EXACT: A tool for comprehending VBA-based Excel spreadsheet applications

Amalfitano, Domenico; Simone, Vincenzo De; Fasolino, Anna Rita; Tramontana, Porfirio

doi:10.1002/smr.1787

Cited by 4 publications

(3 citation statements)

References 54 publications

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“…To limit the impact on the existing tools, the integration architecture may rely on “adapter” connectors that enable a not invasive interconnection among the tools. In this step, reverse engineering processes, involving either the data produced by the tools() or the tool user interfaces, may have to be carried out. In these cases, data wrapping or tool wrapping techniques() may have to used to design the needed connectors.…”

Section: Improving Traceability Links Management Through Tool‐integramentioning

confidence: 99%

“…Eventually, to extract the testing results, we had to develop an Excel Adapter component for retrieving information from Excel spreadsheet files. We exploited the reverse engineering process proposed in Amalfitano et al and the tool reported in Amalfitano et al for inferring the data models of the test case and the test case result artifacts stored in spreadsheet files. These models were needed for importing the data in the ALM platform.…”

Section: Using the Proposed Process In A Real Automotive Industrial Cmentioning

confidence: 99%

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Using tool integration for improving traceability management testing processes: An automotive industrial experience

Amalfitano

Simone

Maietta

et al. 2019

J Software Evolu Process

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Despite the high relevance of traceability in software processes, the activities of traceability creation and management are not always adequately supported in practice. The lack of integration between the tools adopted in the development processes is one of the main causes of such an ineffective management, where traceability relationships are still manually generated and maintained. In this paper we present an industrial experience we performed for improving the traceability management in a testing process performed in the Fiat Chrysler Automobiles company. In this context, we carried out a process for analyzing and identifying the main issues due to the ineffective traceability management and proposed a solution for addressing them.We designed and implemented a software architecture for integrating the existing application lifecycle management platform with the tools used in the process with the aim of automating the process execution and the traceability links management. The new architecture was validated by a case study that showed how the integration solution produced beneficial effects on quality attributes of the testing process. KEYWORDS automotive, industrial case study, software process improvement, tool integration, traceability management 1 INTRODUCTION Requirement traceability was defined by Gotel et al, 1 as the ability to describe and follow the life of a requirement, in both forward and backward directions.It is realized in practice by establishing relationships, usually defined trace links, between the requirements and one or more artifacts of the system. 2 Since then, this definition was extended, and nowadays, we talk more in general about software traceability for indicating the creation and the use of links (or connections) between different kinds of software artifacts such as requirements, models, source code, test cases, or test results. These connections are called trace links and connect in a bidirectional way a source artifact to a target artifact. The research community is devoting great efforts for addressing the topic of the traceability management that is the planning, the organization, and the coordination of all the activities related to traceability, including the creation, maintenance, and use of trace links. 3 Moreover, both software development standards and process assessment frameworks, such as ISO/IEC 15504, automotive SPICE, capability maturity model integration (CMMI), ISO 26262, and IEC 61508, suggest the companies to adopt traceability management solutions to guarantee Abbreviations: ALM, application lifecycle management; API, application programming interface; DSML, domain-specific modeling language; ECU, electronic control unit; FCA, Fiat Chrysler Automobiles; GUI, graphical user interface; ITL, incorrect traceability links; ITLRP, incorrect traceability links reduction percentage; MIL, model in the loop; MTL, missing traceability links; MTLRP, missing traceability links reduction percentage; RQ, research question; SP, speedup percentage; SPEM, software and system pr...

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Section: Improving Traceability Links Management Through Tool‐integramentioning

confidence: 99%

Section: Using the Proposed Process In A Real Automotive Industrial Cmentioning

confidence: 99%

Using tool integration for improving traceability management testing processes: An automotive industrial experience

Amalfitano

Simone

Maietta

et al. 2019

J Software Evolu Process

Self Cite

View full text Add to dashboard Cite

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“…The derived model is visualized as a UML class diagram. Another interesting work of Amafitano et al [39] presents a tool that helps to analyze connections of cells and VBA code.…”

Section: Related Workmentioning

confidence: 99%

On the refinement of spreadsheet smells by means of structure information

Koch

Hofer

Wotawa

2019

Journal of Systems and Software

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Spreadsheet users are often unaware of the risks imposed by poorly designed spreadsheets. One way to assess spreadsheet quality is to detect smells which attempt to identify parts of spreadsheets that are hard to comprehend or maintain and which are more likely to be the root source of bugs. Unfortunately, current spreadsheet smell detection techniques suffer from a number of drawbacks that lead to incorrect or redundant smell reports. For example, the same quality issue is often reported for every copy of a cell, which may overwhelm users. To deal with these issues, we propose to refine spreadsheet smells by exploiting inferred structural information for smell detection. We therefore first provide a detailed description of our static analysis approach to infer clusters and blocks of related cells. We then elaborate on how to improve existing smells by providing three example refinements of existing smells that incorporate information about cell groups and computation blocks. Furthermore, we propose three novel smell detection techniques that make use of the inferred spreadsheet structures. Empirical evaluation of the proposed techniques suggests that the refinements successfully reduce the number of incorrectly and redundantly reported smells, and novel deficits are revealed by the newly introduced smells.

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