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How Automated Code Analysis can be used Today and in the Future

  • April 17, 2021

Undetected faults in applications are one of the leading causes for implementation and distribution problems experienced by organizations. Is your development team using the right source code analysis tool to detect critical vulnerabilities and make the necessary fixes? Does poor software quality increase maintenance time, heighten security risks, or create more work for your developers? How much technical debt is involved with each development project in terms of broken components and maintenance needs? Traditional testing does not catch every vulnerability within an application. If dependable source code analysis tools are not being utilized prior to release or implementation, you could be letting future problems slip right through the cracks.

What is Source Code Analysis?

Source code vulnerability analysis tools are sets of automated solutions for assessing application code. These tools can be used to detect flaws, identify improvement areas, flag misused variables, or create documentation in order to ultimately create a higher quality end product. In modern time, simple upload interfaces can provide an entry point to automated static analysis which will assess the source code and will provide an alternative to manually evaluating each line of code.  The outputs are mapped data with detailed information designed in order to identify problem areas and provide references for proper usage. Some diagnostic methods require millions of input sample files for modern machine learning techniques; advances in the field of deep learning will continue to add value.  But not all of these solutions require massive amounts of test data cases or an extensive amount of time to run. Some methods offer a cost-effective approach to identifying areas of improvement within developed software.  A hybrid approach to the problems, including both big data and same static analysis offer the best results and the most useful feedback as a developer-aid. If poor quality, bad configurations, or generally hard to diagnose software issues are becoming a big problem for your organization, these tools offer a dependable, repeatable first-step toward solutions development.

Automated Code Analysis

Automated Analysis Detects Vulnerabilities and Increases Quality

Automated source code analysis offer countless benefits as your development team remains under pressure to rapidly complete software projects and meet end user or business requirements. Reusable functions, testing shortcuts, and tight delivery dates make it easy to miss critical flaws within software. Automated source code analysis tools supply an automated way to use repeatable, objective application risk flagging and references. Source code vulnerability analysis is a critical part of the solutions for:

  1. Software Quality
  2. Developer Productivity
  3. Application Complexity
  4. Technical Debt
  5. Software Risk

To measure the improvement derived an assessment of defined business functions or function points should be considered.  The cost of poor quality, security loophole-riddled, or difficult to maintain software needs is a critical handicap for virtually all enterprises in today’s age. Each application developed by or for your organization has a set number of functions it should accomplish, which can be used to measure complexity and help scope your development goals. Enabling your developers with the right toolset is a necessary first step. Undetected vulnerabilities and insufficient source code review cause several problems within an infrastructure including system-wide failures, security breaches, and performance degradation. Don’t let missed flaws or poor quality take down your infrastructure.

Core Benefits and Future Applications of Automated Code Analysis

  1. Code Conversation – Using code analysis with us we have provided a detailed code conversation utility mapping java source language to kotlin in excel format which helps you to identify, convert, or translate between source data easily.  This can help you understand another developer’s project without necessarily being familiar with both coding syntax patterns, we handle that for you.
  2. Better Continuity – When new developer joins a project there is always a learning period of studying the existing code base.  Code Analysis is helpful to a project with multiple different team members because we used same structure output and documentation for each source code language or application.  Therefore, with familiarity of code in general, you can quickly train and break down the existing code and proceed with the proper references and issues identified easily accessible.
  3. Identifying Misused Variables – Using a GNN based Code Analysis, we used scan code line by line with different algorithm logic to identify your code quality and structure. By using this pattern you can also identify misused variable in code.
  4. Identifying Security Risks – Code analysis can be used to identify security holes such as memory leaks or bad configurations in your source code. Using analysis of graphs or common patterns it can identify risks at a decently reliable rate. Some of the latest research in this field is included here:
  5. Automatically Tag Type Casting Requirements – Using code analysis pattern you can also identify different interface and classes parameters values in desire result which helps you to identify which class and interface have what require parameters.

Metacoder will be making its Automated Code Analysis tool available through our platform in Q2 2021.  With our services you can experience these benefits for an affordable per-use cost.  Our reports will guide your testing and development team towards solutions to in an efficient manner, saving valuable time and problem solving bandwidth.  Stay tuned for our the upcoming release and demonstration!