A logical spreadsheet is a spreadsheet in which the formula language is composed of logical expressions. Logical spreadsheets were invented shortly after traditional electronic spreadsheets were introduced, but since then logical spreadsheet research has been somewhat sparse. Recently, however, there has been a resurgence in the interest of logical spreadsheets in the research community. In this article, we summarize logical spreadsheet research up to this point.

Usability and usefulness have made the spreadsheet one of the most successful computing applications of all times: millions rely on it every day for anything from typing grocery lists to developing multimillion-dollar budgets. One thing spreadsheets are not very good at is manipulating the symbolic data and helping users make decisions based on them. By tapping into recent research in Logic Programming, Databases and Cognitive Psychology, we propose a deductive extension to the spreadsheet paradigm that precisely addresses this issue. The accompanying tool, which we call NEXCEL, is intended as an automated assistant for the daily reasoning and decision-making needs of computer users, in the same way as a spreadsheet application such as Microsoft Excel assists them every day with simple and complex calculations. Users without formal training in Logic or even Computer Science can interactively define logical rules in the same simple way as they define formulas in Excel. NEXCEL immediately evaluates these rules, thereby returning lists of values that satisfy them, again just like with numerical formulas. The deductive component is seamlessly integrated into the traditional spreadsheet so that a user not only still has access to the usual functionalities but is also able to use them as part of the logical inference and, dually, to embed deductive steps in a numerical calculation.

Spreadsheets are a widespread tool for a variety of tasks, particularly in business settings. Spreadsheet users employ a form of programming that, although popular, is highly error-prone and has limited expressiveness. A promising approach to overcome these shortcomings is to augment spreadsheets with logic-based knowledge representation and reasoning (KR&R) functionality. In this paper, we present Logic Embedded in SpreadSheets (LESS), a system which integrates PowerLoom, a highly expressive logic-based KR&R system, with Microsoft (MS) Excel. The design of LESS provides different tiers of functionality that explore trade-offs between direct access to the underlying logic engine and user-friendly support for spreadsheets users. A prototype of LESS was implemented as an MS Excel add-in.

We exploit the spreadsheet metaphor to make deductive problem-solving methods available to the vast population of spreadsheet end-users. In particular, we show how the function-based problem-solving capabilities of spreadsheets can be extended to include logical deductive methods in a way that is consistent with the existing spreadsheet ‘look and feel’. The foundation of our approach is the integration of a standard deductive logic system into a successful Commercial-Off-The-Shelf (COTS) spreadsheet. We have demonstrated this by designing and implementing an extension to Excel that manages the integration of Excel and a deductive logic engine based on the World Wide Web Consortium (W3C) standard ontology language OWL + SWRL.

The promise of rule-based computing was to allow end-users to create, modify, and maintain applications without the need to engage programmers. But experience has shown that rule sets often interact in subtle ways, making them difficult to understand and reason about. This has impeded the widespread adoption of rule-based computing. This paper describes the design and implementation of XcelLog, a user-centered deductive spreadsheet system, to empower non-programmers to specify and manipulate rule-based systems. The driving idea underlying the system is to treat sets as the fundamental data type and rules as specifying relationships among sets, and use the spreadsheet metaphor to create and view the materialized sets. The fundamental feature that makes XcelLog suitable for non-programmers is that the user mainly sees the effect of the rules; when rules or basic facts change, the user sees the impact of the change immediately. This enables the user to gain confidence in the rules and their modification, and also experiment with what-if scenarios without any programming. Preliminary experience with using XcelLog indicates that it is indeed feasible to put the power of deductive spreadsheets for doing rule-based computing into the hands of end-users and do so without the requirement of programming or the constraints of canned application packages.

In this article, we describe PrediCalc, a logical spreadsheet that allows for many-to-many constraints and propagation in all directions. We explain PrediCalc’s update mechanism and PrediCalc’s unique approach to handling inconsistencies between the spreadsheet values and the spreadsheet formulas. We have developed a paraconsistent entailment relation for the purpose of computing the consequences of PrediCalc’s value assignments under inconsistency.

We close with thoughts on the prospects of logical spreadsheets on the World Wide Web, and describe our initial Websheet prototypes.