物件導向軟體之架構(Object-Oriented Software Construction)探討

ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

Hofmann and Jost have presented a heap space analysis [1] that finds linear space bounds for many functional programs. It uses an amortised analysis: assigning hypothetical amounts of free space (called potential) to data structures in proportion to their sizes using type annotations. Constraints on these annotations in the type system ensure that the total potential assigned to the input is an upper bound on the total memory required to satisfy all allocations.

We describe a related system for bounding the stack space requirements which uses the depth of data structures, by expressing potential in terms of maxima as well as sums. This is achieved by adding extra structure to typing contexts (inspired by O'Hearn's bunched typing [2]) to describe the form of the bounds. We will also present the extra steps that must be taken to construct a typing during the analysis.

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Amortised Memory Analysis Using the Depth of Data Structures

We study the problem of automatically analyzing the worst-case resource usage of procedures with several arguments. Existing automatic analyses based on amortization or sized types bound the resource usage or result size of such a procedure by a sum of unary functions of the sizes of the arguments.In this article we generalize this to arbitrary multivariate polynomial functions thus allowing bounds of the form mn which had to be grossly overestimated by m2 p n2 before. Our framework even encompasses bounds like ∑i,j≤ n mi mj where the mi are the sizes of the entries of a list of length n.This allows us for the first time to derive useful resource bounds for operations on matrices that are represented as lists of lists and to considerably improve bounds on other superlinear operations on lists such as longest common subsequence and removal of duplicates from lists of lists. Furthermore, resource bounds are now closed under composition which improves accuracy of the analysis of composed programs when some or all of the components exhibit superlinear resource or size behavior.The analysis is based on a novel multivariate amortized resource analysis. We present it in form of a type system for a simple first-order functional language with lists and trees, prove soundness, and describe automatic type inference based on linear programming.We have experimentally validated the automatic analysis on a wide range of examples from functional programming with lists and trees. The obtained bounds were compared with actual resource consumption. All bounds were asymptotically tight, and the constants were close or even identical to the optimal ones.

Multivariate amortized resource analysis

Software model checking with abstraction refinement is emerging as a practical approach to verify industrial software systems. Its distinguishing characteristics lie in the way it applies logical reasoning to deal with abstraction. It is therefore natural to investigate whether and how the use of a constraint-based programming language may lead to an elegant and concise implementation of a practical tool. In this paper we describe the outcome of our investigation. Using a Prolog system together with Constraint Logic Programming extensions as the implementation platform of our choice we have built such a tool, called ARMC (for Abstraction Refinement Model Checking), which has already been used for practical verification.

ARMC: the logical choice for software model checking with abstraction refinement

Cost analysis of Java bytecode is complicated by its unstructured control flow, the use of an operand stack and its object-oriented programming features (like dynamic dispatching) This paper addresses these problems and develops a generic framework for the automatic cost analysis of sequential Java bytecode Our method generates cost relations which define at compile-time the cost of programs as a function of their input data size To the best of our knowledge, this is the first approach to the automatic cost analysis of Java bytecode

/pdf/cost-analysis-of-java-bytecode-ochzl6ty5j.pdf

Cost analysis of java bytecode

The classical approach to automatic cost analysis consists of two phases. Given a program and some measure of cost, the analysis first produces cost relations (CRs), i.e., recursive equations which capture the cost of the program in terms of the size of its input data. Second, CRs are converted into closed-form, i.e., without recurrences. Whereas the first phase has received considerable attention, with a number of cost analyses available for a variety of programming languages, the second phase has been comparatively less studied. This article presents, to our knowledge, the first practical framework for the generation of closed-form upper bounds for CRs which (1) is fully automatic, (2) can handle the distinctive features of CRs, originating from cost analysis of realistic programming languages, (3) is not restricted to simple complexity classes, and (4) produces reasonably accurate solutions. A key idea in our approach is to view CRs as programs, which allows applying semantic-based static analyses and transformations to bound them, namely our method is based on the inference of ranking functions and loop invariants and on the use of partial evaluation.

Closed-Form Upper Bounds in Static Cost Analysis

Cost analysis of object-oriented bytecode programs

The classical approach to automatic cost analysis consists of two phases. Given a program and some measure of cost, we first produce recurrence relations(RRs) which capture the cost of our program in terms of the size of its input data. Second, we convert such RRs into closed form(i.e., without recurrences). Whereas the first phase has received considerable attention, with a number of cost analyses available for a variety of programming languages, the second phase has received comparatively little attention. In this paper we first study the features of RRs generated by automatic cost analysis and discuss why existing computer algebra systems are not appropriate for automatically obtaining closed form solutions nor upper bounds of them. Then we present, to our knowledge, the first practical framework for the fully automatic generation of reasonably accurate upper bounds of RRs originating from cost analysis of a wide range of programs. It is based on the inference of ranking functionsand loop invariantsand on partial evaluation.

/pdf/automatic-inference-of-upper-bounds-for-recurrence-relations-3fmytvm3li.pdf

Automatic Inference of Upper Bounds for Recurrence Relations in Cost Analysis

This paper describes the architecture of costa , an abstract interpretation based cos t and t ermination a nalyzer for Java bytecode. The system receives as input a bytecode program, (a choice of) a resource of interest and tries to obtain an upper bound of the resource consumption of the program. costa provides several non-trivial notions of cost, as the consumption of the heap, the number of bytecode instructions executed and the number of calls to a specific method. Additionally, costa tries to prove termination of the bytecode program which implies the boundedness of any resource consumption. Having cost and termination together is interesting, as both analyses share most of the machinery to, respectively, infer cost upper bounds and to prove that the execution length is always finite (i.e., the program terminates). We report on experimental results which show that costa can deal with programs of realistic size and complexity, including programs which use Java libraries. To the best of our knowledge, this system provides for the first time evidence that resource usage analysis can be applied to a realistic object-oriented, bytecode programming language.

/pdf/costa-design-and-implementation-of-a-cost-and-termination-1ast9u1nqo.pdf

Puri Arenas

Papers

Cost analysis of java bytecode

Closed-Form Upper Bounds in Static Cost Analysis

Cost analysis of object-oriented bytecode programs

Automatic Inference of Upper Bounds for Recurrence Relations in Cost Analysis

COSTA: Design and Implementation of a Cost and Termination Analyzer for Java Bytecode