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88
Analyzing regression test selection techniques
 IEEE Transactions on Software Engineering
, 1996
"... AbstractRegression testing is a necessary but expensive maintenance activity aimed at showing that code has not been adversely affected by changes. Regression test selection techniques reuse tests from an existing test suite to test a modified program. Many regression test selection techniques have ..."
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Cited by 161 (40 self)
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AbstractRegression testing is a necessary but expensive maintenance activity aimed at showing that code has not been adversely affected by changes. Regression test selection techniques reuse tests from an existing test suite to test a modified program. Many regression test selection techniques have been proposed; however, it is difficult to compare and evaluate these techniques because they have different goals. This paper outlines the issues relevant to regression test selection techniques, and uses these issues as the basis for a framework within which to evaluate the techniques. We illustrate the application of our framework by using it to evaluate existing regression test selection techniques. The evaluation reveals the strengths and weaknesses of existing techniques, and highlights some problems that future work in this area should address. Index TermsSoftware maintenance, regression testing, selective retest, regression test selection. 1
A DavisPutnam Based Enumeration Algorithm for Linear PseudoBoolean Optimization
, 1995
"... The DavisPutnam enumeration method (DP) has recently become one of the fastest known methods for solving the clausal satisfiability problem of propositional calculus. We present a generalization of the DPprocedure for solving the satisfiability problem of a set of linear pseudoBoolean (or 01) ..."
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Cited by 102 (1 self)
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The DavisPutnam enumeration method (DP) has recently become one of the fastest known methods for solving the clausal satisfiability problem of propositional calculus. We present a generalization of the DPprocedure for solving the satisfiability problem of a set of linear pseudoBoolean (or 01) inequalities. We extend the method to solve linear 01 optimization problems, i.e. optimize a linear pseudoBoolean objective function w.r.t. a set of linear pseudoBoolean inequalities. The algorithm compares well with traditional linear programming based methods on a variety of standard 01 integer programming benchmarks. Keywords 01 Integer Programming; Propositional Calculus; Enumeration Contents 1 Introduction 1 2 Preliminaries 1 3 The Classical DavisPutnam Procedure 3 4 DavisPutnam for Linear PseudoBoolean Inequalities 5 5 Optimizing with PseudoBoolean DavisPutnam 7 6 Implementation 8 7 Heuristics 10 8 Computational Results 10 9 Conclusion 12 1 Introduction The DavisPutn...
Gomory Cuts Revisited
, 1996
"... In this paper, we investigate the use of Gomory's mixed integer cuts within a branchandcut framework. It has been argued in the literature that "a marriage of classical cutting planes and tree search is out of the question as far as the solution of largescale combinatorial optimization problems i ..."
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Cited by 44 (5 self)
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In this paper, we investigate the use of Gomory's mixed integer cuts within a branchandcut framework. It has been argued in the literature that "a marriage of classical cutting planes and tree search is out of the question as far as the solution of largescale combinatorial optimization problems is concerned" [16] because the cuts generated at one node of the search tree need not be valid at other nodes. We show in this paper that it is possible, using a simple lifting procedure, to make Gomory cuts generated in a node of the enumeration tree globally valid in the case of mixed 01 programs. Other issues addressed in this paper are of computational nature, such as strategies for generating the cutting planes, deciding between branching and cutting, etc. The result is a robust mixed integer program solver. 1 Introduction In the late fifties and early sixties, Gomory [6], [7], [8] proposed to solve integer programs by using cutting planes, thus reducing integer programming to the solu...
The convex hull of two core capacitated network design problems
 MATHEMATICAL PROGRAMMING
, 1993
"... The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed pointtopoint demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs ..."
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Cited by 43 (0 self)
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The network loading problem (NLP) is a specialized capacitated network design problem in which prescribed pointtopoint demand between various pairs of nodes of a network must be met by installing (loading) a capacitated facility. We can load any number of units of the facility on each of the arcs at a specified arc dependent cost. The problem is to determine the number of facilities to be loaded on the arcs that will satisfy the given demand at minimum cost. This paper studies two core subproblems of the NLP. The first problem, motivated by a Lagrangian relaxation approach for solving the problem, considers a multiple commodity, single arc capacitated network design problem. The second problem is a three node network; this specialized network arises in larger networks if we aggregate nodes. In both cases, we develop families of facets and completely characterize the convex hull of feasible solutions to the integer programming formulation of the problems. These results in turn strengthen the formulation of the NLP.
MIP: Theory And Practice  Closing The Gap
 System Modelling and Optimization: Methods, Theory, and Applications
, 2000
"... this paper, now include cuttingplane capabilities as well as other ideas from the backlog of accumulated theory. As suggested by the title of this paper, the gap between theory and practice is indeed closing ..."
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Cited by 42 (1 self)
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this paper, now include cuttingplane capabilities as well as other ideas from the backlog of accumulated theory. As suggested by the title of this paper, the gap between theory and practice is indeed closing
A Dynamic Programming Approach for Consistency and Propagation for Knapsack Constraints
 Annals of Operations Research
, 2001
"... Knapsack constraints are a key modeling structure in constraint programming. These constraints are normally handled with simple bounding arguments. We propose a dynamic programming structure to represent these constraints. With this structure, we show how to achieve hyperarc consistency, to determi ..."
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Cited by 37 (0 self)
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Knapsack constraints are a key modeling structure in constraint programming. These constraints are normally handled with simple bounding arguments. We propose a dynamic programming structure to represent these constraints. With this structure, we show how to achieve hyperarc consistency, to determine infeasibility before all variables are set, to generate all solutions quickly, and to update the structure after domain reduction. Preliminary testing on a dicult set of multiple knapsack instances shows signicant reduction in branching, though an eective implementation is needed in order to reduce computation time. Keywords: Global Constraints, Dynamic Programming, Knapsack Constraints 1.
Implementing the DantzigFulkersonJohnson Algorithm for Large Traveling Salesman Problems
, 2003
"... Dantzig, Fulkerson, and Johnson (1954) introduced the cuttingplane method as a means of attacking the traveling salesman problem; this method has been applied to broad classes of problems in combinatorial optimization and integer programming. In this paper we discuss an implementation of Dantzig et ..."
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Cited by 36 (6 self)
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Dantzig, Fulkerson, and Johnson (1954) introduced the cuttingplane method as a means of attacking the traveling salesman problem; this method has been applied to broad classes of problems in combinatorial optimization and integer programming. In this paper we discuss an implementation of Dantzig et al.'s method that is suitable for TSP instances having 1,000,000 or more cities. Our aim is to use the study of the TSP as a step towards understanding the applicability and limits of the general cuttingplane method in largescale applications.
A Polyhedral Approach to Multicommodity Survivable Network Design
 Numerische Mathematik
, 1993
"... The design of costefficient networks satisfying certain survivability ..."
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Cited by 34 (0 self)
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The design of costefficient networks satisfying certain survivability
Karmarkar's Algorithm and Combinatorial Optimization Problems
, 1988
"... Branchandcut methods are very successful techniques for solving a wide variety of integer programming problems, and they can provide a guarantee of optimality. We describe how a branchandcut method can be tailored to a specific integer programming problem, and how families of general cutting pla ..."
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Cited by 33 (6 self)
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Branchandcut methods are very successful techniques for solving a wide variety of integer programming problems, and they can provide a guarantee of optimality. We describe how a branchandcut method can be tailored to a specific integer programming problem, and how families of general cutting planes can be used to solve a wide variety of problems. Other important aspects of successful implementations are discussed in this chapter. The area of branchandcut algorithms is constantly evolving, and it promises to become even more important with the exploitation of faster computers and parallel computing. 1
Pueblo: A hybrid pseudoboolean SAT solver
 Journal on Satisfiability, Boolean Modeling and Computation
, 2006
"... This paper introduces a new hybrid method for efficiently integrating PseudoBoolean (PB) constraints into generic SAT solvers in order to solve PB satisfiability and optimization problems. To achieve this, we adopt the cuttingplane technique to draw inferences among PB constraints and combine it w ..."
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Cited by 31 (0 self)
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This paper introduces a new hybrid method for efficiently integrating PseudoBoolean (PB) constraints into generic SAT solvers in order to solve PB satisfiability and optimization problems. To achieve this, we adopt the cuttingplane technique to draw inferences among PB constraints and combine it with generic implication graph analysis for conflictinduced learning. Novel features of our approach include a lightweight and efficient hybrid learning and backjumping strategy for analyzing PB constraints and CNF clauses in order to simultaneously learn both a CNF clause and a PB constraint with minimum overhead and use both to determine the backtrack level. Several techniques for handling the original and learned PB constraints are introduced. Overall, our method benefits significantly from the pruning power of the learned PB constraints, while keeping the overhead of adding them into the problem low. In this paper, we also address two other methods for solving PB problems, namely Integer Linear Programming (ILP) and preprocessing to CNF SAT, and present a thorough comparison between them and our hybrid method. Experimental comparison of our method against other hybrid approaches is also demonstrated. Additionally, we provide details of the MiniSATbased implementation of our solver Pueblo to enable the reader to construct a similar one.