Solution
TCS MasterCraft™
TCS MasterCraft™: Enabling Cognitive and Intelligent Automation
Highlights
- The world is undergoing a remarkable transformation. It is shifting from the era of on-site data centers, where access was confined to computers within network firewalls, to the age of cloud-based applications.
- Digital transformation of enterprises is already a mandate, and when it comes to application modernization, the goal is to improve an application's business logic and functionality while ensuring it is customizable and compatible with new user standards and future updates.
- The conversational assistant plays a pivotal role in facilitating the reverse engineering process by deciphering complex software systems through dialogue, asking context-specific questions, and aiding in comprehending an application's function, structure, and behavior.
On this page
On this pageinpage
Reverse engineering
Reverse engineering extracts business logic from complex systems.
The world is transitioning from traditional on-site data centers to cloud-based applications, which offer flexibility to operate in the cloud, connect via APIs, and provide accessibility across devices. Digital transformation has become a mandate for enterprises, especially in application modernization, where the goal is to enhance business logic and functionality while ensuring compatibility with modern standards. The challenge lies in understanding an application's architecture for re-engineering, particularly when it has evolved over decades. Reverse engineering helps by extracting business logic from complex systems, a task made more efficient by conversational assistants. These tools facilitate comprehension by engaging users with context-specific questions, aiding in the analysis of an application’s function, structure, and behavior. As legacy systems evolve, rediscovering this information becomes critical, especially when subject matter experts (SMEs) are unavailable. Conversational tools streamline reverse engineering, making the process more accessible for code adaptation and modernization.
A human touch
Conversational assistants simplify technical aspects and humanize digital transformation.
Organizations are revitalizing legacy applications by migrating them to the cloud and adapting them to modern digital demands. This journey begins with analyzing legacy systems' source code to understand their inner workings. However, dissecting core code can be complex. Existing solutions provide insights, but making sense of them can be daunting.
Conversational assistants bridge this gap by adding a human touch to software code comprehension. Powered by extensive databases, they simplify technical aspects and navigate complex legacy applications. These assistants speed up understanding, make specialized knowledge accessible, and humanize digital transformation.
The global conversational AI and virtual assistant market is growing rapidly.
Conversational AI and virtual assistants facilitate legacy system transformation as trusted allies. This innovative approach accelerates modernization and broadens access to expertise.
Conversational assistant’s key benefits in application modernization:
- Simplify complex legacy application analysis
- Speed up understanding and expertise access
- Humanize digital transformation
- Accelerate legacy system modernization
- Broaden access to specialized knowledge
Conversational assistants are reshaping reverse engineering and application source code analysis in the digital age
Valuable partner
Conversational assistants support engineers through the reverse engineering journey, ultimately leading to successful modernization outcomes.
A conversational assistant integrated into engineering processes can provide real-time assistance and guidance, making the entire application modernization process more efficient and seamless.
Instant answers to engineering queries
- With a conversational assistant, engineers can ask questions, seek clarification, and receive instant responses about the application's architecture and re-engineering strategies, allowing for more accurate and effective modernization.
The conversational assistant: an SME
The conversational assistant provides contextual insights into applications, streamlining reverse engineering. Users gain an understanding of fields, files, variables, tables, and logic. Multi-language support (Spanish, Hebrew, Japanese, German, Dutch, French, and more) enables diverse users to utilize features and receive support in their preferred language.
Dynamic knowledge base creation
- A conversational assistant, in the context of source code analysis, operates by taking the source code as input, along with any accompanying comments and supporting documents related to the application. This allows the assistant to build a dynamic knowledge base specific to that application, which is a key differentiating factor compared to other existing bots.
- The assistant utilizes various methods, like documents, to acquire knowledge from the input. One approach is to learn from the information present within the comments. By analyzing the author's comments and other comments within the source code, the assistant can extract insights and understand the intentions and thought processes behind the code.
- Another method involves analyzing the code's syntax and structure. By examining the code's syntax, the assistant can identify patterns, dependencies, and relationships between elements, allowing for a deeper understanding of the code's functionality and behavior.
- The assistant can leverage external resources such as design documents, application manual files, or other supporting documents associated with the application. The assistant can enhance knowledge and provide more accurate and comprehensive insights by incorporating information from these documents.
Comprehensive code understanding
- By combining these approaches, the conversational assistant can establish a robust understanding of the source code and the application it represents. This enables the assistant to provide valuable guidance, answer queries, and offer recommendations based on its dynamic knowledge base. Ultimately, the conversational assistant enhances the code analysis process and assists engineers in making informed decisions during application modernization and reverse engineering efforts.
- The conversational assistant can assist in automating certain aspects of the reverse engineering process, such as code analysis and documentation generation. This saves valuable time and resources, enabling engineers to focus on crucial and complex tasks.
Enhancing efficiency and productivity
- Application modernization projects can enhance efficiency, accuracy, and productivity by integrating a conversational assistant into the digital transformation process. The conversational assistant is a valuable partner, supporting engineers throughout the reverse engineering journey, ultimately leading to successful modernization outcomes.
Role of KPIs
SME effort reduction, de-skilling, reduced time-to-market, and accurate quality of deliverables.
A machine learning-powered conversational assistant facilitates application analysis with contextual knowledge extraction. It processes user queries within the application context, using ML algorithms to enhance its capabilities. The system retrieves information from a comprehensive knowledge base, providing real-time responses to user queries. This boosts productivity with swift and accurate responses. Key performance indicators (KPIs) are crucial in enhancing software application transformation when integrated with reverse engineering. Let’s delve deeper to understand the role of KPIs for seamless transformation:
SME effort reduction and de-skilling:
ML-assisted conversational assistants reduce SME effort in reverse engineering legacy systems. Automated business rule extraction and technical blueprints enable non-SMEs to actively participate. This de-skilling effect scales the reverse engineering team, freeing SMEs to focus on core challenges and critical decisions and streamlining the process for greater efficiency.
Reduced time-to-market:
Integrating reverse engineering with ML-driven conversational assistants reduces SME dependency, enabling non-SMEs to participate. This boosts throughput, accelerates project timelines, and enhances competitiveness,allowing companies to adapt quickly to changing market demands and technologies.
Accurate quality of deliverables:
Accuracy is crucial in reverse engineering. Tool-aided analysis with a conversational assistant mitigates errors, ensuring precise knowledge extraction from legacy code. This surpasses reliance on documents or SMEs' tacit knowledge, providing a reliable foundation for software development. Improved accuracy enables organizations to confidently modernize legacy systems with a solid understanding.
Technical headway
Conversational assistants will feature recommendation engine, robust analytics module, predict code optimization, and more.
Shortly, conversational assistants are set to become integral to every transformation project, offering a holistic conversational experience throughout the journey. Here's a glimpse into the high-level technical enhancements:
Recommendation engine:
The conversational assistant will feature an advanced recommendation engine, leveraging ML and data analytics. It will analyze project-specific data and requirements to provide intelligent, data-driven recommendations for transformation projects.
Input application analytics:
A robust analytics module will be integrated into the assistant, enabling comprehensive analysis of input applications. This technical feature will provide valuable insights, driven by data, to inform decision-making during transformation initiatives.
Prediction of code optimization:
Advanced ML algorithms will be employed to predict code optimization possibilities. The assistant will offer proactive suggestions for optimizing code efficiency and enhancing the technical aspects of the transformation process.
Prediction of transformation options:
Leveraging predictive analytics, the assistant will anticipate various transformation options and evaluate potential pathways, empowering project teams to make informed technical decisions and streamline the transformation journey.
Speech enablement:
The conversational assistant will introduce speech enablement, leveraging natural language processing and speech recognition technologies. This enhancement will enable users to interact with the assistant through voice commands, enhancing accessibility and usability.
Continual learning in intent detection:
The assistant will undergo continual learning in its intent detection capabilities. Using ML will enhance its technical proficiency in understanding complex user queries and providing accurate responses.
Amplify output
Conversational assistant is expected to save 10-15% in productivity adding to the already good 40-50% automation rate.
Conversational assistants have the potential to reshape task handling and make processes more streamlined and automated through voice-powered systems. Integration of these conversational assistants in the field of application understanding and reverse engineering of source code, with continuously improving contextual knowledge on the fly, goes beyond mere convenience; it means improving customer experiences, optimizing field operations, and enhancing overall business management.
Conversational assistant represents a cutting-edge fusion of ML capabilities, specifically designed to seamlessly extract vital information from a broad spectrum of business applications and different domains. It provides a thorough look at these applications and digs into both the executable and non-executable lines of the code.
The extraction of such contextual intelligence plays a pivotal role in reducing reliance on SMEs, thereby streamlining processes and significantly expediting time-to-market while maintaining a high standard of precision. A conversational assistant is expected to save an extra 10-15% in productivity on top of the already good 40-50% automation rate it achieves. Embrace the future of application modernization led by conversational assistants, revolutionize your operations, and amplify productivity with the power of intelligent automation.
