Giovanni Capobianco

On the role of the nouns in IR-based traceability recovery

The intensive human effort needed to manually manage traceability information has increased the interest in utilising semi-automated traceability recovery techniques. This paper presents a simple way to improve the accuracy of traceability recovery methods based on Information Retrieval techniques. The proposed method acts on the artefact indexing considering only the nouns contained in the artefact content to define the semantics of an artefact. The rationale behind such a choice is that the language used in software documents can be classified as a sectorial language, where the terms that provide more indication on the semantics of a document are the nouns. The results of a reported case study demonstrate that the proposed artefact indexing significantly improves the accuracy of traceability recovery methods based on the probabilistic or vector space based IR models.

Improving IR-based traceability recovery via noun-based indexing of software artifacts

One of the most successful applications of textual analysis in software engineering is the use of information retrieval (IR) methods to reconstruct traceability links between software artifacts. Unfortunately, because of the limitations of both the humans developing artifacts and the IR techniques any IR‐based traceability recovery method fails to retrieve some of the correct links, while on the other hand it also retrieves links that are not correct. This limitation has posed challenges for researchers that have proposed several methods to improve the accuracy of IR‐based traceability recovery methods by removing the ‘noise’ in the textual content of software artifacts (e.g., by removing common words or increasing the importance of critical terms). In this paper, we propose a heuristic to remove the ‘noise’ taking into account the linguistic nature of words in the software artifacts. In particular, the language used in software documents can be classified as a technical language, where the words that provide more indication on the semantics of a document are the nouns. The results of a case study conducted on five software artifact repositories indicate that characterizing the context of software artifacts considering only nouns significantly improves the accuracy of IR‐based traceability recovery methods. Copyright

Traceability Recovery Using Numerical Analysis

The paper proposes a novel Information Retrieval technique based on numerical analysis for recovering traceability links between code and software documentation. The results of a reported case study demonstrate that the proposed approach significantly outperforms two vector-based IR models, i.e., the Vector Space Model and Latent Semantic Indexing, and it is comparable and sometimes better than a probabilistic model, i.e., the Jensen-Shannon method. The paper also discusses the influence of each method with the specific artifact type considered and the artifact language.

Fluctuations in dusty plasmas

Dust charge and density fluctuations can substantially change basic plasma properties—dispersion of low frequency modes, plasma fluctuations—and introduce new effects—attraction of negatively charged dust particles, dust and ion stochastic heating—which cannot be found if dust fluctuations are neglected. The kinetic theory of fluctuations is used to describe these effects, in particular the changes in the spectral densities of the plasma fluctuations in un-magnetized plasmas in the presence of dust.

Winter survival of microbial contaminants in soil：An in situ verification

The aim of the research was to evaluate, at site scale, the influence of freezing and freeze/thaw cycles on the survival of faecal coliforms and faecal enterococci in soil, in a climate change perspective. Before the winter period and during grazing, viable cells of faecal coliforms and faecal enterococci were detected only in the first 10 cm below ground, while, after the winter period and before the new seasonal grazing, a lower number of viable cells of both faecal indicators was detected only in some of the investigated soil profiles, and within the first 5 cm. Taking into consideration the results of specific investigations, we hypothesise that the non-uniform spatial distribution of grass roots within the studied soil can play an important role in influencing this phenomenon, while several abiotic factors do not play any significant role. Taking into account the local trend in the increase of air temperature, a different distribution of microbial pollution over time is expected in spring waters, in future climate scenarios. The progressive increase in air temperature will cause a progressive decrease in freeze/thaw cycles at higher altitudes, minimising cold shocks on microbial cells, and causing spring water pollution also during winter.

Optimal Paths for Dual Propulsion Vehicles on Real Street Network Graphs

There are several examples of dual propulsion vehicles: hybrid cars, bi-fuel vehicles, electric bikes. Compute a path from a starting point to a destination for these typologies of vehicles requires evaluation of many alternatives. In this paper we develop a mathematical model, able to compute paths for dual propulsion vehicles, that takes in account the power consumption of the two propulsors, the different types of charging, the exchange of energy and, last but not least, the total cost of the path. We focus our attention on electric bikes and we perform several experiments on real street network graph. In our tests we took into account the slope of roads, the recharge in downhill streets and the effort of the cyclist. To validate the model we performed computational tests on properly generated instances set. This set of instances is composed of graphs representing real cities of all around the world. The computational tests show the effectiveness of our approach and its applicability on a real street network.