Construction and testing of polynomials predicting software maintainability

Oman, Paul; Hagemeister, J.R.

doi:10.1016/0164-1212(94)90067-1

Cited by 138 publications

(84 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We decided to use the Oman maintainability index (MI) [42,61] as a metric for quality, because it combines several other metrics that are generally agreed to be components of code quality: low complexity (as measured by MCC), small size (as measured by Halstead's volume (HV) and LOC), and good documentation (as measured by the fraction of LOC that contain comments). While the precise formula 2 used to calculate MI is debatable, being based on fitting data from a small number of not-too-large projects, this metric has nevertheless gained some following.…”

Section: Measured Qualitymentioning

confidence: 99%

The Linux kernel as a case study in software evolution

Israeli

Feitelson

2010

Journal of Systems and Software

110

View full text Add to dashboard Cite

We use 810 versions of the Linux kernel, released over a period of 14 years, to characterize the system's evolution, using Lehman's laws of software evolution as a basis. We investigate different possible interpretations of these laws, as reflected by different metrics that can be used to quantify them. For example, system growth has traditionally been quantified using lines of code or number of functions, but functional growth of an operating system like Linux can also be quantified using the number of system calls. In addition we use the availability of the source code to track metrics, such as McCabe's cyclomatic complexity, that have not been tracked across so many versions previously. We find that the data supports several of Lehman's laws, mainly those concerned with growth and with the stability of the process. We also make some novel observations, e.g. that the average complexity of functions is decreasing with time, but this is mainly due to the addition of many small functions.

show abstract

Section: Measured Qualitymentioning

confidence: 99%

The Linux kernel as a case study in software evolution

Israeli

Feitelson

2010

Journal of Systems and Software

110

View full text Add to dashboard Cite

show abstract

“…In our case study, the maintainability of a system is quantified with a Maintainability Index (Oman and Hagemeister, 1994). MI is a combination of different metrics that affect maintainability.…”

Section: Methodology Used In Predicting Maintainabilitymentioning

confidence: 99%

“…Section 9 gives conclusions obtained from the empirical study. Oman and Hagemeister (1994) quantified the maintainability of a system with an MI (Maintainability Index) which was primarily a combination of different code metrics. The concept of using both the code as well as design metrics in predicting maintainability was proposed by Misra (2005).…”

Section: Introductionmentioning

confidence: 99%

Empirical Comparison of Two Metrics Suites for Maintainability Prediction in Packages of Object-Oriented Systems: A Case Study of Open Source Software

Madhwaraj¹

2014

Journal of Computer Science

View full text Add to dashboard Cite

Software maintainability has been an important external quality attribute that concerns both styles of software development, the proprietary model as well as open source. As lots of open source software are predominantly built using the OO paradigm, there exists a need for empirical validation with respect to certain quality aspects especially maintainability. There are a few studies in the past which use code metrics and a few which use design metrics, much earlier in the software development life cycle to predict maintainability. In addition, there are studies which apply both code as well as design metrics to evaluate maintainability. The objective of this research is to perform an empirical comparison of two popular OO metrics suites, the Martin suite and the CK suite on four open source software systems by analysing a few key design metrics such as size, coupling, complexity, inheritance and stability. Two important observations were made with this empirical study. First, between the two OO suite of design metrics, the prediction model developed using Martin metrics scores better than the model developed using the CK suite. Second, the combination of Martin and CK suites is helpful in predicting the maintainability of OO software, with a predictive accuracy of 66.7%, better than that of the models constructed by either Martin metrics or by the CK metrics individually.

show abstract

“…Some of the earliest contributions to software metrics deal with the measurement of code complexity [1], [2] and maintainability [3] based on the complexity measures proposed in [1], [2]. From the standpoint of code modularization, some of the earliest software metrics are based on the notions of coupling and cohesion [4], [5].…”

Section: Previous Work On Software Metrics Relevant To Our Contributionmentioning

confidence: 99%

“…2. Maintainability Index [3]. This is a linear expression based on the Halstead and cyclomatic measures as well as module lines of code and module comments.…”

mentioning

confidence: 99%

API-Based and Information-Theoretic Metrics for Measuring the Quality of Software Modularization

Sarkar

RAMA

Kak

2007

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

Abstract-We present in this paper a new set of metrics that measure the quality of modularization of a non-object-oriented software system. We have proposed a set of design principles to capture the notion of modularity and defined metrics centered around these principles. These metrics characterize the software from a variety of perspectives: structural, architectural, and notions such as the similarity of purpose and commonality of goals. (By structural, we are referring to intermodule coupling-based notions, and by architectural, we mean the horizontal layering of modules in large software systems.) We employ the notion of API (Application Programming Interface) as the basis for our structural metrics. The rest of the metrics we present are in support of those that are based on API. Some of the important support metrics include those that characterize each module on the basis of the similarity of purpose of the services offered by the module. These metrics are based on information-theoretic principles. We tested our metrics on some popular open-source systems and some large legacy-code business applications. To validate the metrics, we compared the results obtained on human-modularized versions of the software (as created by the developers of the software) with those obtained on randomized versions of the code. For randomized versions, the assignment of the individual functions to modules was randomized.

show abstract

Construction and testing of polynomials predicting software maintainability

Cited by 138 publications

References 1 publication

The Linux kernel as a case study in software evolution

The Linux kernel as a case study in software evolution

Empirical Comparison of Two Metrics Suites for Maintainability Prediction in Packages of Object-Oriented Systems: A Case Study of Open Source Software

API-Based and Information-Theoretic Metrics for Measuring the Quality of Software Modularization

Contact Info

Product

Resources

About