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Nandamudi L. Vijaykumar

Publications and source records attributed to Nandamudi L. Vijaykumar.

2 recordsLinked to original sources

Establishing a Search String to Detect Secondary Studies in Software Engineering

Context: A tertiary study can be performed to identify related reviews on a topic of interest. However, the elaboration of an appropriate and effective search string to detect secondary studies is challenging for Software Engineering (SE) researchers. Objective: The main goal of this study is to propose a suitable search string to detect secondary studies in SE, addressing issues such as the quantity of applied terms, relevance, recall and precision. Method: We analyzed seven tertiary studies under two perspectives: (1) structure -- strings' terms to detect secondary studies; and (2) field: where searching -- titles alone or abstracts alone or titles and abstracts together, among others. We validate our string by performing a two-step validation process. Firstly, we evaluated the capability to retrieve secondary studies over a set of 1537 secondary studies included in 24 tertiary studies in SE. Secondly, we evaluated the general capacity of retrieving secondary studies over an automated search using the Scopus digital library. Results: Our string was capable to retrieve an optimum value of over 90\% of the included secondary studies (recall) with a high general precision of almost 60\%. Conclusion: The suitable search string for finding secondary studies in SE contains the terms "systematic review", "literature review", "systematic mapping", "mapping study" and "systematic map".

cs.SE↗

Abordagem probabilística para análise de confiabilidade de dados gerados em sequenciamentos multiplex na plataforma ABI SOLiD

The next-generation sequencers such as Illumina and SOLiD platforms generate a large amount of data, commonly above 10 Gigabytes of text files. Particularly, the SOLiD platform allows the sequencing of multiple samples in a single run, called multiplex run, through a tagging system called Barcode. This feature requires a computational process for separation of the data sample because the sequencer provides a mixture of all samples in a single output. This process must be secure to avoid any harm that may scramble further analysis. In this context, realized the need to develop a probabilistic model capable of assigning a degree of confidence in the marking system used in multiplex sequencing. The results confirmed the adequacy of the model obtained, which allows, among other things, to guide a process of filtering the data and evaluation of the sequencing protocol used.

q-bio.GN↗