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. its popularity, with the extent to which it is reusable, a target quality score at repository level, and then proposed, works, one may conclude that this target score can be e, used to train models for estimating the reusability of source, work lies in the way the ground truth value for each component, indeed provide some informal proof for the reuse rate of repos-, they refer at repository level dictates that modeling reusability, at component (class or package) level requires some type of av-. poses a major challenge for the research community. b) Flexibility : Changes in the software should be easy to make. 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). In order to ex-, amine, and thus model, the influence of each metric on the reuse, rate of software components, we first extract its distribution at, mark dataset, we use the values from all packages (or classes), included in the dataset for which the calculated reuse rate val-. all properties seem to be in line with the final score. Being an evolving concept, lot of organizations are moving forward to incorporate software reusability within their environment. 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%). oue, Identifying source code reuse across repositories using lcs-based, source code similarity, in: IEEE 14th International Working Conference. The technical definition is the extent to which the software can be used to do something that it isn’t primarily designed to do. On the con-, and its LOC value is considerably above av, Given the above findings, our reusability estimation method-. several systems have been, In the context of reusing components from online repositories, assessing the quality and specifically the reusability of source code before reusing it poses a major challenge for the research community. 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-. Preliminary evaluation indicates that our approach can effectively estimate software quality. 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. Software Reliability is also an important factor affecting system reliability. 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. its reusability. 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-. ISO 9126 Part one, referred to as ISO 9126–1 is an extension of previous work done by McCall (1977), Boehm (1978), FURPS and others in defining a set of software quality characteristics. components. 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. 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. Although these e, not actually provide an interpretable analysis to the developer, ties that need improvement. The components must not be too complex and should be bug-free. The first, class has a score of 89.1% and the second has 6.58%, while the. As a result, the final. first package has a score of 89.3% and the second has 9.68%. Software reusability These kind of metrics prove helpful in shaping appropriate practices, while developing a software and its entire life cycle. help is available, it may still be subjective or case-specific. 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. instance, Diamantopoulos et al. 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. Due to incremental growth of software development which leads to increase in complexity of software, so software reusability is an important criteria to quality of system software. Time-saving: Re-using the ready made components is time saving for the software team. this way skewing also the final reusability score. The most intuitive reuse is in the reality of “plug-and-play” just like the hardware counterpart. Communications in Computer and Information Science. This practice is in principle cost-effective, however it may lead to low quality software products. This chapter gives an overview of reuse issues. For any organization, improving the business performance means performing their software ... characteristics of software components. artifacts. tute the information basis upon which our models are built. its reusability. of quality experts for evaluating the source code and determin-. Our approach employs the reuse rate of software compo-, nents (classes and packages) as ground truth information to-, which measures how often a software components has been, reused, there are also other factors that may influence the fi-, the impact of those limitations, we resort in analyzing the most, popular projects included in the maven registry, is composed of a very large set of projects and thus ensures that, there are multiple options regarding each reuse scenario, all of, them equally “easy-to-use” from a functional perspective. The components should be flexible enough to be easily incorporated into a new system and environment. Software reuse is a promising technology in software development and is seen as a solution to the rising cost of software and the existing bottleneck problems due to demands exceeding supplies. In object-oriented systems, assessing reusability plays a key role in reducing a cost and improving the quality of the software. 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. These judgments can be expressed into linguistic values, which makes the process more intuitive. 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-. Once all bins are assigned with a reusabil-, ity score, we normalize these scores so that they are all in, stances produced in the previous steps, which have the, regression is a reusability evaluation model that returns, a reusability score given the value of the metric (continu-, Figure 8 illustrates the results of the reusability modeling, level. models for reusability estimation at both class and package levels. Furthermore, most approaches are, either based on expert-defined metric thresholds [12, 14, 15] or, Preprint submitted to Journal of Systems and Softwar, require some type of ground truth quality score (again defined, by an expert) that can be used to train a model to produce adapt-. 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. Software reusability is changing the way programmer’s code and organizations operate. In other words, software reusability is developing a brand new software from an existing one. This activity is to analyze the functional and nonfunctional requirements of target software. 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. into one complexity score (solid black line line). 21–27. formulate a reusability score by employing information from in more classes in order to regain high cohesion. As shown, the packages appear to have zero reuse rate. Component reuse programs. the formulation of the reuse rate of each software component. queries and easily integrating it with other tools. Ridge Regression [51] was used for train-, ing the regression model, while the dedicated regularized least-. ing whether the degree of reuse is acceptable. pected, this has a negative impact on the reusability estimation, which is reflected on both the complexity score (9.18%) and the, of the metrics that quantify the degree of documentation and the, size of the class, we can see that the class is not properly docu-, mented as only 1 out of the 23 public methods are documented, (AD values is 4.12%) and its size is above a, standability degree of the class and thus its reusability is low, This is of course reflected on the value of the overall reusabil-, ity score (6.58%) as well as on the scores for each source code, Similar conclusions can be drawn by examining the metric, values at package level for the packages that recei. formulate a reusability score by employing information from Each bin has been assigned with a reusability score based, on the reuse rate of the classes contained in the benchmark. 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