N. Fenton. Software measurement: A necessary scientific basis. IEEE Trans. Softw. Eng., 20(3), 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....properties is complete, i.e. any pair of abstractions can be ordered by using the stated properties. Sets of generic properties do not necessarily provide a total order among entities, as not all abstractions may be comparable with respect to a particular measurement attribute [25] [24], so only a partial order can be obtained [33] Context dependent properties further constrain the order relation among entities in such a way that a total order can be obtained, though this is not true in general. For instance, a total ordering of the entities may not be obtained when dealing ....

....obtained, though this is not true in general. For instance, a total ordering of the entities may not be obtained when dealing with multidimensional attributes, or several aspects of the same attribute (e.g. data flow and control flow complexity, or even control flow complexity alone, as shown in [24]) 5.4 Define Independent Measures For each attribute of an entity, measures are defined by using the abstractions elements and relationships, and are checked against the attribute s generic and context dependent properties. Management and resource constraints are taken into account for ....

N. Fenton, "Software Measurement: A Necessary Scientific Basis," IEEE Trans. Software Eng., vol. 20, no. 3, pp. 199-206, Mar. 1994.

....were never conveniently validated through comprehensive empirical efforts, partly due to the difficulties in getting adequate samples for that validation. A discussion on the research difficulties in the software measurement area (which is, of course, crucial to estimation) can be found in [11]. The shift to a new approach to software development requires new estimation models to better capture the essence of CBD. Due to the novelty of CBD and related estimation models, there is still a lack of past experience in which one can support his 3 estimation efforts. An example of a face ....

N. Fenton, "Software Measurement: A Necessary Scientific Basis," IEEE Transactions on Software Engineering, vol. 20, pp. 199-206, 1994.

....cohesion; we defer the treatment of abstract or data cohesion to future work. Measurement techniques used in the physical sciences guide us in our development of functional cohesion measures. Aspects of functional cohesion are internal product attributes related to properties of programs [11]. Our objectives include the development of (1) a good model of functional cohesion, and (2) measures that use the model to quantify functional cohesion. For cohesion measures to provide meaningful measurements, they must be rigorously defined, accurately reflect well understood software ....

....We develop cohesion measures in terms of the slice model, and validate the measures by demonstrating that they are consistent with expected cohesion model orderings and determining their scale properties. Thus, we appeal to the representation condition of measurement theory [10, pp. 25 26] [11], which requires that our intuition about the relative quantity of functional cohesion is preserved by a cohesion measure. To be measurable on an ordinal scale, an attribute of cohesion must impart an ordering on the model. That is, the model of a procedure with more of one cohesion attribute ....

N. Fenton, "Software measurement: A necessary scientific ba- sis," IEEE Trans. Software Eng., vol. 20, no. 3, pp. 199-206, 1994.

....We start by considering the reasons why measurement of software was introduced, then we describe what are the attributes of software and of the software process that are the objects of measurement. A general theory of measurement is presented that was first applied to software measurement by [Fenton 94] The two types of metrics validation, empirical and theoretical, are discussed. Then a number of metrics for the different development phases is presented in details. We discuss function points for the requirements phase and the metrics for choesion and coupling defined in [Briand et al. 94] for ....

....suite of metrics for OO designs by [Chidameber, Kemerer 94] Lines of Code [Conte et al. 86] Software Science [Halstead 75] and Cyclomatic Number [McCabe 76] In Section 7 we summarize the main points treated 2. Uses of measurement Measurement has two broad uses: for assessment and prediction [Fenton 94] Examples of using metrics for assessment are: 1. monitoring the advancement of a project in order to take the appropriate corrective decisions, 2. evaluating a software product or process. When using measurement for prediction, the value of an attribute A is given by a mathematical model, ....

[Article contains additional citation context not shown here]

N. Fenton, Software Measurement: a Necessary Scientific Basis, IEEE Trans. Software Eng., 20, 1994, pp. 199-206.

....results from several quantitative analyses of the archival data from the Apache project. The measures we derive from these data are well suited to address our research questions [4] however, they may be unfamiliar to many readers since they are not software metrics that are in wide use, e.g. [6, 10]. For this reason, we provide data from several commercial projects, to give the reader some sense of what kinds of results might be expected. Although we picked several commercial projects that are reasonably close to Apache, none is a perfect match, and the reader should not infer that the ....

FENTON, N. 1994. Software Measurement: A Necessary Scientific Basis. IEEE Transactions on Software Engineering, vol. 20, 199-206.

.... should include in the definition of the quality and which criteria should associated with specific factors, and additionally they dont explicitly specify the metrics in the bottom layer, which makes the application in practice difficult [KIT96] In recent years, ISO 9126 model was proposed [FEN94] It improves the McCall model and defines six factors but doesnt elaborate in criteria and metrics layers. REBOOT model [KAR95] is composed of one quality model and reusability model, which give detailed definition and description for each layer. Layer decomposition can be adopted to develop ....

N. E. Fenton, Software Measurement: A Necessary Scientific Basis, IEEE Trans. Software Eng., Vol. 20, No. 3, pp. 199-206, Mar. 1994.

....only to expression, whilst the data slice will contain leaves and instances of variable names occurring on the LHS of assignment statements and in declarations. We should also point out, that Bieman and Ott have augmented their work with a more rigorous investigation of the scale properties [4, 22] of their measures. Our work, by comparison, is at an earlier stage of development. Arun Lakhotia [6] takes a different approach. His work is more closely related to the original seven levels of cohesion identified by Constantine and Yourdon [3] Effectively, Lakhotia codifies the natural language ....

Norman E. Fenton. Software measurement: A necessary scientific basis. IEEE Transactions on Software Engineering, 20(3):199--206, 1994.

....may also have cohesion like attributes, that are measurable in terms of the dependencies between pattern components, which may be classes or sub patterns. Other potential design measures can be based on some notion of distance from desired patterns. We can develop empirical relation systems [24] that model our intuition about relative distances of a structure of classes from a particular pattern. We can then define ordinal, and eventually ratio, scale measures from such empirical relation systems. This is the approach that we took to develop measures of functional cohesion and class ....

N. Fenton. Software measurement: a necessary scientific basis. IEEE Trans. Software Engineering, 20(3):199--206, 1994.

....of) dynamically changing) relationships between them [36] The complexity of an ERD could be highly influenced by the different elements that compose it, such as entities, attributes, relationships, generalisations, etc. Hence it is not advisable to define a general measure for its complexity [37]. Following this reasoning Genero et al. 15] have proposed a set of measures for measuring ERD structural complexity, following the notion of complexity of Henderson Sellers [38] These metrics allow database designers: 1) a quantitative comparison of design alternatives, and therefore and ....

N. Fenton, Software Measurement: A Necessary Scientific Basis. IEEE Transactions on Software Engineering, 20(3), 1994, 199-206.

....standard quality thresholds or degrade over time. Quality prediction forecasts the quality of software components using measures which are available early in the software life cycle. In each case, a model of quality is used to define the association between the external and internal attributes [14] of software products in the IESEM repository. Although external attributes, such as maintainability, reliability or usability are the ones that most software people need to know, they cannot be measured directly. Indirect measures of internal attributes, like size, 13 modularity, or coupling are ....

N. Fenton, "Software measurement: a necessary scientific basis", IEEE Transactions on Software Engineering 20, 3 (March 1994) 199-206.

....specification languages such as IDL[17, 24] and ODL[18] More details on AOL can be found in [11, 1] Software metrics are extremely appealing when a large software has to be assessed and no a priori documentation and or information are available. Several papers [15, 7, 25, 9, 20] and books [10, 19, 22] investigated software metrics attempting to draw conclusions on the relation between measured values and software characteristics (e.g. reliability, testability, maintainability, etc) with special regard to quality issues [20, 4] In the present work we extract a suite of software metrics that ....

N. Fenton. Software measurement: A necessary scientific basis. IEEE Transactions on Software Engineering, 20(3):199--206, Mar 1994.

....models, e.g. maintainability, testability. Empirical evaluation of OO design principles. Empirical evaluation of OO technologies. Measurement Validation Principles Several authors have suggested that measures should adhere to measurement theoretical principles (Zuse 1991, Fenton 1992, Fenton 1994) as a means of evaluating software measures and to qualify the use of certain statistical techniques (depending on the measurement level of the measures) Briand et al. Briand et al. 1996a) argues, however, that a more pragmatic approach is likely to provide the software engineering community ....

Fenton, N. (1994). "Software Measurement: A Necessary Scientific Basis". IEEE Transactions on Software Engineering, Vol. 20, No. 3, pp. 199-206.

....a document compliant with the rule it violates. In [4] diagnosis has been realised as the identification of parts of formal specifications which are not affected by an inconsistency and, therefore, they are safe to reason from. Using the facets for classifying software metrics proposed by Fenton [21], the metrics defined in this paper can be characterised as assessment metrics which measure external features of the product of the software development life cycle. Similar metrics have been proposed elsewhere in the literature but have not been used as a means of assessing the significance of ....

Fenton N., 1994. Software Measurement: A necessary Scientific Basis, IEEE Transactions on Software Engineering, 30(3), pp. 199-206.

....cost of a play, or the length of the development process. Obviously, the entity and the dimension to be measured must be specified in advance. Measurements cannot be taken and then applied to just any dimensions. Unfortunately this is exactly what the software development community has been doing [10], e.g. lines ofcode, being a valid measurement of size, has been used to measure the complexity of programs [28] An intuitive and empirical assessment of the entities and dimensions must be preserved by the measurement (the assignment of numbers and symbols) For example, when measuring the ....

....in the section on Measurement Theory. Because people observe things differently (and often intuitively feel differently about things) a model is usually defined for the entities and dimensions to be measured. The model requires everyone to look at the subject from the same viewpoint. Fenton [10] uses the example of human height. Should posture be taken into consideration when measuring human height Should shoes be allowed Should the measurement be made to the top of the head or the top of the hair The model forces a reasonable consensus upon the measurers. This idea is applied to ....

[Article contains additional citation context not shown here]

Fenton, Norman, "Software Measurement: A Necessary Scientific Basis", IEEE Transactions on Software Engineering, Vol. 20, No. 3, March 1994.

No context found.

N. Fenton. Software measurement: A necessary scientific basis. IEEE Trans. Softw. Eng., 20(3), 1994.

No context found.

N. E. Fenton. Software measurement: A necessary scientific basis. IEEE Transactions on Software Engineering, 20(3):199--206, 1994.

No context found.

Norman E. Fenton. Software measurement: A necessary scientific basis. IEEE Transactions on Software Engineering, 20(3):199--206, 1994.

No context found.

Fenton, N. (1994). Software measurement: A necessary scientific basis. IEEE Transactions on Software Engineering , 199--206.

No context found.

N. Fenton, "Software measurement: a necessary scientific basis," IEEE Transactions on Software Engineering, vol. 20, pp. 199-206, 1994.

No context found.

N. Fenton. Software measurement: A necessary scientific basis. IEEE Transactions in Software Engineering, 20(3):199--206, 1994.

No context found.

Fenton, N. (1994) Software Measurement: A Necessary Scientific Basis, IEEE Transactions on Software Engineering, 20, 3, 199-206.

No context found.

N. E. Fenton. Software measurement: A necessary scientific basis. IEEE Transactions on Software Engineering, 20(3):199--206, 1994.

No context found.

N. E. Fenton, "Software measurement: a necessary scientific basis," IEEE Transactions on Software Engineering, vol. 20, no. 3, pp. 199--206,

No context found.

N. Fenton, Software Measurement: a Necessary Scientific Basis, IEEE Trans. Software Eng., 20, 1994, pp. 199-206.

No context found.

N. Fenton, Software Measurement: a Necessary Scientific Basis, IEEE Trans. Software Eng., 20, 1994, pp. 199-206.

First 50 documents  Next 50

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC