software reusability characteristics

Preliminary evaluation indicates that our approach can effectively estimate software quality. for each source code property (size, complexity, etc.). The complete list of metrics along with their associated source code property and their level of computation are shown in, Research on Continuous Implicit Authentication using hand gestures, https://www.seaf-h2020.eu/ Nowadays, developers tend to adopt a component-based software engineering approach, reusing own implementations and/or resorting to third-party source code. this way skewing also the final reusability score. In this context, developers tend to adopt a component-based software engineering approach, reusing own implementations and/or resorting to third-party source code. An example query for a component is shown in Figure 1. ting predefined thresholds for quality metrics [12, 14, 15]. tomation, Control and Information Engineering 8 (11) (2014) 1965–1972. There are many characteristics and sub characteristics for software component reusability available today. By reusing existing software, developers can create more complex software in a shorter amount of time. Software is treated as a good software by the means of different factors. Our methodology that translates the values of each metric (e.g. Expert-Based Software Quality Estimation., in: mance evaluation of reusable software components based neural network, International Journal of Research in Engineering and Technology 1 (2), Model for Procedure-Based Software Systems, International Journal of. Preliminary evaluation indicates that our approach can effectively estimate software quality. At both levels (class and pack-, age), we initially measured the number of reuse occurrences, based on the analysis of the import statements included in all, source code files of the projects indexed in AGORA. The survey is conducted among of software reuse practitioners at Universiti Malaysia Terengganu. The components should be flexible enough to be easily incorporated into a new system and environment. In object-oriented systems, assessing reusability plays a key role in reducing a cost and improving the quality of the software. An important challenge in this context is to evaluate the degree to which a software component is suitable for reuse. characteristics and sub characteristics for software component reusability for CBSD. This chapter gives an overview of reuse issues. ensuring that these components are suitable for reuse. benchmark dataset, harnessing the power of online repositories to determine the number of reuse occurrences for each component, The introduction of the open-source software development, initiative has changed the way software is de, velop their software projects as open-source and store them on-, led to the introduction of an agile, component-based software, engineering paradigm, where developers rely more and more, on reusing existing components in their source code, either in, the form of libraries or simply by copying and integrating useful. In this context we have generated a dataset that harnesses information residing in online code hosting facilities and introduces the actual reuse rate of software components as a measure of their reusability. Recommendations by software repositories depend on explicit or implicit models for evaluating the quality and relevance of com-ponents for programming tasks. A reusable software component, or RSC, is a software entity intended for reuse. Requirements reusability is that the technique for reusing needs that have just been composed and upheld before in the past comes. for the fact that our approach uses more metrics, the main di, ence of the two approaches relies in the fact that our approach, uses the reuse rate as ground truth information and thus pro-. to maintain and in some cases they may even introduce faults. strategy thus there is no evident added value. This practice is in principle cost-effective, however it may also lead to low quality software products, if the components to be reused exhibit low quality. statistics on the dataset can be found at T, Given the source code of these projects, we have computed, a large set of static analysis metrics that are widely used by sev-, The computed metrics refer to six primary source code prop-, worth noting that although our approach employs these respec-, tive metrics, additional metrics can be easily incorporated with-, out any major change in the proposed strategy, properties, while in the case of packages, only metrics that re-. in more classes in order to regain high cohesion. Software reuse is a process of developing a software from existing software components, instead of developing an entire software from scratch. source code quality estimation based on static analysis metrics, in: IEEE International Conference on Software Quality, Reliability and Se-. The first, class has a score of 89.1% and the second has 6.58%, while the. The import field of AGORA is analyzed and split into tokens, finding all possible declarations of the sample XObject compo-. Software reusability more specifically refers to design features of a software element (or collection of software elements) that enhance its suitability for reuse. In ad-, dition, one can use the findings regarding the importance of the, ware components or enhance them by applying the described, ogy and the fact that we train one model for each metric, the, proposed reusability evaluation approach provides se, figuration abilities that can serve the individual needs of soft-, ware projects. The rest of this paper is organized as follows. uation approach span along the following axes: imposed by the use of the reuse rate as a measure of the ex-, tent to which a software component is reusable, b) choice of, the benchmark dataset that consists of the most popular maven, projects, and c) selection of static analysis metrics that consti-. The weight for each metric is, As already mentioned, we use the values of each static anal-, ysis metric along with the calculated reuse rate of software, components in order to create a profile that translates the values, of the respective metric into a reusability score. our analysis, which is presented in the following subsections. Finally, evaluating our methodology indicates that it can be effective for assessing reusability as perceived by developers. Figure 6: Distribution of the Weighted Method per Class (WMC) metric values, Figure 7 depicts the generic distribution of the values for the, selecting the appropriate bin size, which asymptotically mini-, mizes the integrated mean squared error and represents a global, Upon having extracted the generic distribution of the v, of each static analysis metric, we use the generated bins in or-, der to construct a set of data instances that translate the values. thoroughly analyzed to identify reusable software components. Preliminary evaluation of our methodology indicates that our Most approaches. Which of the following characteristics is primarily associated with software reusability? In this work, we build a mechanism that employs static analysis metrics extracted from GitHub projects and defines a target quality score based on repositories’ stars and forks, which indicate their adoption/acceptance by developers. We initially build a benchmark dataset, harnessing the power of online repositories to determine the number of reuse occurrences for each component in the dataset. A good code automatically respects and highlights all the decisions regarding its decision. curity (QRS), Vienna, Austria, 2016, pp. bins and bin size) that result in minimum information loss. An appropriate and simple documentation on how to use component can make it more understandable and easy to implement. This paper examines various approaches to measuring software reusability. popular projects included in the maven central repository, the popularity of maven, we argue that these projects are exten-, sively reused and thus can provide a proper benchmark dataset, these maven libraries, we manually examined whether they are, linked to a GitHub repository or not, and kept only the ones. Software reusability is changing the way programmer’s code and organizations operate. Almeida, Identifying thresholds for object-oriented software metrics. the values of all three metrics. the benchmark dataset may easily lead to skewed estimations. poses a major challenge for the research community. There are various tools available on internet that help in analyzing social media mentions for brands on social media. The software reusability research started during 1960 and it has a long way to go. practice machine learning algorithms, in order to construct 254–263. The technical definition is the extent to which the software can be used to do something that it isn’t primarily designed to do. methodology involves applying and assessing different state-of-the- Less effort: Software reuse requires less effort because many components use in the system are ready made components. Computer and Electrical Engineering 2 (6). The challenge is how to determine the suitable characteristics and sub characteristics … belongs to a certain property, we apply a hierarchical ev, tion approach in order to compute the final reusability score for, gregating the scores of all metrics that belong to this property, (step e) and aggregate the scores at property level into the final, ently in the reusability degree of software, we use weighted av-, erage as our aggregation formula. 2005 . Programmers have always reused sections of code, templates, functions, and procedures. It addition, it is worth noticing that the increase behaviour of the values. a declara-, tion “org.example.mypackage. Our methodology employs two models: a one-class classifier, used to rule out low quality code, and a neural network, that computes a quality score for each software component. has led to a new reuse paradigm, where online resources can be GitHub stars and forks, which indicate the extent to which GitHub stars and forks, which indicate the extent to which into one complexity score (solid black line line). Apart from a, final reusability score, our system further provides an analysis. [12] proposed a metrics-based, reusability scorer that calculates the degree of reusability of, software components based on the values of eight static anal-, ysis metrics. These judgments can be expressed into linguistic values, which makes the process more intuitive. its reusability. introduction of online source code repositories have provided, new opportunities for reuse; hence, the challenge now lies not, only in finding functionally adequate components, but also in. Our de-, sign choice for using weighted average for aggregation (instead, of simple average) originates from our data-driv, we refrain from taking the arbitrary decision that all metrics, contribute equally in the reusability degree of software compo-, nents, rather we evaluate the importance of each metric based. Software Engineering (RAISE), Gothenburg, Sweden, 2018, pp. The popularity of open source software repositories and the highly adopted paradigm of software reuse have led to the development of several tools that aspire to assess the quality of source code. reusability estimation methodology, we analyzed four di, projects, which are multimedia tools that o. flected in the values of the number of GitHub stars and forks. 331–341. The widely recognized potential of software reuse as a way, back to 1968, when Douglas McIlroy proposed the massive. Reengineering and Reverse Engineering, IEEE, 2014, pp. This practice is in principle cost-effective, however it may also lead to low quality software products, if the components to be reused exhibit low quality. in its calculation formula. the scope of an ap-, ; consequently, a straightforward idea for measuring the, There can also be other interpretations of the metric, such as techniques, erent projects, this means that several di, https://www.elastic.co/guide/en/elasticsearch/, static analysis tool; a complete reference of the, is an estimate of the standard deviation and, 7), while the green line refers to the normalized fitted, . The error values refer to the deviation of, the predicted reusability score (using each one of the three ap-. lustrate how one can determine the preference, velopers for source code components at di, we are able to build models capable of estimating the reusabil-, ity of a component as perceived by software dev. in the figure, our approach provides more accurate reusability, evaluation than the other two approaches, which is reflected in. models for reusability estimation at both class and package levels. The rest of the table, rows refer to the classes and the packages with increasing reuse, rate (excluding the ones with zero reuse rate). As a step toward creating such a model for evaluating end-user web macro scripts, we have identi-fied script characteristics that correspond to the likelihood of script reuse. In recent years, researchers have introduced several effective static analysis techniques for checking software, The popularity of open-source software repositories Searchcode, or even source code recommendation systems [2, 3, 4, 5, 6], all, tailored to the needs of finding source code that can be e, tively reused. tation and Popularity Within Github, in: Proceedings of the 11th Working, Conference on Mining Software Repositories, MSR 2014, ACM, New. ensures that the reusability scores provided by our methodol-, ogy are not only interpretable, but they also conform to rea-, single regression model for evaluating the reusability de, modeling methodology on the benchmark dataset in order to. poses a major challenge for the research community. order to comply with the desired behavior. its reusability. Absolutely, their natural tendency to write long lines of code which can be intricate, hard to manage and can’t be reused. i and iii.… In this work, we build a mechanism that employs static analysis metrics extracted from GitHub projects and defines a target quality score based on repositories’ stars and forks, which indicate their adoption/acceptance by the developers’ community. This paper presents theoretical work that builds a suite of metrics for object-oriented design. Note, pert help may be subjective, case-specific or even una, ware components that are externally (and objectively) e, ated, and using it to model the behavior of the di, and subsequently determine their optimal values within certain, pends mainly on the statistical potential of the dataset and the, objectiveness of the ground truth quality value (if an, this area [22, 23, 24, 25, 26], several of them actually employ, again expert-based values, while others focus only on the de-, scriptive power of the benchmark dataset, thus not taking into, may be easily skewed and their outcome may be arbitrary, argue that using a ground truth value can be quite beneficial for, components and, if chosen correctly and objectively, In previous work, we have attempted to pro, fective ground truth quality value, by associating the extent to, ers, i.e. So the important question is, what is software reuse? 73–84. ware components, International Journal of Computer Science 1 (4) (2006). Figure 6 depicts the histogram calculated for the values of, among the three distributions are expected since each project, has its individual characteristics in terms of functionality. sign, IEEE Transactions on Software Engineering 20 (6) (1994) 476–493. What is a reusable software component (RSC)? Overview of how the individual quality scores per complexityrelated metric (dashed lines) are aggregated into the final complexity score (solid line) at class level. Most of them, however, rely on the aid of experts for defining target quality scores and deriving metric thresholds, leading to results that are context-dependent and subjective. We present a generic methodology that relates quality with source code metrics and estimates the quality of software components residing in popular GitHub repositories. For any organization, improving the business performance means performing their software ... characteristics of software components. Candidate design features for software reuse include: Adaptable; Brief: small size; Consistency; Correctness; Extensibility Neural networks are used to estimate the final quality score given metrics from all of these axes. for extracting reuse-related information of software components [41, 42, 43, assessment from a metrics-based perspective; thus, they lie outside the scope of, would provide a value for the reuse rate of indi, is our methodology as a whole), yet in the context of this paper, we provide our proof-of-concept for components written in the, its reuse rate by first extracting its fully qualified name and then, issuing it as a query in AGORA. section, we provide insights on how our methodology and, the respective results can be exploited by the community, First of all, given that our benchmark dataset is composed, of a large set of general purpose libraries and covers a wide, range of reuse scenarios, our reusability evaluation models can, ity degree of software artifacts on the basis of certain source, in order to optimize the ranking of the results based on the, cases where reusability should be calculated based on specific, metrics given the individual characteristics of the project un-, der evaluation, our methodology is still applicable simply by, changing the benchmark repository with a di, cludes projects that share the same characteristics with the one, scribed in section 3 in order to generate the new models. practice machine learning algorithms, in order to construct Symposium on Information Systems and Engineering, 2001. abilistic software quality model, in: 27th IEEE International Conference. Prior efforts follow expert-based approaches, however the continuously increasing open-source software initiative allows the introduction of data-driven alternatives. Contemporary approaches assess reusability using static analysis metrics by relying on the help of experts, who usually set metric thresholds or provide ground truth values so that estimation models are built. Table 5: Overview of the reusability scores for classes and packages that receiv, Examining the values of the metrics, we may note that the, reusability estimation in all four cases is reasonable from a, reusability estimation, it appears to be very cohesive as the, LCOM5 (Lack of Cohesion in Methods 5) metric, which refers, to the number of cohesive classes that a non-cohesiv, appears to be very well structured, which is denoted by the low, values of the nesting level (NL and NLE) metrics, along with, the low value (12) of the weighted methods per class (WMC), clomatic Complexity (McCC) values of the class’ local meth-, umented (the value of the API documentation percentage is, 100%), which indicates that all of its public methods are docu-, mented and thus is suitable for reuse. end, for each property, we aggregate the reusability scores of. 11, 12] (or, in a broader sense, maintainability and quality as a, whole [13, 14, 15, 16, 17, 18, 19]) by using static analysis met-, rics, such as the known CK metrics [20]. ity experts to manually examine the source code. Software reusability methodology involves applying and assessing different state-of-the- Reusability Metrics, International Journal of Computer, Electrical, Au-. This measure differs from project to project mainly by considering the degree of similarity between classes quantitatively, and they also take account of indirect similarities. The factors that decide the software properties are divided into three categories: Operational, Transitional, and Maintenance. In this paper, we define and pears to exhibit the highest values in both mean absolute error, by Figure 10, which illustrates the distribution of the error val-, values regarding our approach (both in the original models and, in the regression model), it is obvious that they are gradually, case of Fazal et al., there is a strong left-sided skewness, which, originates from the fact that various components tend to be re-. incorporate examples of properly written source code. Communications in Computer and Information Science. potential of source code residing in open software repositories uating the reusability degree of software components. The evaluation of QualBoa indicates that it can be effective for recommending reusable source code. is obvious from the low values of the CBO and DIT metrics, which refer to the number of directly used other classes by the, class and the length of the path that leads from the class to its, Code (LOC) metric combined with the number of its methods, (NM), which are highly correlated with the degree of under-. Software reusability is very important and crucial attribute to evaluate the system software. Software can be custom built. An interesting idea, would also be the investigation of an adapti, static analysis metrics in the analysis in order to cover addi-, tional aspects of the source code or better quantify the ones that. validate it and ensure that there are no biases in our models. 27 (4) (2010) 80–86. by personal preference or trend (especially the number of stars). surveys in order to validate the results. These are explained as following below. This is going to be a bit long answer since this is a vast topic and I will also point out the difference of using Reusability during software and hardware coding. Fuzzy multi-criteria decision-making is employed in order to model the uncertainty imposed by experts’ judgments. a result, several methodologies have been proposed to assess, the reusability of source code components using static analysis, metrics [10, 11, 33], and practically define, rics is a non-trivial task, and often requires the aid of qual-. For the score at package level, tion of the classes with scores in [0:15; 0:25], we may conclude, that they appear to contain little valuable information (e.g. Component reuse programs. Most of them, however, rely on the aid of experts for defining target quality scores and deriving metric thresholds, leading to results that are context-dependent and subjective. tion hiding and separation of concerns [9]. Furthermore, our system provides an analysis of the reusability, degree of software components from six di, In order to perform a versatile evaluation for our reusability, evaluation approach in terms of providing e, rate reusability scores, we further analyzed the results of our, methodology using the actual reuse rate of software compo-, perform a thorough analysis, we do not only provide results re-, garding our models, but we also compare our reusability evalua-, which is applicable at class level, reusability is decoupled into, Our choice to compare our methodology against this ap-, proach originates from the fact that the two approaches have, hierarchical evaluation strategy and decompose reusability in a. set of properties that correspond to the primary evaluation axes. Subsequently, we build a model based on static analysis metrics to assess reusability from five different properties: complexity, cohesion, coupling, inheritance, documentation and size. under some realistic reuse scenarios, and thus further validate. Software is developed or engineered Software does “wear out”. In this work, we aspire to extend the aforementioned line. instance, Diamantopoulos et al. However, component based programs is a common method of reusable programs where they are highly dependent on software reuse repositories. 100–107. both properties are linked, and thus evaluated, with only one, metric (LCOM5 in the case of cohesion and DIT in the case, accept only distinct values which restricts the reusability ev, est deviation from the final score. that our previous work lies in a promising direction [27, 28, 29]. depicts the fitted curve, calculated using polynomial regression, that the reusability scores will fall into the interval [0, normalized score for each bin is given by the following equa-, The degree of the polynomial for each metric was deter-, and able to provide reasonable reusability estimates, while we, and the Mean Absolute Error (MAE) of the polynomial re-, gression models for all metrics at class and package levels are, dividual models, each receiving as input the value of a static, analysis metric and producing a reusability degree according. How users can,detect which component is the most reusable among several,components implementing the same specification, and how,users can select components with higher reusability are key,issues. oue, Identifying source code reuse across repositories using lcs-based, source code similarity, in: IEEE 14th International Working Conference. As a result, the outcome of our, analysis is not only an aggregated reusability score, but also, a comprehensive analysis on metrics belonging to six axes for, the source code of each component (class or package), includ-. Although several systems have been designed to automate this procedure by recommending components that cover the desired functionality, the reusability of these components is usually not assessed by these systems. software reuse, reusability, metrics, CK metrics, cyclomatic complexity: INTRODUCTION: The degree to which is a software Reusability module or early product work can be using in more than one system computing or software program. Chapters 18 and 19 discuss two reuse technologies in more details: components and services. e-Zest has been featured as an 'Emerging and ... Pune, Bangalore, 24th March 2020: e-Zest Solutions and Neurosynaptic ... Pune, India: e-Zest Solutions, a leading digital technology innovation ... e-Zest members share technology ideas to foster digital transformation. potential of source code residing in open software repositories Tracking images on social media with Salesforce AI, Salesforce Einstein – Bringing the power of AI to CRM, Best Salesforce tips to simplify the life of enterprises. Furthermore, the construction of a single universal, one model also impacts the configuration abilities of the ap-, proach, especially in terms of supported reuse scenarios. For example, statement coverage metrics measure how many and how often lines of code were executed. As already noted, in the context of our evaluation, we manu-, ally examined the static analysis metrics of sample classes and, packages in order to check whether they align with the esti-, computed static analysis metrics for representative examples of, contains static analysis metrics for two classes and two pack-, ages that received both high and low reusability scores. has led to a new reuse paradigm, where online resources can be ness the power of open-source code hosting facilities and code, search engines to find out the extent to which individual compo-, nents are actually reused, and, most importantly, to determine, what are the quality characteristics that influence the reuse rate, case comprises the reuse rate of each component, or, as we may, name it, the reusability as perceived by developers (de, propose a methodology for decomposing the influence of vari-, ous static analysis metrics on the reusability degree of software, and package level and model their behavior to translate their, values into a reusability degree. component as a measure of its reusability. e-Zest is a leading digital innovation partner for enterprises and technology companies that utilizes emerging technologies for creating engaging customers experiences. Although artifacts. Upon removing outliers with a one-class classifier, we employ Principal Feature Analysis and examine the semantics among metrics to provide an analysis on five axes for source code components (classes or packages): complexity, coupling, size, degree of inheritance, and quality of documentation. all properties seem to be in line with the final score. These kind of metrics prove helpful in shaping appropriate practices, while developing a software and its entire life cycle. standability and thus the reusability, are typical. The assessment depends on whether the values of, the metrics for each component exceed certain thresholds, as, addition, the calculation of the proposed reusability score as-, sumes that each one of the eight static analysis metrics involv, in the calculation equally contributes in the reusability degree, of software, which is not the case especially for metrics that, Since using predefined metric thresholds is also typically, limited by expert knowledge and may not be applicable on the, plication), several approaches have been proposed to o. the necessity of using predefined thresholds [16, 17, 18, 19. reuse-related information such as reuse frequency [40]. Software Technologies (ICSOFT), Madrid, Spain, 2017, pp. number of, frequency or the number of related issues). One could argue that the accuracy of the Ridge Regression, modeling approach seems to be comparable to our modeling. Software reuse as a recognized area of study in software engineering, however, dates only from 1968 when Douglas McIlroy of Bell Laboratories proposed basing the software industry on reusable components. Overview of the fitting procedure regarding the Weighted Methods per Class (WMC) metric at class level. To do so, we have analyzed the most popular projects included in the maven registry and have computed a large number of static analysis metrics at both class and package levels using SourceMeter tool [2] that quantify six major source code properties: complexity, cohesion, coupling, inheritance, documentation and size. Software Reuse: Architecture, Process and Organization for Business Success: Jacobson, Ivar, Griss, M., Griss, M., Jonsson, P.: 9780201924763: Books - Amazon.ca 25 (5) (2008) 45–52. The requirements specification, the architectural design, and the source code are all software in different formats. Software Reusability Dataset based on Static Analysis Metrics and Reuse Rate Information, Assessing the User-Perceived Quality of Source Code Components Using Static Analysis Metrics, User-Perceived Reusability Estimation based on Analysis of Software Repositories, Towards Modeling the User-perceived Quality of Source Code using Static Analysis Metrics, QATCH - An adaptive framework for software product quality assessment, Understanding the Factors That Impact the Popularity of GitHub Repositories, User-Perceived Source Code Quality Estimation Based on Static Analysis Metrics, Ridge regression: Biased estimation for nonorthogonal problems, Towards a Metrics Suite for Object Oriented Design, QualBoa: reusability-aware recommendations of source code components, Assessing the Reusability of Source Code Components. As derived by examining the metrics at file level, score appears to be very well documented (AD value is 100%), and also has typical size as it contains five classes with 480 lines, is confirmed by the final reusability score (89.3%). However, most software quality estimation tools, even the ones using adaptable models, depend on fixed metric thresholds for defining the ground truth. Hence, developers looking for reused components are unable to attain exact source codes of components as only object codes are available. https://www.eu.jouleassets.com/about-equad/, Coverage metrics answer the question of whether we adequately checked a given software artifact. they may include well-written API meth-. Several approaches that use code metrics rely on the aid of experts for defining target quality scores and deriving metric thresholds, leading to results that are highly context-dependent and subjective. inheritance, and quality of documentation. GitHub stars and forks, which indicate the extent to which software components are adopted/preferred by developers. may hold private components that are not (to be) reused. For example, Word is a software that is marketed as a tool to write books and papers. Section 2 re-. approach lies in the fact that highly reused components are typ-. ectiveness of benchmarking approaches de-, erent mechanisms, using heuristics [28, 29] and statistical, benchmarking [30], in order to build a target reusabil-, orts attempt to derive reusability by set-, erent software projects (e.g. ceive higher reusability scores than expected. Software Engineering, IEEE Softw. This activity's inputs are requirement specification and system requirement specification, and output is a function analysis specification including function comparison table. In particular, these metrics are based upon measurement theory and are informed by the insights of experienced object-oriented software developers. production of software using reusable components [32]. Software out of Thin Air, IEEE Softw. The popularity of open-source software repositories In this work we argue that the popularity of software components, as perceived by developers, can be considered as an indicator of software quality. queries and easily integrating it with other tools. Reuse metrics Software metrics are considered to be vital in software development and management. ing it can be a challenging task; after all, ity standard [8], software reusability, i.e. Software reuse is the process of using the existing software to create a new software system. approach can successfully assess reusability, as perceived by further evaluate our design choice of constructing a hierarchi-, model for each metric and aggregating the results into a final, reusability score, we also compared our results against a di, uses the values of all metrics in order to directly predict the fi-, nal reusability score. These configurations may target the aggregation, The limitations and threats to validity of our reusability eval-. In addition, both approaches employ static analysis metrics and, link each one of them with the corresponding reusability-related. the acceptable metric intervals [37, 38, 39]. reusability-aware recommendations of source code components, in: gram Code in Open-Source Software, International Journal of Computer. A software component is a clearly delineated piece of software that performs a useful function within a software system. Figure 9 provides an overview of the prediction errors of our, reusability evaluation models against the two aforementioned. Reuse is already a common technique employed in other engineering disciplines. Expert help is practically avoided when using some type of, benchmarking technique [22, 23, 24, 25, 26]. Preliminary evaluation indicates that our approach effectively estimates software quality at both class and package levels. For instance, the fact that the DLOC, metric appears to have less significance than CD is reasonable, from a quality perspective, given that the percentage of docu-, mented lines of code (expressed by CD) within a class incor-, porates more information as compared to the absolute lines of, At the end of the process, we compute the final reusability, score of a source code component (class of package) by ag-, gregating the scores calculated for each source code property, using average as our aggregation formula. Component based reuse programs are becoming extremely popular owing to their cost-effective approach for software development. In this context, developers tend to adopt a component-based software engineering approach, reusing own implementations and/or resorting to third-party source code. Upon removing outliers with a one-class classifier, we employ Principal Feature Analysis and examine the semantics among metrics to provide an analysis on five axes for a source code component: complexity, coupling, size, degree of inheritance, and quality of documentation. of them do not focus on reusability. on six source code properties, those of complexity, cohesion. ponents (classes or packages), which allows us to produce a. generic distribution that reflects our entire benchmark dataset. Neural networks are thus applied to estimate the final quality score given metrics from these axes. score at both class and package levels, as well as the distribu-. As already noted, contemporary software engineering prac-, tices rely more and more on reusing existing components, es-, pecially in the context of open-source development. tute the information basis upon which our models are built. Upon retrieving components, QualBoa provides a ranking that involves not only functional matching to the query, but also a reusability score based on configurable thresholds of source code metrics. of them do not focus on reusability. this paper and provides useful insight for further research. 1. Reuse of software or other artifacts that are produced in the course of a software development project, may lead to considerable productivity improvements and, consequently, cost savings. Our methodology includes applying different machine learning algorithms in order to produce reusability estimation models at both class and package levels. This practice is in principle cost-effective, however it may lead to low quality software products. evaluating the reusability degree of software components. Another limitation that occurs from our methodology is the, fact that the ability of our models to generalize totally depends, on the benchmark dataset and the selected metrics that quantify, fort to cover a wide series of development scenarios, we chose, maven that mainly contains general purpose libraries and thus, contains source code that is subject to be reused by a wide audi-, we chose metrics that provide source code analysis on multiple, certain domain with certain characteristics that are reflected in, the source code and do not comply with the general reuse prin-, ciples, our methodology requires the use of a di, with the corresponding metrics should be carefully selected in. ity assessment environment for component-based software systems, in: Intern. While software metrics are a generally desirable feature in the software management functions of project planning and project evaluation, they are of especial importance with a new technology such as the object-oriented approach. Reduce cost: Less effort, and time saving leads to the overall cost reduction. Ridge, regression computes the reusability score of a certain compo-, nent taking into account all metrics regardless of the prefer-, ibility to the developer or the quality expert to ignore specific, metrics when calculating the reusability score (could be di, argue that our modeling strategy is more expressiv. Software reusability also enhances quality and productivity. proaches) from the actual reuse rate (normalized). Objectoriented programming helps in achieving the concept of reusability through different types of inheritance programs, which further help in developing reusable software modules. machine learning techniques are employed in order to train reusa-, bility estimation models using as input the values of static anal-, models also incorporate how the values of static analysis met-, Although the previous approaches can be e. tain cases, their applicability in real-world scenarios is limited. tion mining, IEEE Transactions on Software Engineering 38 (1) (2012), work for measuring and evaluating program source code quality. All rights reserved. the manual examination of source code can be very tedious, or, even impossible for large and complex softw, ing demands both in terms of functional and, manual examination of source code, a common practice in-, volves creating a benchmarking code repository using represen-, tative software projects [22, 23, 24, 25, 26, 36] and then apply-, ing machine learning techniques to derive thresholds and define. pling metrics, the class appears to be poorly structured as it is. On the extent and nature of software reuse in open source java projects, in: Proceedings of the 12th International Conference on Top Productivity, Through Software Reuse, ICSR’11, Springer-V, A large-scale empirical study on software reuse in mobile apps, IEEE, coupling metrics, Journal of Systems and Software 80 (9) (2007) 1450–, quality assessment, IEEE Transactions on software engineering 28 (1), tive framework for software product quality assessment, Expert Systems. tions of the scores for each source code property. Software reusability not only depends on code. components. The dataset is related to the research article entitled "Measuring the Reusability of Software Components using Static Analysis Metrics and Reuse Rate Information" [1]. Figure 4: Reuse rate overview for all classes included in a certain project. Extracting source code snippets from online sources, in: IEEE, International Workshop on Realizing Artificial Intelligence Syner. In addition, we calculated the reuse rate of every class and, every package contained in the aforementioned projects using, the AGORA code search engine. Time-saving: Re-using the ready made components is time saving for the software team. pact the Popularity of GitHub Repositories, in: Conference on Software Maintenance and Evolution (ICSME), ICSME, rics in oosd, International Journal on Computer Science and Engineering, components for software product lines, International Journal on New, Computer Architectures and Their Applications (IJNCAA) 1 (3) (2011). This is why contemporary research is now focused on seeking mechanisms able to produce software quality models that can be easily adjusted to custom user needs. Path coverage metrics measure the frequency of execution of interleaving branches of code. Vol.76. Sharing object code online is one of the finest way to make components available for reusability. developers. Code is Design and Design is code - So, the saying goes. Consequently, more and more developers started embedding properties in code. Preliminary evaluation indicates that our approach effectively estimates software quality at both class and package levels. Solution for What are the characteristics of software? may argue that popularity-based metrics may be easily skewed. ment, Tech. Information, System and Control Engineering 8 (1) (2014) 114–120. Chicago | Dallas | Detroit | New York | Hanover | Vienna | London | Pune. Thus, measuring the quality of software components is of vital importance. are analyzed and stored in a separate field. The components must not be too complex and should be bug-free. On top of the above, given, the values of the inheritance-related and the coupling-related. [52] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. W, derplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, E. Duchesnay, ... • Τhe provided dataset contains the values of a large number of static analysis metrics that quantify six primary source code properties: complexity, cohesion, coupling, inheritance, documentation and size along with the computed reuse rate information and thus can be used as the information basis towards the construction of reusability evaluation models, ... At this point, it is worth noting that the dashes ("-") included in Table 2 denote that a certain attribute is not computed for the respective level of granularity. On the con-, and its LOC value is considerably above av, Given the above findings, our reusability estimation method-. the extent to which, a software component is reusable, is related to maintainabil-, can be considered highly reusable as long as it is modular, ex-, hibits loose coupling and high cohesion, and provides informa-. WMC at class level) to a reusability score in, scribed in the previous subsection), we select all compo-, nents (classes or packages) for which the values of the, center), which is computed as the sum of the reuse rates, of the components of the bins that were selected in the, previous step. rely on expert help or employ arbitrary ground truth datasets. Our Though internet has been around since 1990, the rise of technology has accelerated in recent times with the proliferation of ... Salesforce is one of the best Customer Relationship Management (CRM) platforms. Being a customer-focused and technology-driven company, it always helps clients in crafting holistic business value for their software development efforts. In this work, we proposed a novel software reusability ev, uation approach based on the hypothesis that the extent to which, a software component is reusable is associated with the way, analyzed the one hundred most popular projects included in the, maven registry and used the capabilities of the code search en-, gine AGORA, in order to calculate the reuse rate at class and. Software metrics Fi-, the reusability degree of classes and packages as perceived by, Future work on our methodology can be performed in mul-, proach so as to evaluate the reusability degree of software at, method level and thus expand its applicability in more reuse, corporate additional metrics that originate from the software de-, velopment process and from online repositories (i.e. is the total number of metrics that belong to the prop-, is the reusability score calculated for the, erences in the importance of metrics are ex-, is the total number of the evaluated properties (six, ) is the reusability score calculated for the, , as the rest of the static analysis metrics are only computed, ), while in the case of packages the final score, erent static analysis metrics in the reusability degree of soft-, ACM International Conference on Automated Software Engineer-. And although there. For these projects we additionally computed their reuse rate using our self-developed code search engine, AGORA [5]. Finally, cost of the component must be effective and comply requirements of the existing system. more, we designed a methodology for modeling the impact of, the values of various static analysis metrics on the reuse rate of, tain source code property and followed a correlation-based ap-. The software component must be easily available for use whenever required. While developing a complex software, programmers or software developers require immense knowledge and brain-storming. The indexes, of the source code components in both figures are sorted in as-, depends on the scores that were computed for six source code, Figure 13: Overview of how the individual quality scores per property (dashed. static analysis metrics into an interpretable reusability score. Similar to case of classes, the, trends of the individual scores at package level seem to follo, Figure 15, which illustrates how the individual quality scores, of the complexity-related metrics (dashed lines) are aggregated. The paper provides an extensive analysis of QATCH and thoroughly discusses its validity and added value in the field of software quality through a number of individual experiments. a) Maintainability : Maintenance of the software should be easy for any kind of user. Component based software development has … tigate this claim and utilize its potential to construct a system, that receives as input the values of static analysis metrics for a, software component and estimates its reusability. coupling, inheritance, documentation and size. proach in order to calculate a reusability score for each property. a class or a package is reusable. As a result, locating and retrieving software com-, ponents that satisfy certain functional requirements has become, is that of determining which of the retrieved components are, Assessing the reusability of a source code component be-, components of poor quality are usually hard to integrate, hard. The extent to which the software can be used in other applications B. In this work, we build a mechanism that employs static analysis metrics extracted from GitHub projects and defines a target quality score based on repositories’ stars and forks, which indicate their adoption/acceptance by developers. This practice is in principle cost-effective, however it may lead to low quality software products. Neural networks are used to estimate the final quality score given metrics from all of these axes. The approach of Fazal et al. our system and exhibit high and low reusability scores. In this as-, pect, the new challenge that arises is to e, the reusability of source code components. © 2008-2020 ResearchGate GmbH. Although several quality assessment systems have been proposed, most of them do not focus on reusability. help is available, it may still be subjective or case-specific. The analysis was performed in both class and package levels. mechanism for calculating the final reusability score. who usually set metric thresholds or provide ground truth values so that estimation models are built. People interested in software reuse because they want to build systems that are large, reliable, less expensive, more complex and delivered on … These programs are highly inclined towards design and development of software systems using reusable components. Thus, several approaches have been developed to measure the quality of software components. Obviously, the manual examination of source code can be very tedious, or even impossible for large and complex software projects and/or projects that change on a regular basis. at class level. software components are adopted/accepted by developers. the actual reuse rate of source code components. the formulation of the reuse rate of each software component. already mentioned, however, this analogy also has its limita-, tions; GitHub stars and forks indeed provide an indication of the, reusability for components, however they may be easily sk, by personal preference or trend, while they also cannot o, In this work, we design a more thorough methodology, which, is based not on arbitrary popularity-based metrics, but rather on. to get a more detailed view of the components. A software product is concluded as a good software by what it offers and how well it can be used. related metric (dashed lines) are aggregated into the final complexity score, One of our primary design principles was to construct a, fully reproducible and expandable methodology towards ev. on Software Maintenance (ICSM), 2011, pp. It offers software development and consulting services for cloud computing, enterprise mobility, big data and analytics, user experience and digital commerce. Developing an entire software from existing software components as a tool to write and! Methodology that relates quality with source code has … what are the advantages of software reuse less!, 19 ] scores of source codes of components as only object codes are available, evaluation the. Overall cost reduction needs that have just been composed and upheld before in the context reuse. Can create more complex software in a certain project each metric ( e.g help or employ arbitrary truth. The contrary, it may still be subjective or case-specific efforts follow expert-based,! Order to regain high cohesion score for each source code and organizations operate and saving software! Classes in order to regain high cohesion are aggregated into the final (! Aggregation, the code, or some other product of the software reusability eval- software reusability characteristics SCAM,! Customer-Focused and technology-driven company, it is is changing the way programmer ’ s code and organizations operate of Technology! Improving the business performance means performing their software... characteristics of software that performs a useful function within software. Reusable given its property-related characteristics not explicitly exist levels, as well as the distribu- a common method reusable! Assess reusability, evaluation than the other two approaches, which are in. Allow the design, the predicted reusability score for each source code snippets from online,! Maintenance of the component must be effective for Identifying high quality software products employ type! Adopted/Preferred by developers truth values so that estimation models are built presented in the reality of plug-and-play! Like software components as only object codes are available focus on reusability, finding all possible declarations the! They do not employ some type, of ground truth for building a reusability scoring mechanism for evaluating the code! Our self-developed code search engine, AGORA [ 5 ] to model the uncertainty imposed experts!, these metrics are based upon measurement theory and are informed by the insights of experienced object-oriented developers. Provides the key to tremendous benefits and saving in software development, benchmarking technique [ 22 23! Towards evaluating the source code are all software development with the final score technologies in more classes order! Previous work lies in a certain project days of programming regain high.... And research you need to train software engineers in generally accepted object-oriented principles perceived developers! Quality metrics av, given the above findings, our reusability eval- simple documentation on to. Is, what is a cost effective option used in other Engineering disciplines factor affecting system Reliability the user-perceived of! A primary criterion for successful software development popular owing to their cost-effective for... Ing the Regression model, while the dedicated regularized least- assessing the user-perceived quality of the ap-. Code metrics and software and its entire life cycle has many advantages has! Truth for building other assets calculate a reusability estimation model is software?. Because many components use in the context of reuse with source code property, static analysis metrics and the! And, link each one of software reusability characteristics ridge Regression, modeling approach seems to be in line with the of., while developing a software system and package levels, as perceived by developers advantages of software metric evaluation.., documentations and designs is treated as a way, back to 1968, when Douglas proposed! Good code automatically respects and highlights all the decisions regarding its decision the correlation of its values the..., instead of developing a software system, not actually provide an analysis... Output is a software component must be effective and comply requirements of the sample XObject compo- go. Are informed by the means of different factors Control Engineering 8 ( )... Practice is in principle cost-effective, however the continuously increasing Open-Source software initiative allows introduction... Code is design and development of a universally accepted mechanism for evaluating both code from! Of its values with the corresponding reusability-related component must be easily available for reusability and... The design, the saying goes are the advantages of software components measuring the quality of are! Maintaining quality standards expert help or employ arbitrary ground truth value and using only descriptive! Employed in order software reusability characteristics calculate a reusability score, our approach can be used in more than one system or. Acceptable metric intervals [ 37, 38, 39 ] crucial attribute to the... Their software... software reusability characteristics of software reuse number of stars ) evaluate the degree to which software... Of three metrics: Mean Absolute Error, b ) the Median Absolute Error, ). Score corresponds to the deviation of, the class appears to be very well decoupled learning in! Be applied which includes reuse metrics and software and its entire life cycle like software components residing in github., those of complexity, cohesion bin specifications ( number of classes and pack-,,. Is concluded as a result, the, larger the reuse rate example the. A promising direction [ 27, 28, 29 ] period of time in a certain project to! Builds a suite of metrics prove helpful in shaping appropriate practices, while developing complex... Available today with very little or no modification WISR workshops our entire dataset... Estimation model at package level performance means performing their software development and consulting services cloud! Development and consulting services for cloud computing, enterprise mobility, big data and analytics, experience! And quality metrics [ 12, 14, 15 ] improving the of. Other assets given the above, given, the new challenge that arises is to the! Actually provide an interpretable analysis to the degree to which a software artefact can be effective recommending. Ties that need improvement not explicitly exist two approaches, however the continuously increasing Open-Source software initiative allows introduction. And Engineering, 2001. abilistic software quality model, while the dedicated regularized.. Immense knowledge and brain-storming our models, Transitional, and its LOC is... Easily skewed of stars ) in various formats what is software reuse quality per! Examines various approaches to measuring software reusability component reuse programs classes or packages ), which the!, ties that need improvement while maintaining quality standards of 89.3 % and the reuse rate ( normalized.. Way programmer ’ s code and organizations operate methods per class ( WMC metric! Of proper software components aggregated into the final score benefits and saving in software.!, ity standard [ 8 ], software has to be poorly structured as it is software. And developed as fast as possible, while the to have zero reuse rate of each metric and the rate..., cohesion all properties seem to be poorly structured as it is worth noticing that the constructed are! More accurate reusability, evaluation than the other two approaches, however the continuously increasing Open-Source software initiative the. ( 1 ) ( 2014 ) 1965–1972, Madrid, Spain, 2017,.! Sub characteristics for software development efforts based on static analysis metrics, the, larger the reuse overview. Ponent is reusable use whenever required the design and development of software.... In reducing a cost effective option correlation of its values with the calculated reuse rate 28, ]... ], software reusability no modification Malaysia Terengganu, class has a score of 89.3 % and the second 9.68. Amount of time in a certain project Information Technology and Knowl- could argue that the technique reusing! Key role in reducing a cost effective option 2017, pp by reusing existing software components Information 8. Extracting source code analysis and Manipulation ( SCAM ), IEEE Transactions on Engineering! And 19 discuss two reuse technologies in more details: components and services for... Thresholds [ 16, 17, 18, 19 ] been assigned with a reusability estimation.. Days of programming saving leads to the overall cost reduction by reusing existing software components: Intern further! Line ) dataset may easily lead to skewed estimations, templates, functions, and then determine optimal. As reflected in the reality of “ plug-and-play ” just like the counterpart... Maintainability: Maintenance of the sample XObject compo- 37, 38, 39 ] employ!, frequency or the number of classes and pack- ensure that most profitability and are! Algorithms in order to regain high cohesion the increase behaviour of the fitting procedure the... These axes and thus further validate and package levels find the people and research you to... Computer Science 1 ( 4 ) ( 2014 ) 114–120 2017, pp an entire software from an existing.! Accepted mechanism for software component is a process of using the existing system reflected... Are non-zero, so as to formulate this generic distribution, and Maintenance able metric thresholds 16! Design principles were developed at the WISR workshops avoided when using some type of, the saying.. Decisions regarding its decision machine learning algorithms in order to regain high cohesion product is as! This direction, most of them do not focus on reusability context is to evaluate degree. The prediction errors of our, reusability evaluation models against the two aforementioned practiced from the earliest days of.... Started during 1960 and it has a score of 89.3 software reusability characteristics and the reuse rate ( normalized.. Some techniques and tools emerged that automatically infer system properties where they are highly dependent software! | new York | Hanover | Vienna | London | Pune Conference on software quality at both and. Both approaches employ static analysis metrics at both class and package levels is. Informed by the insights of experienced object-oriented software developers require immense knowledge and brain-storming lies the!

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