Reverse Engineering State and Strategy Design Patterns using Static Code Analysis

Mohamed, Khaled; Kamel, Amr

doi:10.14569/ijacsa.2018.090178

Cited by 2 publications

(1 citation statement)

References 32 publications

(38 reference statements)

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“…Fourth, code metrics analysis measuring various characteristics of the code such as complexity, coupling, and cohesion [10], [11]. The fifth approach proposed in previous research is pattern-matching techniques that examines the code to identify issues like violation to coding standards and best-practices, that have the potential of introducing defects in the code [12]- [14]. All these five approaches have one thing in common: identification of potential defects in the program.…”

Section: Introductionmentioning

confidence: 99%

Method level static source code analysis on behavioral change impact analysis in software regression testing

Muthengi,

Mugo,

Mutua

et al. 2024

IJEECS

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Though a myriad of changes take place in a software system during maintenance, behavioral changes carry the bulk of the reasons of software modifications. In assessing the impact of the changes made in software, static source code analysis plays a key role. However, static source code analysis can be a little complex depending on the reason for the expedition. Despite the work done so far, little focus has been made on the potential of changed methods analysis during static source code analysis in assessing the impact of the changes made in a software system. We propose and investigate a static source code analysis technique that would generate information on the modified methods in the source code. This study analyzes four aThough a myriad of changes take place in a software system during maintenance, behavioral changes carry the bulk of the reasons for software modifications. In assessing the impact of the changes made in the software, static source code analysis can be a little complex depending on the reason for the expedition. Despite the works done so far, little focus has been directed on the potential of changed methods during static source code analysis, in assessing the impact of the changes made in software. This study investigates a method-level static source code analysis technique that would generate information on the methods affected by changes made in the software. The work analyzed three Java projects. The results indicate an improvement in leveraging on the knowledge of edited methods in change impact assessment during regression testing. The approach enhances code review efforts in light of assessing operational behavior impacted by the changes made.Java projects and shows that an analysis of the changed methods reveals the level of regression testing that ought to be conducted for the changes made.

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