A program slice consists of the parts of a program that (potentially) affect the values computed at some point of interest Such a point of interest is referred to as a slicing criterion, and is typically specified by a location in the program in combination with a subset of the program’s variables The task of computing program slices is called program slicing The original definition of a program slice was presented by Weiser in 1979 Since then, various slightly different notions of program slices have been proposed, as well as a number of methods to compute them An important distinction is that between a static and a dynamic slice Static slices are computed without making assumptions regarding a program’s input, whereas the computation of dynamic slices relies on a specific test case This survey presents an overview of program slicing, including the various general approaches used to compute slices, as well as the specific techniques used to address a variety of language features such as procedures, unstructured control flow, composite data types and pointers, and concurrency Static and dynamic slicing methods for each of these features are compared and classified in terms of their accuracy and efficiency Moreover, the possibilities for combining solutions for different features are investigated Recent work on the use of compiler-optimization and symbolic execution techniques for obtaining more accurate slices is discussed The paper concludes with an overview of the applications of program slicing, which include debugging, program integration, dataflow testing, and software maintenance

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A Survey of Program Slicing Techniques.

Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts, regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysts, and better evaluation methods for commercial static analyzers for practitioners. We propose a mathematical framework which is generic, because it is not specific to any particular software artifact, and rigorous, because it is based on precise mathematical concepts. We use this framework to propose definitions of several important measurement concepts (size, length, complexity, cohesion, coupling). It does not intend to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalisms and properties we introduce are convenient and intuitive. This framework contributes constructively to a firmer theoretical ground of software measurement.

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Property-based software engineering measurement

Program slicing is applied to the software maintenance problem by extending the notion of a program slice (that originally required both a variable and line number) to a decomposition slice, one that captures all computation on a given variable, i.e., is independent of line numbers. Using the lattice of single variable decomposition slices ordered by set inclusion, it is shown how a slice-based decomposition for programs can be formed. One can then delineate the effects of a proposed change by isolating those effects in a single component of the decomposition. This gives maintainers a straightforward technique for determining those statements and variables which may be modified in a component and those which may not. Using the decomposition, a set of principles to prohibit changes which will interfere with unmodified components is provided. These semantically consistent changes can then be merged back into the original program in linear time. >

Using program slicing in software maintenance

We define and apply two new measures of object-oriented class cohesion to a reasonably large C++ system. We find that most of the classes are quite cohesive, but that the classes that are reused more frequently via inheritance exhibit clearly lower cohesion.

https://dl.acm.org/doi/pdf/10.1145/223427.211856

Cohesion and reuse in an object-oriented system

It represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use.

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Computational Thinking 計算論的思考

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research.

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Introductory programming: a systematic literature review

We examine the functional cohesion of procedures using a data slice abstraction. Our analysis identifies the data tokens that lie on more than one slice as the "glue" that binds separate components together. Cohesion is measured in terms of the relative number of glue tokens, tokens that lie on more than one data slice, and super-glue tokens, tokens that lie on all data slices in a procedure, and the adhesiveness of the tokens. The intuition and measurement scale factors are demonstrated through a set of abstract transformations. >

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Measuring functional cohesion

Previous work has shown that a relationship exists between cohesion and the slice profile of a program. The authors explore the use of several metrics based on such slice profiles to give a quantitative estimate of the level of cohesion in a module. Example modules are used to analyze the behavior of the metric values as the modules are modified such that the cohesion is changed. The sensitivity of the metrics to the various types of changes is discussed. >

Slice based metrics for estimating cohesion

High module cohesion is often suggested as a desirable property of program modularity. The subjective nature of the definition of cohesion, however, can make it difficult to use in practice. In this paper, we examine the relationship between the data flow in a module and its level of cohesion using aprocessing element flow graph (PFG). Based on these PFG's, we regroup the original seven levels of cohesion into four classifications, Slice profiles are then defined by generating slices for all output variables of a module. A relationship is then shown between these slice profiles and the, PFG used to indicate levels of cohesion. It is suggested that these slice profiles can be used to determine more easily the cohesiveness of a module.

The Relationship Between Slices And Module Cohesion

The basis for measuring many attributes in the physical world, such as size and mass, is fairly obvious when compared to the measurement of software attributes. Software has a very complex structure, and this makes it difficult to define meaningful measures that actually quantify attributes of interest. Program slices provide an abstraction that can be used to define important software attributes that can serve as a basis for measurement. We have successfully used program slices to define objective, meaningful, and valid measures of cohesion. Previously, cohesion was viewed as an attribute that could not be objectively measured; cohesion assessment relied on subjective evaluations. In this paper we review the original slice-based cohesion measures defined to measure functional cohesion in the procedural paradigm as well as the derivative work aimed at measuring cohesion in other paradigms and situations. By viewing software products at differing levels of abstraction or granularity, it is possible to define measures which are available at different points in the software life cycle and/or suitable for varying purposes.

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Linda Ott

Papers

Introductory programming: a systematic literature review

Measuring functional cohesion

Slice based metrics for estimating cohesion

The Relationship Between Slices And Module Cohesion

Program slices as an abstraction for cohesion measurement