@article{7212,
abstract = {The fixation probability of a single mutant invading a population of residents is among the most widely-studied quantities in evolutionary dynamics. Amplifiers of natural selection are population structures that increase the fixation probability of advantageous mutants, compared to well-mixed populations. Extensive studies have shown that many amplifiers exist for the Birth-death Moran process, some of them substantially increasing the fixation probability or even guaranteeing fixation in the limit of large population size. On the other hand, no amplifiers are known for the death-Birth Moran process, and computer-assisted exhaustive searches have failed to discover amplification. In this work we resolve this disparity, by showing that any amplification under death-Birth updating is necessarily bounded and transient. Our boundedness result states that even if a population structure does amplify selection, the resulting fixation probability is close to that of the well-mixed population. Our transience result states that for any population structure there exists a threshold r⋆ such that the population structure ceases to amplify selection if the mutant fitness advantage r is larger than r⋆. Finally, we also extend the above results to δ-death-Birth updating, which is a combination of Birth-death and death-Birth updating. On the positive side, we identify population structures that maintain amplification for a wide range of values r and δ. These results demonstrate that amplification of natural selection depends on the specific mechanisms of the evolutionary process.},
author = {Tkadlec, Josef and Pavlogiannis, Andreas and Chatterjee, Krishnendu and Nowak, Martin A.},
issn = {15537358},
journal = {PLoS computational biology},
publisher = {PLoS},
title = {{Limits on amplifiers of natural selection under death-Birth updating}},
doi = {10.1371/journal.pcbi.1007494},
volume = {16},
year = {2020},
}
@inproceedings{7810,
abstract = {Interprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointers analysis. The most widely-used framework for interprocedural data-flow analysis is IFDS, which encompasses distributive data-flow functions over a finite domain. On-demand data-flow analyses restrict the focus of the analysis on specific program locations and data facts. This setting provides a natural split between (i) an offline (or preprocessing) phase, where the program is partially analyzed and analysis summaries are created, and (ii) an online (or query) phase, where analysis queries arrive on demand and the summaries are used to speed up answering queries.
In this work, we consider on-demand IFDS analyses where the queries concern program locations of the same procedure (aka same-context queries). We exploit the fact that flow graphs of programs have low treewidth to develop faster algorithms that are space and time optimal for many common data-flow analyses, in both the preprocessing and the query phase. We also use treewidth to develop query solutions that are embarrassingly parallelizable, i.e. the total work for answering each query is split to a number of threads such that each thread performs only a constant amount of work. Finally, we implement a static analyzer based on our algorithms, and perform a series of on-demand analysis experiments on standard benchmarks. Our experimental results show a drastic speed-up of the queries after only a lightweight preprocessing phase, which significantly outperforms existing techniques.},
author = {Chatterjee, Krishnendu and Goharshady, Amir Kafshdar and Ibsen-Jensen, Rasmus and Pavlogiannis, Andreas},
booktitle = {European Symposium on Programming},
isbn = {9783030449131},
issn = {16113349},
location = {Dublin, Ireland},
pages = {112--140},
publisher = {Springer Nature},
title = {{Optimal and perfectly parallel algorithms for on-demand data-flow analysis}},
doi = {10.1007/978-3-030-44914-8_5},
volume = {12075},
year = {2020},
}
@article{7158,
abstract = {
Interprocedural analysis is at the heart of numerous applications in programming languages, such as alias analysis, constant propagation, and so on. Recursive state machines (RSMs) are standard models for interprocedural analysis. We consider a general framework with RSMs where the transitions are labeled from a semiring and path properties are algebraic with semiring operations. RSMs with algebraic path properties can model interprocedural dataflow analysis problems, the shortest path problem, the most probable path problem, and so on. The traditional algorithms for interprocedural analysis focus on path properties where the starting point is fixed as the entry point of a specific method. In this work, we consider possible multiple queries as required in many applications such as in alias analysis. The study of multiple queries allows us to bring in an important algorithmic distinction between the resource usage of the one-time preprocessing vs for each individual query. The second aspect we consider is that the control flow graphs for most programs have constant treewidth.
Our main contributions are simple and implementable algorithms that support multiple queries for algebraic path properties for RSMs that have constant treewidth. Our theoretical results show that our algorithms have small additional one-time preprocessing but can answer subsequent queries significantly faster as compared to the current algorithmic solutions for interprocedural dataflow analysis. We have also implemented our algorithms and evaluated their performance for performing on-demand interprocedural dataflow analysis on various domains, such as for live variable analysis and reaching definitions, on a standard benchmark set. Our experimental results align with our theoretical statements and show that after a lightweight preprocessing, on-demand queries are answered much faster than the standard existing algorithmic approaches.
},
author = {Chatterjee, Krishnendu and Goharshady, Amir Kafshdar and Goyal, Prateesh and Ibsen-Jensen, Rasmus and Pavlogiannis, Andreas},
issn = {0164-0925},
journal = {ACM Transactions on Programming Languages and Systems},
number = {4},
publisher = {ACM},
title = {{Faster algorithms for dynamic algebraic queries in basic RSMs with constant treewidth}},
doi = {10.1145/3363525},
volume = {41},
year = {2019},
}
@article{7210,
abstract = {The rate of biological evolution depends on the fixation probability and on the fixation time of new mutants. Intensive research has focused on identifying population structures that augment the fixation probability of advantageous mutants. But these amplifiers of natural selection typically increase fixation time. Here we study population structures that achieve a tradeoff between fixation probability and time. First, we show that no amplifiers can have an asymptotically lower absorption time than the well-mixed population. Then we design population structures that substantially augment the fixation probability with just a minor increase in fixation time. Finally, we show that those structures enable higher effective rate of evolution than the well-mixed population provided that the rate of generating advantageous mutants is relatively low. Our work sheds light on how population structure affects the rate of evolution. Moreover, our structures could be useful for lab-based, medical, or industrial applications of evolutionary optimization.},
author = {Tkadlec, Josef and Pavlogiannis, Andreas and Chatterjee, Krishnendu and Nowak, Martin A.},
issn = {2399-3642},
journal = {Communications Biology},
publisher = {Springer Nature},
title = {{Population structure determines the tradeoff between fixation probability and fixation time}},
doi = {10.1038/s42003-019-0373-y},
volume = {2},
year = {2019},
}
@article{6380,
abstract = {There is a huge gap between the speeds of modern caches and main memories, and therefore cache misses account for a considerable loss of efficiency in programs. The predominant technique to address this issue has been Data Packing: data elements that are frequently accessed within time proximity are packed into the same cache block, thereby minimizing accesses to the main memory. We consider the algorithmic problem of Data Packing on a two-level memory system. Given a reference sequence R of accesses to data elements, the task is to partition the elements into cache blocks such that the number of cache misses on R is minimized. The problem is notoriously difficult: it is NP-hard even when the cache has size 1, and is hard to approximate for any cache size larger than 4. Therefore, all existing techniques for Data Packing are based on heuristics and lack theoretical guarantees. In this work, we present the first positive theoretical results for Data Packing, along with new and stronger negative results. We consider the problem under the lens of the underlying access hypergraphs, which are hypergraphs of affinities between the data elements, where the order of an access hypergraph corresponds to the size of the affinity group. We study the problem parameterized by the treewidth of access hypergraphs, which is a standard notion in graph theory to measure the closeness of a graph to a tree. Our main results are as follows: We show there is a number q* depending on the cache parameters such that (a) if the access hypergraph of order q* has constant treewidth, then there is a linear-time algorithm for Data Packing; (b)the Data Packing problem remains NP-hard even if the access hypergraph of order q*-1 has constant treewidth. Thus, we establish a fine-grained dichotomy depending on a single parameter, namely, the highest order among access hypegraphs that have constant treewidth; and establish the optimal value q* of this parameter. Finally, we present an experimental evaluation of a prototype implementation of our algorithm. Our results demonstrate that, in practice, access hypergraphs of many commonly-used algorithms have small treewidth. We compare our approach with several state-of-the-art heuristic-based algorithms and show that our algorithm leads to significantly fewer cache-misses. },
author = {Chatterjee, Krishnendu and Goharshady, Amir Kafshdar and Okati, Nastaran and Pavlogiannis, Andreas},
issn = {2475-1421},
journal = {Proceedings of the ACM on Programming Languages},
number = {POPL},
publisher = {ACM},
title = {{Efficient parameterized algorithms for data packing}},
doi = {10.1145/3290366},
volume = {3},
year = {2019},
}
@article{738,
abstract = {This paper is devoted to automatic competitive analysis of real-time scheduling algorithms for firm-deadline tasksets, where only completed tasks con- tribute some utility to the system. Given such a taskset T , the competitive ratio of an on-line scheduling algorithm A for T is the worst-case utility ratio of A over the utility achieved by a clairvoyant algorithm. We leverage the theory of quantitative graph games to address the competitive analysis and competitive synthesis problems. For the competitive analysis case, given any taskset T and any finite-memory on- line scheduling algorithm A , we show that the competitive ratio of A in T can be computed in polynomial time in the size of the state space of A . Our approach is flexible as it also provides ways to model meaningful constraints on the released task sequences that determine the competitive ratio. We provide an experimental study of many well-known on-line scheduling algorithms, which demonstrates the feasibility of our competitive analysis approach that effectively replaces human ingenuity (required Preliminary versions of this paper have appeared in Chatterjee et al. ( 2013 , 2014 ). B Andreas Pavlogiannis pavlogiannis@ist.ac.at Krishnendu Chatterjee krish.chat@ist.ac.at Alexander Kößler koe@ecs.tuwien.ac.at Ulrich Schmid s@ecs.tuwien.ac.at 1 IST Austria (Institute of Science and Technology Austria), Am Campus 1, 3400 Klosterneuburg, Austria 2 Embedded Computing Systems Group, Vienna University of Technology, Treitlstrasse 3, 1040 Vienna, Austria 123 Real-Time Syst for finding worst-case scenarios) by computing power. For the competitive synthesis case, we are just given a taskset T , and the goal is to automatically synthesize an opti- mal on-line scheduling algorithm A , i.e., one that guarantees the largest competitive ratio possible for T . We show how the competitive synthesis problem can be reduced to a two-player graph game with partial information, and establish that the compu- tational complexity of solving this game is Np -complete. The competitive synthesis problem is hence in Np in the size of the state space of the non-deterministic labeled transition system encoding the taskset. Overall, the proposed framework assists in the selection of suitable scheduling algorithms for a given taskset, which is in fact the most common situation in real-time systems design. },
author = {Chatterjee, Krishnendu and Pavlogiannis, Andreas and Kößler, Alexander and Schmid, Ulrich},
journal = {Real-Time Systems},
number = {1},
pages = {166 -- 207},
publisher = {Springer},
title = {{Automated competitive analysis of real time scheduling with graph games}},
doi = {10.1007/s11241-017-9293-4},
volume = {54},
year = {2018},
}
@article{5751,
abstract = {Because of the intrinsic randomness of the evolutionary process, a mutant with a fitness advantage has some chance to be selected but no certainty. Any experiment that searches for advantageous mutants will lose many of them due to random drift. It is therefore of great interest to find population structures that improve the odds of advantageous mutants. Such structures are called amplifiers of natural selection: they increase the probability that advantageous mutants are selected. Arbitrarily strong amplifiers guarantee the selection of advantageous mutants, even for very small fitness advantage. Despite intensive research over the past decade, arbitrarily strong amplifiers have remained rare. Here we show how to construct a large variety of them. Our amplifiers are so simple that they could be useful in biotechnology, when optimizing biological molecules, or as a diagnostic tool, when searching for faster dividing cells or viruses. They could also occur in natural population structures.},
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin A.},
issn = {2399-3642},
journal = {Communications Biology},
number = {1},
publisher = {Springer Nature},
title = {{Construction of arbitrarily strong amplifiers of natural selection using evolutionary graph theory}},
doi = {10.1038/s42003-018-0078-7},
volume = {1},
year = {2018},
}
@article{6009,
abstract = {We study algorithmic questions wrt algebraic path properties in concurrent systems, where the transitions of the system are labeled from a complete, closed semiring. The algebraic path properties can model dataflow analysis problems, the shortest path problem, and many other natural problems that arise in program analysis. We consider that each component of the concurrent system is a graph with constant treewidth, a property satisfied by the controlflow graphs of most programs. We allow for multiple possible queries, which arise naturally in demand driven dataflow analysis. The study of multiple queries allows us to consider the tradeoff between the resource usage of the one-time preprocessing and for each individual query. The traditional approach constructs the product graph of all components and applies the best-known graph algorithm on the product. In this approach, even the answer to a single query requires the transitive closure (i.e., the results of all possible queries), which provides no room for tradeoff between preprocessing and query time.
Our main contributions are algorithms that significantly improve the worst-case running time of the traditional approach, and provide various tradeoffs depending on the number of queries. For example, in a concurrent system of two components, the traditional approach requires hexic time in the worst case for answering one query as well as computing the transitive closure, whereas we show that with one-time preprocessing in almost cubic time, each subsequent query can be answered in at most linear time, and even the transitive closure can be computed in almost quartic time. Furthermore, we establish conditional optimality results showing that the worst-case running time of our algorithms cannot be improved without achieving major breakthroughs in graph algorithms (i.e., improving the worst-case bound for the shortest path problem in general graphs). Preliminary experimental results show that our algorithms perform favorably on several benchmarks.
},
author = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus and Goharshady, Amir Kafshdar and Pavlogiannis, Andreas},
issn = {0164-0925},
journal = {ACM Transactions on Programming Languages and Systems},
number = {3},
publisher = {Association for Computing Machinery (ACM)},
title = {{Algorithms for algebraic path properties in concurrent systems of constant treewidth components}},
doi = {10.1145/3210257},
volume = {40},
year = {2018},
}
@article{512,
abstract = {The fixation probability is the probability that a new mutant introduced in a homogeneous population eventually takes over the entire population. The fixation probability is a fundamental quantity of natural selection, and known to depend on the population structure. Amplifiers of natural selection are population structures which increase the fixation probability of advantageous mutants, as compared to the baseline case of well-mixed populations. In this work we focus on symmetric population structures represented as undirected graphs. In the regime of undirected graphs, the strongest amplifier known has been the Star graph, and the existence of undirected graphs with stronger amplification properties has remained open for over a decade. In this work we present the Comet and Comet-swarm families of undirected graphs. We show that for a range of fitness values of the mutants, the Comet and Cometswarm graphs have fixation probability strictly larger than the fixation probability of the Star graph, for fixed population size and at the limit of large populations, respectively. },
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
issn = {20452322},
journal = {Scientific Reports},
number = {1},
publisher = {Nature Publishing Group},
title = {{Amplification on undirected population structures: Comets beat stars}},
doi = {10.1038/s41598-017-00107-w},
volume = {7},
year = {2017},
}
@misc{5455,
abstract = {A fundamental algorithmic problem at the heart of static analysis is Dyck reachability. The input is a graphwhere the edges are labeled with different types of opening and closing parentheses, and the reachabilityinformation is computed via paths whose parentheses are properly matched. We present new results for Dyckreachability problems with applications to alias analysis and data-dependence analysis. Our main contributions,that include improved upper bounds as well as lower bounds that establish optimality guarantees, are asfollows:First, we consider Dyck reachability on bidirected graphs, which is the standard way of performing field-sensitive points-to analysis. Given a bidirected graph withnnodes andmedges, we present: (i) an algorithmwith worst-case running timeO(m+n·α(n)), whereα(n)is the inverse Ackermann function, improving thepreviously knownO(n2)time bound; (ii) a matching lower bound that shows that our algorithm is optimalwrt to worst-case complexity; and (iii) an optimal average-case upper bound ofO(m)time, improving thepreviously knownO(m·logn)bound.Second, we consider the problem of context-sensitive data-dependence analysis, where the task is to obtainanalysis summaries of library code in the presence of callbacks. Our algorithm preprocesses libraries in almostlinear time, after which the contribution of the library in the complexity of the client analysis is only linear,and only wrt the number of call sites.Third, we prove that combinatorial algorithms for Dyck reachability on general graphs with truly sub-cubic bounds cannot be obtained without obtaining sub-cubic combinatorial algorithms for Boolean MatrixMultiplication, which is a long-standing open problem. Thus we establish that the existing combinatorialalgorithms for Dyck reachability are (conditionally) optimal for general graphs. We also show that the samehardness holds for graphs of constant treewidth.Finally, we provide a prototype implementation of our algorithms for both alias analysis and data-dependenceanalysis. Our experimental evaluation demonstrates that the new algorithms significantly outperform allexisting methods on the two problems, over real-world benchmarks.},
author = {Chatterjee, Krishnendu and Choudhary, Bhavya and Pavlogiannis, Andreas},
issn = {2664-1690},
pages = {37},
publisher = {IST Austria},
title = {{Optimal Dyck reachability for data-dependence and alias analysis}},
doi = {10.15479/AT:IST-2017-870-v1-1},
year = {2017},
}
@misc{5456,
abstract = {We present a new dynamic partial-order reduction method for stateless model checking of concurrent programs. A common approach for exploring program behaviors relies on enumerating the traces of the program, without storing the visited states (aka stateless exploration). As the number of distinct traces grows exponentially, dynamic partial-order reduction (DPOR) techniques have been successfully used to partition the space of traces into equivalence classes (Mazurkiewicz partitioning), with the goal of exploring only few representative traces from each class.
We introduce a new equivalence on traces under sequential consistency semantics, which we call the observation equivalence. Two traces are observationally equivalent if every read event observes the same write event in both traces. While the traditional Mazurkiewicz equivalence is control-centric, our new definition is data-centric. We show that our observation equivalence is coarser than the Mazurkiewicz equivalence, and in many cases even exponentially coarser. We devise a DPOR exploration of the trace space, called data-centric DPOR, based on the observation equivalence.
1. For acyclic architectures, our algorithm is guaranteed to explore exactly one representative trace from each observation class, while spending polynomial time per class. Hence, our algorithm is optimal wrt the observation equivalence, and in several cases explores exponentially fewer traces than any enumerative method based on the Mazurkiewicz equivalence.
2. For cyclic architectures, we consider an equivalence between traces which is finer than the observation equivalence; but coarser than the Mazurkiewicz equivalence, and in some cases is exponentially coarser. Our data-centric DPOR algorithm remains optimal under this trace equivalence.
Finally, we perform a basic experimental comparison between the existing Mazurkiewicz-based DPOR and our data-centric DPOR on a set of academic benchmarks. Our results show a significant reduction in both running time and the number of explored equivalence classes.},
author = {Chalupa, Marek and Chatterjee, Krishnendu and Pavlogiannis, Andreas and Sinha, Nishant and Vaidya, Kapil},
issn = {2664-1690},
pages = {36},
publisher = {IST Austria},
title = {{Data-centric dynamic partial order reduction}},
doi = {10.15479/AT:IST-2017-872-v1-1},
year = {2017},
}
@misc{5559,
abstract = {Strong amplifiers of natural selection},
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak , Martin},
keywords = {natural selection},
publisher = {IST Austria},
title = {{Strong amplifiers of natural selection}},
doi = {10.15479/AT:ISTA:51},
year = {2017},
}
@phdthesis{821,
abstract = {This dissertation focuses on algorithmic aspects of program verification, and presents modeling and complexity advances on several problems related to the
static analysis of programs, the stateless model checking of concurrent programs, and the competitive analysis of real-time scheduling algorithms.
Our contributions can be broadly grouped into five categories.
Our first contribution is a set of new algorithms and data structures for the quantitative and data-flow analysis of programs, based on the graph-theoretic notion of treewidth.
It has been observed that the control-flow graphs of typical programs have special structure, and are characterized as graphs of small treewidth.
We utilize this structural property to provide faster algorithms for the quantitative and data-flow analysis of recursive and concurrent programs.
In most cases we make an algebraic treatment of the considered problem,
where several interesting analyses, such as the reachability, shortest path, and certain kind of data-flow analysis problems follow as special cases.
We exploit the constant-treewidth property to obtain algorithmic improvements for on-demand versions of the problems,
and provide data structures with various tradeoffs between the resources spent in the preprocessing and querying phase.
We also improve on the algorithmic complexity of quantitative problems outside the algebraic path framework,
namely of the minimum mean-payoff, minimum ratio, and minimum initial credit for energy problems.
Our second contribution is a set of algorithms for Dyck reachability with applications to data-dependence analysis and alias analysis.
In particular, we develop an optimal algorithm for Dyck reachability on bidirected graphs, which are ubiquitous in context-insensitive, field-sensitive points-to analysis.
Additionally, we develop an efficient algorithm for context-sensitive data-dependence analysis via Dyck reachability,
where the task is to obtain analysis summaries of library code in the presence of callbacks.
Our algorithm preprocesses libraries in almost linear time, after which the contribution of the library in the complexity of the client analysis is (i)~linear in the number of call sites and (ii)~only logarithmic in the size of the whole library, as opposed to linear in the size of the whole library.
Finally, we prove that Dyck reachability is Boolean Matrix Multiplication-hard in general, and the hardness also holds for graphs of constant treewidth.
This hardness result strongly indicates that there exist no combinatorial algorithms for Dyck reachability with truly subcubic complexity.
Our third contribution is the formalization and algorithmic treatment of the Quantitative Interprocedural Analysis framework.
In this framework, the transitions of a recursive program are annotated as good, bad or neutral, and receive a weight which measures
the magnitude of their respective effect.
The Quantitative Interprocedural Analysis problem asks to determine whether there exists an infinite run of the program where the long-run ratio of the bad weights over the good weights is above a given threshold.
We illustrate how several quantitative problems related to static analysis of recursive programs can be instantiated in this framework,
and present some case studies to this direction.
Our fourth contribution is a new dynamic partial-order reduction for the stateless model checking of concurrent programs. Traditional approaches rely on the standard Mazurkiewicz equivalence between traces, by means of partitioning the trace space into equivalence classes, and attempting to explore a few representatives from each class.
We present a new dynamic partial-order reduction method called the Data-centric Partial Order Reduction (DC-DPOR).
Our algorithm is based on a new equivalence between traces, called the observation equivalence.
DC-DPOR explores a coarser partitioning of the trace space than any exploration method based on the standard Mazurkiewicz equivalence.
Depending on the program, the new partitioning can be even exponentially coarser.
Additionally, DC-DPOR spends only polynomial time in each explored class.
Our fifth contribution is the use of automata and game-theoretic verification techniques in the competitive analysis and synthesis of real-time scheduling algorithms for firm-deadline tasks.
On the analysis side, we leverage automata on infinite words to compute the competitive ratio of real-time schedulers subject to various environmental constraints.
On the synthesis side, we introduce a new instance of two-player mean-payoff partial-information games, and show
how the synthesis of an optimal real-time scheduler can be reduced to computing winning strategies in this new type of games.},
author = {Pavlogiannis, Andreas},
pages = {418},
publisher = {IST Austria},
title = {{Algorithmic advances in program analysis and their applications}},
doi = {10.15479/AT:ISTA:th_854},
year = {2017},
}
@inproceedings{949,
abstract = {The notion of treewidth of graphs has been exploited for faster algorithms for several problems arising in verification and program analysis. Moreover, various notions of balanced tree decompositions have been used for improved algorithms supporting dynamic updates and analysis of concurrent programs. In this work, we present a tool for constructing tree-decompositions of CFGs obtained from Java methods, which is implemented as an extension to the widely used Soot framework. The experimental results show that our implementation on real-world Java benchmarks is very efficient. Our tool also provides the first implementation for balancing tree-decompositions. In summary, we present the first tool support for exploiting treewidth in the static analysis problems on Java programs.},
author = {Chatterjee, Krishnendu and Goharshady, Amir and Pavlogiannis, Andreas},
editor = {D'Souza, Deepak},
issn = {03029743},
location = {Pune, India},
pages = {59 -- 66},
publisher = {Springer},
title = {{JTDec: A tool for tree decompositions in soot}},
doi = {10.1007/978-3-319-68167-2_4},
volume = {10482},
year = {2017},
}
@inproceedings{1011,
abstract = {Pushdown systems (PDSs) and recursive state machines (RSMs), which are linearly equivalent, are standard models for interprocedural analysis. Yet RSMs are more convenient as they (a) explicitly model function calls and returns, and (b) specify many natural parameters for algorithmic analysis, e.g., the number of entries and exits. We consider a general framework where RSM transitions are labeled from a semiring and path properties are algebraic with semiring operations, which can model, e.g., interprocedural reachability and dataflow analysis problems. Our main contributions are new algorithms for several fundamental problems. As compared to a direct translation of RSMs to PDSs and the best-known existing bounds of PDSs, our analysis algorithm improves the complexity for finite-height semirings (that subsumes reachability and standard dataflow properties). We further consider the problem of extracting distance values from the representation structures computed by our algorithm, and give efficient algorithms that distinguish the complexity of a one-time preprocessing from the complexity of each individual query. Another advantage of our algorithm is that our improvements carry over to the concurrent setting, where we improve the bestknown complexity for the context-bounded analysis of concurrent RSMs. Finally, we provide a prototype implementation that gives a significant speed-up on several benchmarks from the SLAM/SDV project.},
author = {Chatterjee, Krishnendu and Kragl, Bernhard and Mishra, Samarth and Pavlogiannis, Andreas},
editor = {Yang, Hongseok},
issn = {03029743},
location = {Uppsala, Sweden},
pages = {287 -- 313},
publisher = {Springer},
title = {{Faster algorithms for weighted recursive state machines}},
doi = {10.1007/978-3-662-54434-1_11},
volume = {10201},
year = {2017},
}
@misc{5445,
abstract = {We consider the quantitative analysis problem for interprocedural control-flow graphs (ICFGs). The input consists of an ICFG, a positive weight function that assigns every transition a positive integer-valued number, and a labelling of the transitions (events) as good, bad, and neutral events. The weight function assigns to each transition a numerical value that represents ameasure of how good or bad an event is. The quantitative analysis problem asks whether there is a run of the ICFG where the ratio of the sum of the numerical weights of good events versus the sum of weights of bad events in the long-run is at least a given threshold (or equivalently, to compute the maximal ratio among all valid paths in the ICFG). The quantitative analysis problem for ICFGs can be solved in polynomial time, and we present an efficient and practical algorithm for the problem. We show that several problems relevant for static program analysis, such as estimating the worst-case execution time of a program or the average energy consumption of a mobile application, can be modeled in our framework. We have implemented our algorithm as a tool in the Java Soot framework. We demonstrate the effectiveness of our approach with two case studies. First, we show that our framework provides a sound approach (no false positives) for the analysis of inefficiently-used containers. Second, we show that our approach can also be used for static profiling of programs which reasons about methods that are frequently invoked. Our experimental results show that our tool scales to relatively large benchmarks, and discovers relevant and useful information that can be used to optimize performance of the programs. },
author = {Chatterjee, Krishnendu and Pavlogiannis, Andreas and Velner, Yaron},
issn = {2664-1690},
pages = {33},
publisher = {IST Austria},
title = {{Quantitative interprocedural analysis}},
doi = {10.15479/AT:IST-2016-523-v1-1},
year = {2016},
}
@misc{5449,
abstract = {The fixation probability is the probability that a new mutant introduced in a homogeneous population eventually takes over the entire population.
The fixation probability is a fundamental quantity of natural selection, and known to depend on the population structure.
Amplifiers of natural selection are population structures which increase the fixation probability of advantageous mutants, as compared to the baseline case of well-mixed populations. In this work we focus on symmetric population structures represented as undirected graphs. In the regime of undirected graphs, the strongest amplifier known has been the Star graph, and the existence of undirected graphs with stronger amplification properties has remained open for over a decade.
In this work we present the Comet and Comet-swarm families of undirected graphs. We show that for a range of fitness values of the mutants, the Comet and Comet-swarm graphs have fixation probability strictly larger than the fixation probability of the Star graph, for fixed population size and at the limit of large populations, respectively.},
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
issn = {2664-1690},
pages = {22},
publisher = {IST Austria},
title = {{Amplification on undirected population structures: Comets beat stars}},
doi = {10.15479/AT:IST-2016-648-v1-1},
year = {2016},
}
@misc{5451,
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
issn = {2664-1690},
pages = {34},
publisher = {IST Austria},
title = {{Strong amplifiers of natural selection}},
doi = {10.15479/AT:IST-2016-728-v1-1},
year = {2016},
}
@misc{5452,
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
issn = {2664-1690},
pages = {32},
publisher = {IST Austria},
title = {{Arbitrarily strong amplifiers of natural selection}},
doi = {10.15479/AT:IST-2017-728-v2-1},
year = {2016},
}
@misc{5453,
author = {Pavlogiannis, Andreas and Tkadlec, Josef and Chatterjee, Krishnendu and Nowak, Martin},
issn = {2664-1690},
pages = {34},
publisher = {IST Austria},
title = {{Arbitrarily strong amplifiers of natural selection}},
doi = {10.15479/AT:IST-2017-749-v3-1},
year = {2016},
}