complex applications. A key idea is nesting. Nested transactions create checkpoints within a longer transaction, so as to limit the scope of abort, without changing the semantics of the original transaction. We build a Java TDSL with built-in support for nested transactions over a number of data structures. We conduct a case study of a complex network intrusion detection system that invests a significant amount of work to process each packet. Our study shows that our library outperforms publicly available STMs twofold without nesting, and by up to 16x when nesting is used.

Lower bounds and impossibility results in distributed computing are both intellectually challenging and practically important. Hundreds if not thousands of proofs appear in the literature, but surprisingly, the vast majority of them apply to deterministic algorithms only. Probabilistic protocols have been around for at least four decades and are receiving a lot of attention with the emergence of blockchain systems. Nonetheless, we are aware of only a handful of randomized lower bounds. In this work we provide a formal framework for reasoning about randomized distributed algorithms. We generalize the notion of indistinguishability, the most useful tool in deterministic lower bounds, to apply to a probabilistic setting. We apply this framework to prove a result of independent interest. Namely, we completely characterize the quality of decisions that protocols for a randomized multi-valued Consensus problem can guarantee in an asynchronous environment with Byzantine faults. We use the new notion to prove a lower bound on the guaranteed probability that honest parties will not decide on a possibly bogus value proposed by a malicious party. Finally, we show that the bound is tight by providing a protocol that matches it. This brief announcement consists of an introduction to the full paper [Guy Goren et al., 2020] by the same title. The interested reader is advised to consult the full paper for a detailed exposition.

In this paper, we challenge the conventional approach of state machine replication systems to design deterministic agreement protocols in the eventually synchronous communication model. We first prove that no such protocol can guarantee bounded communication cost before the global stabilization time and propose a different approach that hopes for the best (synchrony) but prepares for the worst (asynchrony). Accordingly, we design an optimistic byzantine agreement protocol that first tries an efficient deterministic algorithm that relies on synchrony for termination only, and then, only if an agreement was not reached due to asynchrony, the protocol uses a randomized asynchronous protocol for fallback that guarantees termination with probability 1. We formally prove that our protocol achieves optimal communication complexity under all network conditions and failure scenarios. We first prove a lower bound of $Ω(ft+ t)$ for synchronous deterministic byzantine agreement protocols, where $t$ is the failure threshold, and $f$ is the actual number of failures. Then, we present a tight upper bound and use it for the synchronous part of the optimistic protocol. Finally, for the asynchronous fallback, we use a variant of the (optimal) VABA protocol, which we reconstruct to safely combine it with the synchronous part. We believe that our adaptive to failures synchronous byzantine agreement protocol has an independent interest since it is the first protocol we are aware of which communication complexity optimally depends on the actual number of failures.

In this paper, we present the first Asynchronous Distributed Key Generation (ADKG) algorithm which is also the first distributed key generation algorithm that can generate cryptographic keys with a dual (f,2f+1)-threshold (where f is the number of faulty parties). As a result, using our ADKG we remove the trusted setup assumption that the most scalable consensus algorithms make. In order to create a DKG with a dual (f,2f+1)- threshold we first answer in the affirmative the open question posed by Cachin et al. [7] on how to create an Asynchronous Verifiable Secret Sharing (AVSS) protocol with a reconstruction threshold of f+1

With the emergence of attack-prone cross-organization systems, providing asynchronous state machine replication (SMR) solutions is no longer a theoretical concern. This paper presents ACE, a framework for the design of such fault tolerant systems. Leveraging a known paradigm for randomized consensus solutions, ACE wraps existing practical solutions and real-life systems, boosting their liveness under adversarial conditions and, at the same time, promoting load balancing and fairness. Boosting is achieved without modifying the overall design or the engineering of these solutions. ACE is aimed at boosting the prevailing approach for practical fault tolerance. This approach, often named partial synchrony, is based on a leader-based paradigm: a good leader makes progress and a bad leader does no harm. The partial synchrony approach focuses on safety and forgoes liveness under targeted and dynamic attacks. Specifically, an attacker might block specific leaders, e.g., through a denial of service, to prevent progress. ACE provides boosting by running waves of parallel leaders and selecting a winning leader only retroactively, achieving boosting at a linear communication cost increase. ACE is agnostic to the fault model, inheriting it s failure model from the wrapped solution assumptions. As our evaluation shows, an asynchronous Byzantine fault tolerance (BFT) replication system built with ACE around an existing partially synchronous BFT protocol demonstrates reasonable slow-down compared with the base BFT protocol during faultless synchronous scenarios, yet exhibits significant speedup while the system is under attack.

King and Saia were the first to break the quadratic word complexity bound for Byzantine Agreement in synchronous systems against an adaptive adversary, and Algorand broke this bound with near-optimal resilience (first in the synchronous model and then with eventual-synchrony). Yet the question of asynchronous sub-quadratic Byzantine Agreement remained open. To the best of our knowledge, we are the first to answer this question in the affirmative. A key component of our solution is a shared coin algorithm based on a VRF. A second essential ingredient is VRF-based committee sampling, which we formalize and utilize in the asynchronous model for the first time. Our algorithms work against a delayed-adaptive adversary, which cannot perform after-the-fact removals but has full control of Byzantine processes and full information about communication in earlier rounds. Using committee sampling and our shared coin, we solve Byzantine Agreement with high probability, with a word complexity of Õ(n) and O(1) expected time, breaking the O(n2) bit barrier for asynchronous Byzantine Agreement.

Transactional data structure libraries (TDSL) combine the ease-of-programming of transactions with the high performance and scalability of custom-tailored concurrent data structures. They can be very efficient thanks to their ability to exploit data structure semantics in order to reduce overhead, aborts, and wasted work compared to general-purpose software transactional memory. However, TDSLs were not previously used for complex use-cases involving long transactions and a variety of data structures.

Data sketches are approximate succinct summaries of long data streams. They are widely used for processing massive amounts of data and answering statistical queries about it. Existing libraries producing sketches are very fast, but do not allow parallelism for creating sketches using multiple threads or querying them while they are being built. We present a generic approach to parallelising data sketches efficiently and allowing them to be queried in real time, while bounding the error that such parallelism introduces. Utilising relaxed semantics and the notion of strong linearisability we prove our algorithm's correctness and analyse the error it induces in two specific sketches. Our implementation achieves high scalability while keeping the error small. We have contributed one of our concurrent sketches to the open-source data sketches library.

King and Saia were the first to break the quadratic word complexity bound for Byzantine Agreement in synchronous systems against an adaptive adversary, and Algorand broke this bound with near-optimal resilience (first in the synchronous model and then with eventual-synchrony). Yet the question of asynchronous sub-quadratic Byzantine Agreement remained open. To the best of our knowledge, we are the first to answer this question in the affirmative. A key component of our solution is a shared coin algorithm based on a VRF. A second essential ingredient is VRF-based committee sampling, which we formalize and utilize in the asynchronous model for the first time. Our algorithms work against a delayed-adaptive adversary, which cannot perform after-the-fact removals but has full control of Byzantine processes and full information about communication in earlier rounds. Using committee sampling and our shared coin, we solve Byzantine Agreement with high probability, with a word complexity of $\widetilde{O}(n)$ and $O(1)$ expected time, breaking the $O(n^2)$ bit barrier for asynchronous Byzantine Agreement.

Financial institutions are currently looking into technologies for permissioned blockchains. A major effort in this direction is Hyperledger, an open source project hosted by the Linux Foundation and backed by a consortium of over a hundred companies. A key component in permissioned blockchain protocols is a byzantine fault tolerant (BFT) consensus engine that orders transactions. However, currently available BFT solutions in Hyperledger (as well as in the literature at large) are inadequate for financial settings; they are not designed to ensure fairness or to tolerate selfish behavior that arises when financial institutions strive to maximize their own profit. We present FairLedger, a permissioned blockchain BFT protocol, which is fair, designed to deal with rational behavior, and, no less important, easy to understand and implement. The secret sauce of our protocol is a new communication abstraction, called detectable all-to-all (DA2A), which allows us to detect participants (byzantine or rational) that deviate from the protocol, and punish them. We implement FairLedger in the Hyperledger open source project, using Iroha framework, one of the biggest projects therein. To evaluate FairLegder's performance, we also implement it in the PBFT framework and compare the two protocols. Our results show that in failure-free scenarios FairLedger achieves better throughput than both Iroha's implementation and PBFT in wide-area settings.

We provide a new protocol for Validated Asynchronous Byzantine Agreement in the authenticated setting. Validated (multi-valued) Asynchronous Byzantine Agreement is a key building block in constructing Atomic Broadcast and fault-tolerant state machine replication in the asynchronous setting. Our protocol has optimal resilience of ƒ < n/3 Byzantine failures and asymptotically optimal expected O(1) running time to reach agreement. Honest parties in our protocol send only an expected O(n2) messages where each message contains a value and a constant number of signatures. Hence our total expected communication is O(n2) words. The best previous result of Cachin et al. from 2001 solves Validated Byzantine Agreement with optimal resilience and O(1) expected time but with O(n3) expected word communication. Our work addresses an open question of Cachin et al. from 2001 and improves the expected word communication from O(n3) to asymptotically optimal O(n2).

Data sketches are approximate succinct summaries of long data streams. They are widely used for processing massive amounts of data and answering statistical queries about it. Existing libraries producing sketches are very fast, but do not allow parallelism for creating sketches using multiple threads or querying them while they are being built. We present a generic approach to parallelising data sketches efficiently and allowing them to be queried in real time, while bounding the error that such parallelism introduces. Utilising relaxed semantics and the notion of strong linearisability we prove our algorithm's correctness and analyse the error it induces in two specific sketches. Our implementation achieves high scalability while keeping the error small. We have contributed one of our concurrent sketches to the open-source data sketches library.

We point out a somewhat surprising similarity between non-authenticated Byzantine storage, coded storage, and certain emulations of shared registers from smaller ones. A common characteristic in all of these is the inability of reads to safely return a value obtained in a single atomic access to shared storage. We collectively refer to such systems as disintegrated storage, and show integrated space lower bounds for asynchronous regular wait-free emulations in all of them. In a nutshell, if readers are invisible, then the storage cost of such systems is inherently exponential in the size of written values; otherwise, it is at least linear in the number of readers. Our bounds are asymptotically tight to known algorithms, and thus justify their high costs.

The decentralized cryptocurrency Bitcoin has experienced great success but also encountered many challenges. One of the challenges has been the long confirmation time. Another challenge is the lack of incentives at certain steps of the protocol, raising concerns for transaction withholding, selfish mining, etc. To address these challenges, we propose Solida, a decentralized blockchain protocol based on reconfigurable Byzantine consensus augmented by proof-of-work. Solida improves on Bitcoin in confirmation time, and provides safety and liveness assuming the adversary control less than (roughly) one-third of the total mining power.

Driven by the rising popularity of cloud storage, the costs associated with implementing reliable storage services from a collection of fault-prone servers have recently become an actively studied question. The well-known ABD result shows that an f-tolerant register can be emulated using a collection of 2f+1 fault-prone servers each storing a single read-modify-write object, which is known to be optimal. In this paper we generalize this bound: we investigate the inherent space complexity of emulating reliable multi-writer registers as a function of the type of the base objects exposed by the underlying servers, the number of writers to the emulated register, the number of available servers, and the failure threshold.

Contrary to common belief, a recent work by Ellen, Gelashvili, Shavit, and Zhu has shown that computability does not require multicore architectures to support "strong" synchronization instructions like compare-and-swap, as opposed to combinations of "weaker" instructions like decrement and multiply. However, this is the status quo, and in turn, most efficient concurrent data-structures heavily rely on compare-and-swap (e.g. for swinging pointers). We show that this need not be the case, by designing and implementing a concurrent linearizable Log data-structure (also known as a History object), supporting two operations: append(item), which appends the item to the log, and get-log(), which returns the appended items so far, in order. Readers are wait-free and writers are lock-free, hence this data-structure can be used in a lock-free universal construction to implement any concurrent object with a given sequential specification. Our implementation uses atomic read, xor, decrement, and fetch-and-increment instructions supported on X86 architectures, and provides similar performance to a compare-and-swap-based solution on today's hardware. This raises a fundamental question about minimal set of synchronization instructions that the architectures have to support.

Providing clean and efficient foundations and tools for reconfiguration is a crucial enabler for distributed system management today. This work takes a step towards developing such foundations. It considers classic fault-tolerant atomic objects emulated on top of a static set of fault-prone servers, and turns them into dynamic ones. The specification of a dynamic object extends the corresponding static (non-dynamic) one with an API for changing the underlying set of fault-prone servers. Thus, in a dynamic model, an object can start in some configuration and continue in a different one. Its liveness is preserved through the reconfigurations it undergoes, tolerating a versatile set of faults as it shifts from one configuration to another. In this paper we present a general abstraction for asynchronous reconfiguration, and exemplify its usefulness for building two dynamic objects: a read/write register and a max-register. We first define a dynamic model with a clean failure condition that allows an administrator to reconfigure the system and switch off a server once the reconfiguration operation removing it completes. We then define the Reconfiguration abstraction and show how it can be used to build dynamic registers and max-registers. Finally, we give an optimal asynchronous algorithm implementing the Reconfiguration abstraction, which in turn leads to the first asynchronous (consensus-free) dynamic register emulation with optimal complexity. More concretely, faced with n requests for configuration changes, the number of configurations that the dynamic register is implemented over is n; and the complexity of each client operation is O(n).

Distributed consensus is integral to modern distributed systems. The widely adopted Paxos algorithm uses two phases, each requiring majority agreement, to reliably reach consensus. In this paper, we demonstrate that Paxos, which lies at the foundation of many production systems, is conservative. Specifically, we observe that each of the phases of Paxos may use non-intersecting quorums. Majority quorums are not necessary as intersection is required only across phases. Using this weakening of the requirements made in the original formulation, we propose Flexible Paxos, which generalizes over the Paxos algorithm to provide flexible quorums. We show that Flexible Paxos is safe, e cient and easy to utilize in existing distributed systems. We discuss far reaching implications of this result. For example, improved availability results from reducing the size of second phase quorums by one when the system size is even, while keeping majority quorums in the first phase. Another example is improved throughput of replication by using much smaller phase 2 quorums, while increasing the leader election (phase 1) quorums. Finally, non intersecting quorums in either first or second phases may enhance the efficiency of both.

Snapshots are useful tools for monitoring big distributed and parallel systems. In this paper, we adapt the well-known atomic snapshot abstraction to dynamic models with an unbounded number of participating processes. Our dynamic snapshot specification extends the API to allow changing the set of processes whose values should be returned from a scan operation. We introduce the ephemeral memory model, which consists of a dynamically changing set of nodes; when a node is removed, its memory can be immediately reclaimed. In this model, we present an algorithm for wait-free dynamic atomic snapshots.

We introduce transactions into libraries of concurrent data structures; such transactions can be used to ensure atomicity of sequences of data structure operations. By focusing on transactional access to a well-defined set of data structure operations, we strike a balance between the ease-of-programming of transactions and the efficiency of custom-tailored data structures. We exemplify this concept by designing and implementing a library supporting transactions on any number of maps, sets (implemented as skiplists), and queues. Our library offers efficient and scalable transactions, which are an order of magnitude faster than state-of-the-art transactional memory toolkits. Moreover, our approach treats stand-alone data structure operations (like put and enqueue) as first class citizens, and allows them to execute with virtually no overhead, at the speed of the original data structure library.

We study the inherent space requirements of reliable storage algorithms in asynchronous distributed systems. A number of recent works have used codes in order to achieve a better storage cost than the well-known replication approach. However, a closer look reveals that they incur extra costs in certain scenarios. Specifically, if multiple clients access the storage concurrently, then existing asynchronous code-based algorithms may store a number of copies of the data that grows linearly with the number of concurrent clients. We prove here that this is inherent. Given three parameters, (1) the data size -- D bits, (2) the concurrency level -- c, and (3) the number of storage node failures that need to be tolerated -- f, we show a lower bound of Omega(min(f,c)D) bits on the space complexity of asynchronous distributed storage algorithms. Intuitively, this implies that the asymptotic storage cost is either as high as with replication, namely O(fD), or as high under concurrency as with the aforementioned code-based algorithms, i.e., O(cD).

We introduce transactions into libraries of concurrent data structures; such transactions can be used to ensure atomicity of sequences of data structure operations. By restricting transactional access to a well-defined set of data structure operations, we strike a balance between the ease-of-programming of transactions and the efficiency of custom-tailored data structures. We exemplify this concept by designing and implementing a library supporting transactions on any number of maps, sets (implemented as skiplists), and queues. Our library offers efficient and scalable transactions, which are an order of magnitude faster than state-of-the-art transactional memory toolkits. Moreover, our approach treats stand-alone data structure operations (like put and enqueue) as first class citizens, and allows them to execute with virtually no overhead, at the speed of the original data structure library.

We present here a synopsis of a keynote presentation given by Idit Keidar at OPODIS 2015, the International Conference on Principles of Distributed Systems, which took place in Rennes, France, on December 14-17 2015.

A key challenge for distributed systems is the problem of reconfiguration. Clearly, any production storage system that provides data reliability and availability for long periods must be able to reconfigure in order to remove failed or old servers and add healthy or new ones. This is far from trivial since we do not want the reconfiguration management to be centralized or cause a system shutdown. In this tutorial we look into existing reconfigurable storage algorithms. We propose a common model and failure condition capturing their guarantees. We define a reconfiguration problem around which dynamic object solutions may be designed. To demonstrate its strength, we use it to implement dynamic atomic storage. We present a generic framework for solving the reconfiguration problem, show how to recast existing algorithms in terms of this framework, and compare among them.