In the field computer science, robustness is the ability of a computer system to cope with errors during execution and to cope with erroneous input. Robustness can encompass many areas of computer science, such as robust programming, robust machine learning, robust security network etc.
In the present day information – centric society, Data Base Management Systems (DBMS) play an important role in various fields as economics, health care, resource management etc., to name a few. DBMS provide various functions that allow management of a database and its data which can be classified into four main functional groups as Data Definition (creation, modification and removal of definitions that define the organization of the data), Data Update (insertion, modification, and deletion of the actual data), Data Retrieval (data retrieval through querying, in a form directly usable or for further processing by other applications), and Data Administration (registering and monitoring of users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure). In view of their usage in many safety critical and mission critical systems, robustness is a sought after attribute of a DBMS.
Existing, de-facto standard user interface to query the information present in a database is SQL (Structured Query Language), a Relational DBMS (RDBMS). A structural USP of SQL is its declarative persona, which enables users to focus solely on query formulation, leaving it to the database system to identify an efficient execution strategy.
In the thematic article of this issue titled Robust Query Processing in Database Systems, the author opines that the declarative constitution of SQL is also its Achilles heel as the execution strategies chosen by the system often turn out, in hindsight, to be highly sub-optimal as compared to the ideal choice. The author proceeds to present a sampling of recent techniques that address the sub-optimality issue, providing provable and attractive performance guarantees. The article concludes with exemplars of open research problems that need to be addressed before a holistic solution to robust query processing in database systems can be achieved.
A very important application of AI is in Planning. Planning is the process of thinking about the activities required to achieve a desired goal and is fundamental to intelligent behaviour. Planning is one of the most important project management and time management techniques. Planning is preparing a sequence of action steps to achieve some specific goal. If a person does it effectively, they can reduce much of the necessary time and effort of achieving the goal. A plan is like a map. When following a plan, a person can see how much they have progressed towards their project goal and how far they are from their destination.
Planning has a specific process and is necessary for multiple occupations (particularly in fields such as management, business, etc. In each field, there are different types of plans that help companies achieve efficiency and effectiveness. An important, albeit often ignored aspect of planning, is the relationship it holds to forecasting. Forecasting can be described as predicting what the future will look like, whereas planning predicts what the future should look like for multiple scenarios. Planning is a combination of forecasting with preparation of scenarios. It also suggests how to react in each possible scenario. Planning has been used in many industrial applications but they are still few and far between compared to other sub-ﬁelds of AI like learning, constraints and business rules.
In their paper, titled Towards Planning in Mainstream Applications-Important Considerations, the authors highlight key considerations that are important in practice and articulate the issues therein which if addressed, is expected to trigger a new wave of planning-based applications.
In continuation of his article on the Essence of Quantum Computing published in the previous issue, the author deals with such exotic aspects as superposition, entanglement and collapse of quantum states of that foundation to show how powerful quantum algorithms can be constructed for efficient computation. By a variety of examples, the author has shown the power of quantum computing and has described some of the prized algorithms. For the benefit of readers requiring recalling of the underlying mathematics, two relevant appendixes have been included. Further, for readers desirous of getting some hands-on experience with a few of the algorithms presented are provided with necessary URL.
Finally, in continuation of a their series on Experiential Learning of Networking Technologies, the authors deal with an important issue of web security that has assumed importance due to widespread usage of e-commerce. They opine that a widespread but dangerously incorrect belief among web users is that all security issues are taken care of when a website uses HTTPS (secure HTTP). While HTTPS does provide security, websites are often developed and deployed in ways that make them and their users vulnerable to hackers. The authors explore some of these vulnerabilities by introducing key ideas and then provide several experiential learning exercises so that readers can understand the challenges and possible solutions to them in a hands-on manner.
I trust that the readers find this edition informative and of significant value.