S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. SIGPLAN Notices, 24(7):28--40, July 1989.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....is the incorporation of client analysis information into procedure level pointer alias summaries [81] Clientdriven pointer analyses may also be able to selectively apply more aggressive approaches to obtaining precision, such as those of [68] 4. 6 Heap Modeling Shape analysis algorithms [53, 43, 9, 19, 36, 35, 18, 74, 28, 29, 87, 88, 89, 103, 21, 54] have demonstrated high precision, over schemes that name objects based on allocation site (as in [47, 44, 83, 43, 9] but their scalability to even medium programs is uncertain. Mooly Sagiv summarizes the current state of the eld: Although I believe we are making good progress, in all honesty, ....

....apply more aggressive approaches to obtaining precision, such as those of [68] 4. 6 Heap Modeling Shape analysis algorithms [53, 43, 9, 19, 36, 35, 18, 74, 28, 29, 87, 88, 89, 103, 21, 54] have demonstrated high precision, over schemes that name objects based on allocation site (as in [47, 44, 83, 43, 9]) but their scalability to even medium programs is uncertain. Mooly Sagiv summarizes the current state of the eld: Although I believe we are making good progress, in all honesty, we should say that we are not there yet. Tom Reps observes, We have certainly not come to the end of the line in ....

S. Horwitz, P. Pfeier, and T. W. Reps. Dependence analysis for pointer variables. In Proceedings of the ACM SIGPLAN'89 Conference on Programming Language Design and Implementation, pages 28-40, 21-23 June. SIGPLAN Notices 24(7), July 1989.

....internal representations. For example, dependence graphs, developed in connection with aggressive optimizing compilers [7] have been suggested for use in a variety of alternative applications. These include program slicing [4, 10, 17, 18] whole program documentation [3] heap variable modeling [12]. A common operation performed by tools is graph reachability. For example, the question Can procedure P (transitively) call procedure Q is a simple graph reachability question on the program s call graph. Similarly, the question Does the value assigned to x at statement s reach a use of x at ....

S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. In Proceedings of the ACM SIGPLAN 89 Conference on Programming Language Design and Implementation, (Portland, OR, June 21-23, 1989.

.... dependence cache slicing that collects data flow information. 3. Dependence Cache Slicing 3.1. Overview Collecting the precise data dependence relations of variables with a static method is difficult in general, although the control dependence relations are fairly easily collected statically [6, 7, 10]. Once we execute a program with an input data set, we are able to collect actual dependence relations between statements, although the penalty for collecting precise dependence relations has a fairly high overhead. Here, we propose the Dependence Cache Slicing method, for a good compromise ....

....However, such a method Also, this result suggests that the execution overhead for dynamic slicing is unacceptably huge. requires a similarity checking of DDG at execution time, so the run time overhead is serious. Researches exist in which pointer and array variables are statically analyzed [6, 7]. Much of this research tries to statically determine possible aliases of pointer variables and array elements, but these still remain the uncertain cases [16] Since our dependence cache slicing uses dynamic information, we can get reasonable slice precision with affordable execution overhead. ....

Horwitz, S., Pfeiffer, P., and Reps, T.: "Dependence Analysis for Pointer variables", Proceedings of SIGPLAN '89 Conference on Programming Language Design and Implementation, pp.28--40, SIGPLAN Notices Vol. 24, No. 6 (1989).

....objects: Landi and Ryder use the access paths as names for anonymous heap objects. They k limit the access paths to have a finite set of object names, in the presence of recursive structures. Choi et al. name the heap objects by using the place in the program where they are created, as in [24]. They use procedure strings and k limiting of recursive structures [26] to improve their naming scheme. These names are then used in alias calculation. We differ from these approaches in that we claim that the stack and heap problems can and should be separated. The fact that the analyses can be ....

S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. In Proceedings of the SIGPLAN '89 Symposium on Programming Language Design and Implementation, pages 28--40, June 1989.

....locations. The result is a useful view in itself, but is also a preliminary requirement for successive computations often used in program understanding. Such algorithms have traditionally been developed in the framework of optimizing compilers and program parallelization and vectorization [16] [27], 28] Recently they have been investigated in the context of software maintenance, particularly in problems related to slicing [29] 45] Different flow and context sensitive algorithms have been developed to obtain accurate results, at the expense of time and memory complexity [16] 36] The ....

S. Horwitz, P. Pfeiffer, T. Reps, "Dependence Analysis for Pointer Variables", SIGPLAN Notices, vol. 24, n. 7, pp.28-40, 1989.

....of functions pointed to by every function pointer. Thus new edges are added to the call graph, eventually connecting some portions of the call graph that may result disconnected if the edges associated to calls through function pointers were ignored. In literature several points to algorithms [5][8][9] have been proposed in the framework of optimizing compilers and program parallelization and vectorization, to provide information about memory locations referenced by pointers. Recently the achieved knowledge about these algorithms has been applied in the field of software maintenance, ....

....to determine the set of stack or heap allocated objects, data members and variables (i.e. locations) that each single pointer could access. Points to analysis (PTA) is aimed at determining the set of locations a location may point to. Several algorithms have been proposed to perform PTA [1] 5][8][9] 12] 13] 14] which basically differ for the accuracy in reached results, obtained at the price of computational complexity. Since the analysis is statically performed, the results are computed with a conservative approach: for a given pointer, the set of identified locations approximates the ....

S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. SIGPLAN Notices, 24(7):28--40, 1989.

....control all possible linkages, a flow analyzer can be used to determine the code fragments that may be affected by some code change elsewhere. Flow analysis algorithms, which have traditionally been developed in the framework of optimizing compilers and program parallelization and vectorization [6, 12, 13, 14], have recently been investigated in the context of software maintenance, particularly in problems related to slicing and pointer analysis [2, 5, 11, 15, 21, 20, 22] Gallagher and Lyle [9] introduced the notion of decomposition slice as a useful technique to modifying the code, avoiding the ....

S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. SIGPLAN Notices, 24(7):28--40, 1989.

....de nitions analyzer can be used to determine the code fragments that may have de ned the value of a variable reaching a given program point. Flow analysis algorithms, which have traditionally been developed in the framework of optimizing compilers and program parallelization and vectorization [9,16,17,19], have recently been investigated in the context of software maintenance and program understanding. Their application ranges from slicing to change impact analysis and many tools that perform architecture recovery [10,11,15] and concept extraction [18] also depend on data dependence computation. ....

S. Horwitz, P. Pfeier, T. Reps, \Dependence Analysis for Pointer Variables", SIGPLAN Notices, vol. 24, n. 7, pp.28-40, 1989.

....object names obtainable by following links in a recursive data structure, only maintaining the first k dereferences, a process known as k limiting. Others have suggested less naive ways of restricting the namespace while obtaining more accurate aliases of heap stored objects [CWZ90, Deu94, HPR89, LH88, HN90, HHN92, GH96a, GH96b, SRW98] One di#culty with k limiting is that it loses information about the su#x of an object name. With 2 limiting, the alias #p f g h, x# is represented by #p f g#, x#. However this klimited object name also represents a set of object names, e.g. ....

....aliasing technique used. Since the focus of this paper is the MODC schema, the recent work in pointer analysis is merely summerized here. Recently, there have been many investigations of pointer aliasing algorithms which vary in cost and precision. Several concentrate on aliases in heap storage [HPR89, CWZ90, Deu94, HN90, GH96a, GH96b, JM82a, LH88, SRW98] Others calculate flow insensitive aliases with recent emphasis on algorithm scalability on very large programs (i.e. one million lines of code) Cou86, Gua88, BCCH94, And94, SH97b, Ste96b, Wei80, ZRL96, HP98, LH99, RC00, Das00, FRD00, ....

S. Horwitz, P. Pfei#er, and T. Reps. Dependence analysis for pointer variables. In Proceedings of the ACM SIGPLAN Symposium on Compiler Construction, pages 28--40, June 1989.

....belongs to the value attribute of a variable definition is called a substitutor of the variable definition. Each substitutor is characterized by its status: d definite substitutor or p possible substitutor. The problem of finding the substitutors is known as the pointer aliasing problem [1, 2, 7, 12, 11]. This problem can be solved by using the set of abstract variables as a memory model (store based approach [4] Another approach called the path access based approach [1, 12, 11] is more widely used. The value of a variable of the scalar type considered as the attribute of the variable ....

S. Horvitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. Conf. Prog. Lang. Design and Implem., SIGPLAN Notices, 24(7):28--40, 1989. 7 It is described at http://www.xds.ru/osa/must.html#fst 6

....operator, union types and parameter passing allow type system violation. Some attempts have been made to solve some of these problems. These works fall into two categories: 1. works done on pointer and dynamically allocated data structures. Many of them are not applied to a particular language ([7, 10] among others) but rare are those directly applied to C [5] In these works, major problems we cited, such as pointer arithmetic or side effects in expressions, are not addressed. 2. works dedicated to the C language and some of the problems we mentioned. A compiler for a multi processor and ....

....of simple variables, hence the definition: Definition 1 A variable (addresses hi; ki) is in A n iff the declaration of i contains n stars. In other words, there is n 1 memory references (implicit or explicit with the operator) to get the pointed value. Let us give some examples: int ti[10] ; h ti; 0i 2 A 0 int tpi[10] h tpi; 0i 2 A 1 int ( pti) 10] h pti; 0i 2 A 1 int ( ptpi) 10] h ptpi; 0i 2 A 2 int ( tpti[10] 20] h tpti; 0i 2 A 1 To be exhaustive, we must speak of virtual arrays: function parameters declared as n dimensions arrays are not true arrays. They are ....

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Horwitz S., Pfeiffer P., Reps T., Dependence Analysis for Pointer Variables. ACM-PLDI89, 1989

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S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. In SIGPLAN Conference on Programming Languages Design and Implementation, pages 28--40, New York, NY, 1989. ACM Press.

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S. Horwitz, P. Pfei#er, and T. Reps. Dependence analysis for pointer variables. In Prog. Lang. Design and Impl., pages 28--40, 1989. 17

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S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. In SIGPLAN Conference on Programming Languages Design and Implementation, pages 28--40, New York, NY, 1989. ACM Press.

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S. Horwitz, P. Pfeier, and T. Reps. Dependence analysis for pointer variables. In 1989. ACM Press.

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Horwitz, S., Pfeiffer, P., and Reps, T., "Dependence analysis for pointer variables," Proceedings of the SIGPLAN 89 Conference on Programming Language Design and Implementation, (Portland, OR, June 21-23, 1989), ACM SIGPLAN Notices 24(7) pp. 28-40 (July 1989).

....and data types found in full fledged programming languages. Certainly one area for further work is to extend the integration method to handle additional programming language constructs. We have recently made progress towards handling languages with procedure calls [3] and pointer valued variables [1]. Other language constructs, such as declarations, break statements, and I O statements, as well as other data types will be addressed in the future. It remains to be seen how often integrations of real changes to programs of substantial size can be automatically accommodated by the integration ....

Horwitz, S., Pfeiffer, P., and Reps, T., "Dependence analysis for pointer variables," Proceedings of the ACM SIGPLAN 89 Conference on Programming Language Design and Implementation, (Portland, OR, June 21-23, 1989), ACM SIGPLAN Notices 24(7) pp. 28-40 (July 1989).

....and constructs found in real world programming languages, 20 Years of the ACM SIGPLAN Conference on Programming Language Design and Implementation (1979 1999) A Selection, 2003. Copyright 2003 ACM 1 58113 623 4 . 5.00. including arrays [4, 50, 29, 18, 32] reference parameters [20] pointers [28, 19, 10], non structured control flow [2, 11, 1, 46, 27] and threads [26, 15, 30] Context Sensitive Program Analysis Nowadays the interprocedural slicing method of the PLDI 88 paper would be termed a context sensitive interprocedural slicing method. In general, a context sensitive analysis is one in ....

S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. In Conf. on Prog. Lang. Design and Impl., pages 28--40, New York, NY, 1989. ACM Press.

....AW93, PCK93, Zap99] programs. For example, it can be utilized to check at compile time for the absence of certain types of memory management errors, such as memory leakage or dereference of null pointers [DRS98, DRS00] In the past two decades, many shape analysis algorithms have been developed [JM81, JM82, LH88, HPR89, CWZ90, Str92, AW93, PCK93, Wan94, SRW98]. The quality , and thus the usability, of the information these algorithms can determine relies on the assumption that the number of variables is xed. When this assumption is violated, as is the case when recursive procedures are used, the quality of the results, as well as the cost, of these ....

S. Horwitz, P. Pfeier, and T. Reps. Dependence analysis for pointer variables. In SIGPLAN Conf. on Prog. Lang. Design and Impl., pages 28-40, New York, NY, 1989. ACM Press. 56

.... INTRODUCTION In the past two decades, many shape analysis algorithms have been developed that can automatically create di erent classes of shape descriptors for programs that perform destructive updating on dynamically allocated storage [Jones and Muchnick 1981; 1982; Larus and Hil nger 1988; Horwitz et al. 1989; Chase et al. 1990; Stransky 1992; Assmann and Weinhardt 1993; Plevyak et al. 1993; Wang 1994; Sagiv et al. 1998] A common feature of these algorithms is that they represent the set of possible memory states ( stores ) that arise at a given point in the program by shape graphs, in which heap ....

....This paper presents a parametric framework for shape analysis. The framework can be instantiated in di erent ways to create shape analysis algorithms that provide di erent degrees of precision. The essence of a number of previous shapeanalysis algorithms, including [Jones and Muchnick 1981; 1982; Horwitz et al. 1989; Chase et al. 1990; Stransky 1992; Plevyak et al. 1993; Wang 1994; Sagiv et al. 1998] can be viewed as instances of this framework. Other instantiations of the framework yield new shape analysis algorithms that obtain more precise information than previous work. A parametric framework must ....

[Article contains additional citation context not shown here]

Horwitz, S., Pfeiffer, P., and Reps, T. 1989. Dependence analysis for pointer variables. In SIGPLAN Conf. on Prog. Lang. Design and Impl. ACM Press, New York, NY, 28-40.

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S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. SIGPLAN Notices, 24(7):28--40, July 1989.

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Horwitz, S., Pfeiffer, P., Reps, T.W.: Dependence analysis for pointer variables. In: PLDI'89, 1989, 28--40.

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S. Horwitz, P. Pfeiffer and T. Reps, "Dependence Analysis for Pointer Variables", Proceeding of the 1989 Conference on Programming Language Design and Implementation, SIGPLAN Notices 24, 7 (July 1989), 28-40.

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S. Horwitz, P. Pfeier, and T. Reps. Dependence analysis for pointer variables. In Proceedings of the ACM SIGPLAN 89 Conference on Programming Language Design and Implementation, (Portland, OR, June 21-23, 1989.

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S. Horwitz, P. Pfeiffer, and T. Reps. Dependence analysis for pointer variables. In PLDI [PLDI1989], pages 28--40.

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