Techniques for Calculating Software Product Metrics Threshold Values: A Systematic Mapping Study

Several aspects of software product quality can be assessed and measured using product metrics. Without software metric threshold values, it is difficult to evaluate different aspects of quality. To this end, the interest in research studies that focus on identifying and deriving threshold values is growing, given the advantage of applying software metric threshold values to evaluate various software projects during their software development life cycle phases. The aim of this paper is to systematically investigate research on software metric threshold calculation techniques. In this study, electronic databases were systematically searched for relevant papers; 45 publications were selected based on inclusion/exclusion criteria, and research questions were answered. The results demonstrate the following important characteristics of studies: (a) both empirical and theoretical studies were conducted, a majority of which depends on empirical analysis; (b) the majority of papers apply statistical techniques to derive object-oriented metrics threshold values; (c) Chidamber and Kemerer (CK) metrics were studied in most of the papers, and are widely used to assess the quality of software systems; and (d) there is a considerable number of studies that have not validated metric threshold values in terms of quality attributes. From both the academic and practitioner points of view, the results of this review present a catalog and body of knowledge on metric threshold calculation techniques. The results set new research directions, such as conducting mixed studies on statistical and quality-related studies, studying an extensive number of metrics and studying interactions among metrics, studying more quality attributes, and considering multivariate threshold derivation.

Novel Approach for software metrics Sharing

Сбор метрик программного обеспечения является фундаментальной деятельностью, которая необходима для проведния практически любого эмпирического исследования в области программной инженерии. Однако, даже при наличии широкого спектра инструментов, сбор таких фундаментальных данных по-прежнему занимает много времени. Более того, каждый исследователь собирает практически одни и те же данные (например, метрики CK, цикломатическая сложность МакКейба и т.д.) из практически одних и тех же проектов (например, из известных проектов с открытым исходным кодом). Объем такой дублирующей работы, выполняемой в сообществе, уменьшает усилия, которые исследователи могут потратить на наиболее ценную часть своих исследований, такую как разработка новых теорий и моделей и их эмпирическая оценка. В данной работе предлагается новый подход для сбора и обмена данными метрик программного обеспечения, позволяющий сотрудничать исследователям и сократить количество напрасных усилий в сообществе разработчиков программного обеспечения. Мы стремимся достичь этой цели, предлагая Формат обмена программными метриками (SMEF)и REST API для сбора, хранения и обмена данными метрик программного обеспечения. In almost every empirical software engineering study, software metrics collection is a fundamental activity. Although many tools exist to collect this data, it still takes a considerable amount of time. In addition, almost all researchers collect essentially the same data (e.g., CK metrics, McCabe Cyclomatic Complexity, etc.) from essentially the same sources (e.g., well-known open-source projects).Having so much duplication of work done within a community reduces the amount of time that researchers can spend developing new ideas and evaluating them empirically, which is the most valuable part of their research. In this paper, we propose a novel approach for getting and sharing software metrics data that will allow them to collaborate and reduce the amount of wasted effort. SMEF, a file format for exchanging software metrics information, and a REST API, targeted at this objective, are proposed in this paper.

Predicting of Open Source Software Component Reusability Level Using Object-Oriented Metrics by Taguchi Approach

Component-based software development (CBSD) is an efficient approach used by software developers to develop new software. The commercial off the shelf (COTS) and open-source software (OSS) are two styles to implement CBSD. The COTS provides the interface and depicts the black-box behavior, but does not support several software quality characteristics. On the other hard, OSS is a more efficient approach compared to COTS due to its source code availability. This research aims to identify the reusability level of OSS components from an online repository of OSS. The OSS components are classified based on Chidamber and Kemerer reusability metrics (CK-metrics). This paper proposed a mathematical model to establish the relationship between the reusability of CK-metrics. Reusability level of OSS component has been measured and most effective CK-metrics obtained by applying the Taguchi design and analysis of variance (ANOVA). The input parameters for the experimental design are evaluated based on the OSS repository. Performance analysis has been carried out based upon the interaction effect between the reusability of CK-metrics. Main effect plots are created to identify the most reusable component of the OSS. The genetic algorithm (GA) is used to predict the optimized value of the different control parameters. The results indicate that the OSS component reusability level is 0.698194. The reusability of software has a significant effect on the quality of software. The quality of software can be improved by increasing the reusability of software components.

Prediksi Understandability Pada CK Metrics Object Oriented Menggunakan Fuzzy Inference System

The ability of the software to easily understand it is very important, to evaluate the performance of a system or process a certain mechanism is needed. So that the achievement level of software development is obtained, the assessment of code quality and design in the metrics have different contributions to the quality properties of software design. The assessment of software characteristics is described in a model based on the Chidamber Kemerer (CK) Entropy Metrics design property indicator. Measure specific properties of the software by mapping them into numbers according to objective and well-defined measurement rules. To be able to help perform the software quality calculation process based on CK metrics on the eclipse equinox data by using the Mamdani fuzzy inference system, pointing the classification into low which can be interpreted as having good quality. And the value affirmation of the deffuzzyfication method in this case is done by using the COA (center of area) method, to determine the crisp x value, obtained from the membership function formed from the composition process of all outputs.

Impact of Design Patterns on Software Complexity and Size

Many different factors influence the quality of software. Among the most important of these factors is software complexity. One way to improve software quality, therefore, is to minimize its complexity making it more understandable and maintainable. The design phase of the software development life cycle plays an instrumental role in fostering quality in software. Seasoned designers often use past design best practices codified in the form of design patterns to make their designs and the resultant code more elegant, robust, and resilient to change. Little work, however, has been done to empirically assess the quantitative impact of design patterns on software complexity. This research is an attempt to fill this gap. A comparative analysis of before and after versions of program pairs written without and with design patterns was performed for all twenty three GoF (Gang of Four) design patterns. These program pairs were collected (or, in some cases, developed) and compared with respect to their complexity and size. The results of this comparative analysis reveal that the cyclomatic complexity of the programs written using design patterns was less for most of the design patterns as compared to the programs written without using design patterns. However, the values of CK metrics, number of classes, and software size SLOC (Source Lines of Code) increased when design patterns were used.

Speculation of Software Reusability Estimation using CK (Chidamber and Kemerer) Metrics

In today’s software community the most interesting topic is software reusability because of its immense benefits that comprise of decreased product schedule, cost and increase in product quality. Most of the time, software is not built from scratch since it is costly and time-consuming process. Therefore, existing software documents (source code, documents, design, etc.) are used to develop the new application according to user requirements. But still the software reusability is not being followed as a standard approach in the process of software development. Till now initiating the software reuse process there is a need to analyze and properly understand the user requirements in spite of considerable upfront investments for software reusability. We have studied various aspects of software reusability along with software metrics and are being presented in this article. Efficient software designs can be enabled by assessing the software reusability extent. The aging resilient software design could be of paramount significance to enable faultiness software system. The estimation of software reusability plays an important part in software’s cost reduction and quality improvement, in an object-oriented programming. In this paper the idea about the designing the CK metrics suite along with metrics’ evaluation is presented that can help for object-oriented based systems in reflecting the accurate results.

Software Reusability Metrics Estimation From the Social Media by Using Evolutionary Algorithms

Software expansion is rising with the help of the standard paradigm in the 21st century. The maximum contribution of software growth focuses mainly on object-oriented development methodologies. This paradigm helps the developer to develop code quickly and makes sure that the platform assists in producing a quality product. The software reusability metrics play a crucial role for software development. To overcome the scalability issues, researchers and developers both adopt a CK metrics suite to extract the software metrics to extract the features from the repositories. The main objective of this article is to extract the set of metrics from social media by using novel evolutionary techniques. Dissimilar features within this area are examined with a suitable research query that discovers the potential and extent.