Reusability affecting factors and software metrics for reusability: A systematic literature review

Abstract

Measuring and estimating the reusability of software components is important towards finding reusable candidates. Researchers have shown that software metrics can be effectively used to assess software reusability. This work provides a systematic literature review to investigate the main factors that influence software reusability and how these identified factors can be quantified using software metrics. This paper also investigates tool availability of the identified software metrics. Based on the extensive study, we narrowed down 44 factors that could positively or negatively affect the reusability of software systems. In term of software metrics, we report our findings through five main families of metrics, namely coupling, cohesion, complexity, inheritance, and size. We found that most of the metrics examine reusability at the class-level, and the availability of software tools is limited. Furthermore, not all reusability affecting factors are equally impactful to assess the reusability of software components.While existing studies often discussed the impact of complexity towards software reusability, we found that only a handful of complexity metrics were meant for assessing reusability. We have identified several open challenges and gaps in the area, in particular lack of quantifiable measurement for reusability, limited software tools, and limited metrics that directly measure reusability.

A metadata driven process for assessing stability and reusability based on risk of change of software systems

“…In order to evaluate the reliability and accuracy of our proposed process, we perform static analysis (using software metrics) of some selected classes in order to check whether these metrics align with the assessment of our method. To establish the ground truth, the well‐known software metrics related to five reusability affecting factors (coupling, cohesion, complexity, inheritance, and size) are used for the selected projects 17 . Given the source code of selected projects, the work by Papamichail et al 10 calculated a large set of these metrics that we used as ground truth and also extensively used by numerous researchers that aspire to measure reusability 17 .…”

“…We review existing studies related to this area of research. The work related to reusability affecting factors and metrics for reusability has already been discussed in‐depth detail in our previous work 17 . Therefore, in this work, the main focus of the review is on the software changes, stability, and utilization of metadata from source code management systems.…”

“…There is no straight way to assess software reusability, and most existing works use static code metrics (coupling, cohesion, complexity, etc.) as a proxy metric to measure the reusability of the analyzed software 17 . However, traditional approaches that utilize static code metrics only stop at the identification of reusable candidates and ignore the stability (stable enough to be reused easily) of the candidate.…”

“…One of the main reasons for this is because there is no straightforward way to assess software reusability. Existing studies have attempted to use software metrics, and other quality attributes to assess software reusability 17 . The work by Bilal et al 17 conducted a systematic literature review and found a strong correlation between software metrics related to quality factors (such as coupling, cohesion, complexity, inheritance, and size) with software reuse, where they are often used to assess the reusability of software systems.…”

“…Existing studies have attempted to use software metrics, and other quality attributes to assess software reusability 17 . The work by Bilal et al 17 conducted a systematic literature review and found a strong correlation between software metrics related to quality factors (such as coupling, cohesion, complexity, inheritance, and size) with software reuse, where they are often used to assess the reusability of software systems. Software stability only comes into the picture (in software reuse) when the reusable candidates are identified, mainly because developers will then need to assess the reuse strategy based on its stability/ease of reuse.…”