Review and Evaluation of Cohesion and Coupling Metrics at Package and Subsystem Level

Software obfuscation techniques are increasingly being used to prevent attackers from exploiting security flaws and launching successful attacks. With research on software obfuscation techniques rapidly growing, many software obfuscation techniques with varying quality and strength have been proposed in the literature. However, the literature on obfuscation techniques has not yet been coherently collated and reviewed. This research paper aims to present an overview of state-of-the-art software obfuscation techniques, focusing on quality and strength. A systematic analysis and synthesis of literature published between 2010 and April 2021 has been performed to identify the common measures to quantify obfuscation and their measures, the publication venue, and the home country of the researchers. We have identified the obfuscation quality attributes, such as potency, resilience, cost, stealth, and similarity, that are the most widely used metrics to evaluate the quality of obfuscation techniques. In addition, different measures have been used to quantify these qualities, such as complexity (to measure potency), human effort (to measure resilience), efficiency (to estimate cost), and multiclass performance metrics, distance measures, and matching method (to quantify similarity). These measures were then categorized into sub-measures. The literature lacks research in the following two areas: empirical research using a case study strategy, i.e., realworld datasets, and measurements of obfuscation stealth. Researchers did not address stealth as clearly as they addressed potency, cost, and similarity.

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“…The last observation about the measures is their granularity level. There are three granularity levels [100], as follows:…”

Section: E Measure-based Analysis (Rq5)mentioning

confidence: 99%

“…In contrast, cohesion is the degree of intra-dependence in a single module. From a software quality perspective, low coupling and high cohesion are two signs of a good design[100] 15. Class Splitter splits the non-obfuscated classes into obfuscated ones by inserting dummy classes.…”

mentioning

confidence: 99%

Measuring Software Obfuscation Quality–A Systematic Literature Review

2021

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“…It is worth noting here that the nonnegativity attribute of software metrics (among other properties) is proposed in the literature and has been widely adopted as a formal property to evaluate software metrics [33]. The RV metric possesses this property because the variables used in it are the number of corresponding UCs, and such numbers cannot be negative.…”

Section: Non-negativitymentioning

confidence: 99%

Towards Measuring Software Requirements Volatility: A Retrospective Analysis

Ebad

2017

MJCS

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Requirement management (RM) is a fundamental activity in requirements engineering. It keeps track of all the requirements changes that would cause errors or resulted in software delays or cost overruns. When requirements have many changes over time, they have a tendency to be highly volatile. This volatility depends on several factors such as organizational complexity, process maturity of the company, and development phase. Managing the requirements quantitatively by metrics is a good way to understand whether RM is efficient or not. In this paper, we propose a new metric to measure the requirements volatility of object-oriented systems in terms of use cases; we use retrospective analysis that examines the amount of change applied in successive versions of a software product. We theoretically validated our metric through a set of prominent mathematical properties. We also empirically validated our metrics using three versions of an open source project, JHotDraw. Measurements of the metric were shown to be consistent with previous measurements of the JHotDraw versions conducted at the architecture design level. The study results in a foundation for further empirical retrospective studies of the requirements properties.Keywords: requirements engineering, requirements volatility, requirements management, software metrics, use cases, software evolution. INTRODUCTIONSoftware requirements describe the services provided by the system and its operational constraints [1] [2]. These requirements reflect the needs of system stakeholders (including paying customers, users and developers). The process of finding out, analyzing, documenting, and checking these services and constraints is called requirements engineering (RE) . From an evolution perspective, volatile requirements are likely to change after the system has been become operational or during the system development process. An example, is the requirements resulting from government healthcare policies [2]. These requirements must evolve to reflect the changed view of the system in development. Furthermore, the

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Evaluation of Software Reusability Based on Coupling and Cohesion

Priyalakshmi

Latha

2018

Int. J. Soft. Eng. Knowl. Eng.

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Code reuse has become very popular among software developers in recent times since it saves time and resources. One of the significant difficulties to software reuse is the time pertaining to assess the fitness of the reusable code components. Over the recent years, code search engines have made momentous advancement in establishing the semantic suitability of software components for new usage scenarios. But the issue of evaluating software components based on their nonfunctional suitability has been overlooked to a large extent. The maintenance and reusability of software systems are highly influenced by the structural properties of system classes like complexity, size, coupling, cohesion, etc. The quality of object-oriented code or design artifacts is commonly measured by analyzing the structure of these artifacts in terms of the interdependencies of classes and components as well as their internal elements. In this paper, we perform an empirical analysis on Python packages for the two measures namely coupling and cohesion. The coupling score of a module is computed as module imports and the cohesion score of a module is evaluated as call dependency between classes and global functions of the module. Finally, the proposed work evaluates a package in terms of reusability score which is a cumulative score of the coupling scores and cohesion scores of all the modules within the package. The study has evaluated 15 different packages and five different releases of one single package for reusability. We have empirically tested that the Halstead’s effort metric is inversely proportional to the reusability score. The reusability score was validated using four code detuners. The proposed work was compared with the existing metrics namely cyclomatic complexity and maintainability Index showing satisfactory results.

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Review and Evaluation of Cohesion and Coupling Metrics at Package and Subsystem Level

Cited by 3 publications

References 17 publications

Measuring Software Obfuscation Quality–A Systematic Literature Review

Measuring Software Obfuscation Quality–A Systematic Literature Review

Towards Measuring Software Requirements Volatility: A Retrospective Analysis

Evaluation of Software Reusability Based on Coupling and Cohesion

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