Abstract Spreadsheets are very common for information processing to support decision making by both professional developers and non-technical end users. Moreover, business intelligence and artificial intelligence are increasingly popular in the industry nowadays, where spreadsheets have been used as, or integrated into, intelligent or expert systems in various application domains. However, it has been repeatedly reported that faults often exist in operational spreadsheets, which could severely compromise the quality of conclusions and decisions based on the spreadsheets. With a view to systematically examining this problem via survey of existing work, we have conducted a comprehensive literature review on the quality issues and related techniques of spreadsheets over a 35.5-year period (from January 1987 to June 2022) for target journals and a 10.5-year period (from January 2012 to June 2022) for target conferences. Among other findings, two major ones are: (a) Spreadsheet quality is best addressed throughout the whole spreadsheet life cycle, rather than just focusing on a few specific stages of the life cycle. (b) Relatively more studies focus on spreadsheet testing and debugging (related to fault detection and removal) when compared with spreadsheet specification, modeling, and design (related to development). As prevention is better than cure, more research should be performed on the early stages of the spreadsheet life cycle. Enlightened by our comprehensive review, we have identified the major research gaps as well as highlighted key research directions for future work in the area.

Abstract Combinatorial interaction testing (CIT) aims at constructing a covering array (CA) of all value combinations at a specific interaction strength, to detect faults that are caused by the interaction of parameters. CIT has been widely used in different applications, with many algorithms and tools having been proposed to support CA construction. To date, however, there appears to have been no studies comparing different CA constructors when only some of the CA test cases are executed. In this paper, we present an investigation of five popular CA constructors: ACTS, Jenny, PICT, CASA and TCA. We conducted empirical studies examining the five programs, focusing on interaction coverage and fault detection. The experimental results show that when there is no preference or special justification for using other CA constructors, then Jenny is recommended—because it achieves better interaction coverage and fault detection than the other four constructors in many cases. Our results also show that when using ACTS or CASA, their CAs must be prioritized before testing. The main reason for this is that these CAs can result in considerable interaction coverage or fault detection capabilities when executing a large number of test cases; however, they may also produce the lowest rates of fault detection and interaction coverage.

Abstract In fault‐based Boolean expression testing, the main challenge is to generate effective test cases that can detect faults within expressions. Previous studies show that it is hard to detect literal insertion faults, more specifically Disjunctive literal insertion fault (LIF[+]) compared with other faults in Boolean expressions. Researchers have been using different strategies such as multiple near false point coverage (MNFP) and modified condition decision coverage (MCDC) to detect LIF[+] faults. However, these strategies have their own limitations. For example, MNFP can only be applied when the expression is in irredundant disjunctive normal form (IDNF), and MCDC detects a low percentage of LIF[+] faults. In this paper, we propose an abstract syntax tree (AST)‐based test case generation strategy for LIF[+] fault detection that overcomes these limitations. Furthermore, our experimental results indicate that, on average, the test suites satisfying the proposed strategy can detect approximately 97.3% of LIF[+] faults for general form expressions and 89.7% of LIF[+] faults for IDNF expressions, which are 15.6% and 13.8% improvement, respectively, compared to the MCDC test suites. Moreover, the size of the required test suite is smaller than that of MCDC test suite.

Fault based testing is a technique for choosing test cases to reveal certain classes of faults. Due to limited resources and time, testing professionals use their personal experience to (1) "guess" which fault classes are most likely to be present and, then, (2) select appropriate testing methods to reveal such fault classes. The quality of the software depends on whether they can make a good "guess" about the type of faults present and then choose the right testing methods to reveal those faults. However, there is little empirical evidence available in the open literature to support these intuitions. For example, there is no empirical evidence about which types of faults are most commonly made by software developers. By examining the source code changes when faults were fixed in seven open source software artifacts, we propose to classify bug fix patterns into fault classes, and recorded the relative frequencies of those fault classes. This paper reports our findings related to "ifconditional" fixes.

This paper presents an extremely compact, highly efficient hardware implementation of the Reed Solomon (RS) decoder. Such efficiency is of critical importance for the next generation of passive optical networks featuring bit rates of 10 Gb/s, high bit error rates and high cost sensitivity. RS codes are widely used for error correction in optical communication networks. The central element of a t-error correcting RS decoder is the key equation solver, which is the most time-critical stage in the RS decoder operation. It uses 2t equations to determine up to 2t unknown values. A key equation solver typically performs the Berlekamp-Massey (BM) algorithm or the Modified Euclidean (ME) algorithm. Hardware implementations of these algorithms usually include a large number of Galois Field (GF) multipliers needed to achieve the required throughput. This paper presents a scalable BM architecture and a scalable ME architecture that minimizes the number of GF multipliers by their higher utilization. This is achieved through efficient control that avoids idle cycles and also through optimal grouping of multipliers into parallel structures given the bit error distribution for the respective optical network. The major building block of this architecture is a compact, programmable GF processor (GFP) capable of high frequency operation.

Detection conditions of specific classes of faults have recently been studied by many researchers. Under the assumption that at most one of these faults occurs in the software under test, these fault detection conditions were mainly used in two ways. First, they were used to develop test case selection strategies for detecting corresponding classes of faults. Second, they were used to study fault class hierarchies, where a test case that detects a particular class of faults can also detect some other classes of faults. In this paper, we study detection conditions of double faults. Besides developing new test case selection strategies and studying new fault class hierarchies, our analysis provides further insights to the effect of fault coupling. Moreover, these fault detection conditions can be used to compare effectiveness of existing test case selection strategies (which were originally developed for the detection of single occurrence of certain classes of faults) in detecting double faults that may be present in the software

Kuhn, followed by Tsuchiya and Kikuno, have developed a hierarchy of relationships among several common types of faults (such as variable and expression faults) for specification-based testing by studying the corresponding fault detection conditions. Their analytical results can help explain the relative effectiveness of various fault-based testing techniques previously proposed in the literature. This article extends and complements their studies by analyzing the relationships between variable and literal faults, and among literal, operator, term, and expression faults. Our analysis is more comprehensive and produces a richer set of findings that interpret previous empirical results, can be applied to the design and evaluation of test methods, and inform the way that test cases should be prioritized for earlier detection of faults. Although this work originated from the detection of faults related to specifications, our results are equally applicable to program-based predicate testing that involves logic expressions.

Abstract This paper considers test case selection for programs whose specifications are expressed by Boolean algebra. The approach is to select test cases based on Boolean specifications. Three test case selection strategies are proposed that aim at the detection of theliteral insertion faultand theliteral reference fault. Although theMAX‐Bstrategy proposed by Weyukeret al.guarantees detection of these types of faults, the proposed strategies are more effective in the sense that the derived test cases form a subset of those selected by theMAX‐Bstrategy. Copyright © 2001 John Wiley & Sons, Ltd.

The problem of test suite reduction is to find a subset of test cases from the test suite that can still satisfy the same testing objective. Such a subset is referred to as a representative set of the test suite. We use a problem reduction technique, namely the 1-to-1 redundancy dividing strategy, to find the optimal representative sets, which are the representative sets of the smallest size. The 1-to-1 redundancy dividing strategy guarantees that an optimal representative set of the reduced test suite is still an optimal representative set of the original one. However, the converse is not necessarily true. This paper investigates how to find all optimal representative sets of the original test suite from the reduced one. Furthermore, for the minimal representative sets whose proper subsets are not representative sets, the same problem is addressed.

Test data selection for software represented as Boolean formulae has not received much attention until the last decade. Most of the approaches are expression driven because generation of test cases is based on the Boolean formulae being tested. The paper discusses test data generation using a fault based approach in the sense that generation of test cases is based on particular types of faults occurring in the Boolean expression. Two special types of faults are considered. Moreover, two strategies of test case selection that guarantee the detection of these two types of faults are proposed.