Using software metrics to increase efficiency in product creation

Opinnäytetyö etsii korrelaatiota ohjelmistomittauksella saavutettujen tulosten ja ohjelmasta löytyneiden virheiden väliltä. Työssä käytetään koeryhmänä jo olemassaolevia ohjelmistoja. Työ tutkii olisiko ohjelmistomittareita käyttämällä ollut mahdollista paikallistaa ohjelmistojen ongelmakohdat ja näin saada arvokasta tietoa ohjelmistokehitykseen. Mittausta voitaisiin käyttää resurssien parempaan kohdentamiseen koodikatselmuksissa, koodi-integraatiossa, systeemitestauksessa ja aikataulutuksessa. Mittaamisen avulla nämä tehtävät saisivat enemmän tietoa resurssien kohdistamiseen. Koeryhmänä käytetään erilaisia ohjelmistotuotteita. Yhteistä näille kaikille tuotteille on niiden peräkkäiset julkaisut. Uutta julkaisua tehtäessä, edellistä julkaisua käytetään pohjana, jonka päällekehitetään uutta lähdekoodia. Tämän takia ohjelmistomittauksessa pitää pystyä erottelemaan edellisen julkaisun lähdekoodi uudesta lähdekoodista. Työssä käytettävät ohjelmistomittarit ovat yleisiä ja ohjelmistotekniikassalaajasti käytettyjä mittaamaan erilaisia lähdekoodin ominaisuuksia, joiden arvellaan vaikuttavan virhealttiuteen. Tämän työn tarkoitus on tutkia näiden ohjelmistomittareiden käytettävyyttä koeryhmänä toimivissa ohjelmistoympäristöissä. Käytännön osuus työstä onnistui löytämään korrelaation joidenkinohjelmistomittareiden ja virheiden väliltä, samalla kuin toiset ohjelmistomittarit eivät antaneet vakuuttavia tuloksia. Ohjelmistomittareita käyttämällä näyttää olevan mahdollista tunnistaa virhealttiit kohdat ohjelmasta ja siten parantaa ohjelmistokehityksen tehokkuutta. Ohjelmistomittareiden käyttö tuotekehityksessäon perusteltavaa ja niiden avulla mahdollisesti pystyttäisiin vaikuttamaan ohjelmiston laatuun tulevissa julkaisuissa.

A Communication Middleware Quality Enhancement with Qt Framework

In this thesis, a Peer-to-Peer communication middleware for mobile environment is developed using the Qt framework and the Qt Mobility extension. The Peer-to-Peer middleware – called as PeerHood – is for service sharing in network neighborhood. In addition, the PeerHood enables service connectivity and device monitoring functionalities. The concept of the PeerHood is already available in native C++ implementation on Linux platform using services from the platform. In this work, the PeerHood concept is remade to be based on use of the Qt framework. The objective of the new solution is to increase PeerHood quality with using functionalities from the Qt framework and the Qt Mobility extension. Furthermore, by using the Qt framework, the PeerHood middleware can be implemented to be portable cross-platform middleware. The quality of the new PeerHood implementation is evaluated with defined quality factors and compared with the existing PeerHood. Reliability, CPU usage, memory usage and static code analysis metrics are used in evaluation. The new PeerHood is shown to be more reliable and flexible that the existing one.

Towards increased productivity and quality in software development using agile, lean and collaborative approaches

Dagens programvaruindustri står inför alltmer komplicerade utmaningar i en värld där programvara är nästan allstädes närvarande i våra dagliga liv. Konsumenten vill ha produkter som är pålitliga, innovativa och rika i funktionalitet, men samtidigt också förmånliga. Utmaningen för oss inom IT-industrin är att skapa mer komplexa, innovativa lösningar till en lägre kostnad. Detta är en av orsakerna till att processförbättring som forskningsområde inte har minskat i betydelse. IT-proffs ställer sig frågan: “Hur håller vi våra löften till våra kunder, samtidigt som vi minimerar vår risk och ökar vår kvalitet och produktivitet?” Inom processförbättringsområdet finns det olika tillvägagångssätt. Traditionella processförbättringsmetoder för programvara som CMMI och SPICE fokuserar på kvalitets- och riskaspekten hos förbättringsprocessen. Mer lättviktiga metoder som t.ex. lättrörliga metoder (agile methods) och Lean-metoder fokuserar på att hålla löften och förbättra produktiviteten genom att minimera slöseri inom utvecklingsprocessen. Forskningen som presenteras i denna avhandling utfördes med ett specifikt mål framför ögonen: att förbättra kostnadseffektiviteten i arbetsmetoderna utan att kompromissa med kvaliteten. Den utmaningen attackerades från tre olika vinklar. För det första förbättras arbetsmetoderna genom att man introducerar lättrörliga metoder. För det andra bibehålls kvaliteten genom att man använder mätmetoder på produktnivå. För det tredje förbättras kunskapsspridningen inom stora företag genom metoder som sätter samarbete i centrum. Rörelsen bakom lättrörliga arbetsmetoder växte fram under 90-talet som en reaktion på de orealistiska krav som den tidigare förhärskande vattenfallsmetoden ställde på IT-branschen. Programutveckling är en kreativ process och skiljer sig från annan industri i det att den största delen av det dagliga arbetet går ut på att skapa något nytt som inte har funnits tidigare. Varje programutvecklare måste vara expert på sitt område och använder en stor del av sin arbetsdag till att skapa lösningar på problem som hon aldrig tidigare har löst. Trots att detta har varit ett välkänt faktum redan i många decennier, styrs ändå många programvaruprojekt som om de vore produktionslinjer i fabriker. Ett av målen för rörelsen bakom lättrörliga metoder är att lyfta fram just denna diskrepans mellan programutvecklingens innersta natur och sättet på vilket programvaruprojekt styrs. Lättrörliga arbetsmetoder har visat sig fungera väl i de sammanhang de skapades för, dvs. små, samlokaliserade team som jobbar i nära samarbete med en engagerad kund. I andra sammanhang, och speciellt i stora, geografiskt utspridda företag, är det mera utmanande att införa lättrörliga metoder. Vi har nalkats utmaningen genom att införa lättrörliga metoder med hjälp av pilotprojekt. Detta har två klara fördelar. För det första kan man inkrementellt samla kunskap om metoderna och deras samverkan med sammanhanget i fråga. På så sätt kan man lättare utveckla och anpassa metoderna till de specifika krav som sammanhanget ställer. För det andra kan man lättare överbrygga motstånd mot förändring genom att introducera kulturella förändringar varsamt och genom att målgruppen får direkt förstahandskontakt med de nya metoderna. Relevanta mätmetoder för produkter kan hjälpa programvaruutvecklingsteam att förbättra sina arbetsmetoder. När det gäller team som jobbar med lättrörliga och Lean-metoder kan en bra uppsättning mätmetoder vara avgörande för beslutsfattandet när man prioriterar listan över uppgifter som ska göras. Vårt fokus har legat på att stöda lättrörliga och Lean-team med interna produktmätmetoder för beslutsstöd gällande så kallad omfaktorering, dvs. kontinuerlig kvalitetsförbättring av programmets kod och design. Det kan vara svårt att ta ett beslut att omfaktorera, speciellt för lättrörliga och Lean-team, eftersom de förväntas kunna rättfärdiga sina prioriteter i termer av affärsvärde. Vi föreslår ett sätt att mäta designkvaliteten hos system som har utvecklats med hjälp av det så kallade modelldrivna paradigmet. Vi konstruerar även ett sätt att integrera denna mätmetod i lättrörliga och Lean-arbetsmetoder. En viktig del av alla processförbättringsinitiativ är att sprida kunskap om den nya programvaruprocessen. Detta gäller oavsett hurdan process man försöker introducera – vare sig processen är plandriven eller lättrörlig. Vi föreslår att metoder som baserar sig på samarbete när processen skapas och vidareutvecklas är ett bra sätt att stöda kunskapsspridning på. Vi ger en översikt över författarverktyg för processer på marknaden med det förslaget i åtanke.

On the impact of rigorous approaches on the quality of development

Software systems are expanding and becoming increasingly present in everyday activities. The constantly evolving society demands that they deliver more functionality, are easy to use and work as expected. All these challenges increase the size and complexity of a system. People may not be aware of a presence of a software system, until it malfunctions or even fails to perform. The concept of being able to depend on the software is particularly significant when it comes to the critical systems. At this point quality of a system is regarded as an essential issue, since any deficiencies may lead to considerable money loss or life endangerment. Traditional development methods may not ensure a sufficiently high level of quality. Formal methods, on the other hand, allow us to achieve a high level of rigour and can be applied to develop a complete system or only a critical part of it. Such techniques, applied during system development starting at early design stages, increase the likelihood of obtaining a system that works as required. However, formal methods are sometimes considered difficult to utilise in traditional developments. Therefore, it is important to make them more accessible and reduce the gap between the formal and traditional development methods. This thesis explores the usability of rigorous approaches by giving an insight into formal designs with the use of graphical notation. The understandability of formal modelling is increased due to a compact representation of the development and related design decisions. The central objective of the thesis is to investigate the impact that rigorous approaches have on quality of developments. This means that it is necessary to establish certain techniques for evaluation of rigorous developments. Since we are studying various development settings and methods, specific measurement plans and a set of metrics need to be created for each setting. Our goal is to provide methods for collecting data and record evidence of the applicability of rigorous approaches. This would support the organisations in making decisions about integration of formal methods into their development processes. It is important to control the software development, especially in its initial stages. Therefore, we focus on the specification and modelling phases, as well as related artefacts, e.g. models. These have significant influence on the quality of a final system. Since application of formal methods may increase the complexity of a system, it may impact its maintainability, and thus quality. Our goal is to leverage quality of a system via metrics and measurements, as well as generic refinement patterns, which are applied to a model and a specification. We argue that they can facilitate the process of creating software systems, by e.g. controlling complexity and providing the modelling guidelines. Moreover, we find them as additional mechanisms for quality control and improvement, also for rigorous approaches. The main contribution of this thesis is to provide the metrics and measurements that help in assessing the impact of rigorous approaches on developments. We establish the techniques for the evaluation of certain aspects of quality, which are based on structural, syntactical and process related characteristics of an early-stage development artefacts, i.e. specifications and models. The presented approaches are applied to various case studies. The results of the investigation are juxtaposed with the perception of domain experts. It is our aspiration to promote measurements as an indispensable part of quality control process and a strategy towards the quality improvement.

Patterns and quality of object-oriented software systems

Lors de ces dix dernières années, le coût de la maintenance des systèmes orientés objets s'est accru jusqu' à compter pour plus de 70% du coût total des systèmes. Cette situation est due à plusieurs facteurs, parmi lesquels les plus importants sont: l'imprécision des spécifications des utilisateurs, l'environnement d'exécution changeant rapidement et la mauvaise qualité interne des systèmes. Parmi tous ces facteurs, le seul sur lequel nous ayons un réel contrôle est la qualité interne des systèmes. De nombreux modèles de qualité ont été proposés dans la littérature pour contribuer à contrôler la qualité. Cependant, la plupart de ces modèles utilisent des métriques de classes (nombre de méthodes d'une classe par exemple) ou des métriques de relations entre classes (couplage entre deux classes par exemple) pour mesurer les attributs internes des systèmes. Pourtant, la qualité des systèmes par objets ne dépend pas uniquement de la structure de leurs classes et que mesurent les métriques, mais aussi de la façon dont celles-ci sont organisées, c'est-à-dire de leur conception, qui se manifeste généralement à travers les patrons de conception et les anti-patrons. Dans cette thèse nous proposons la méthode DEQUALITE, qui permet de construire systématiquement des modèles de qualité prenant en compte non seulement les attributs internes des systèmes (grâce aux métriques), mais aussi leur conception (grâce aux patrons de conception et anti-patrons). Cette méthode utilise une approche par apprentissage basée sur les réseaux bayésiens et s'appuie sur les résultats d'une série d'expériences portant sur l'évaluation de l'impact des patrons de conception et des anti-patrons sur la qualité des systèmes. Ces expériences réalisées sur 9 grands systèmes libres orientés objet nous permettent de formuler les conclusions suivantes: • Contre l'intuition, les patrons de conception n'améliorent pas toujours la qualité des systèmes; les implantations très couplées de patrons de conception par exemple affectent la structure des classes et ont un impact négatif sur leur propension aux changements et aux fautes. • Les classes participantes dans des anti-atrons sont beaucoup plus susceptibles de changer et d'être impliquées dans des corrections de fautes que les autres classes d'un système. • Un pourcentage non négligeable de classes sont impliquées simultanément dans des patrons de conception et dans des anti-patrons. Les patrons de conception ont un effet positif en ce sens qu'ils atténuent les anti-patrons. Nous appliquons et validons notre méthode sur trois systèmes libres orientés objet afin de démontrer l'apport de la conception des systèmes dans l'évaluation de la qualité.

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments

MOTIVATION: The accurate prediction of the quality of 3D models is a key component of successful protein tertiary structure prediction methods. Currently, clustering or consensus based Model Quality Assessment Programs (MQAPs) are the most accurate methods for predicting 3D model quality; however they are often CPU intensive as they carry out multiple structural alignments in order to compare numerous models. In this study, we describe ModFOLDclustQ - a novel MQAP that compares 3D models of proteins without the need for CPU intensive structural alignments by utilising the Q measure for model comparisons. The ModFOLDclustQ method is benchmarked against the top established methods in terms of both accuracy and speed. In addition, the ModFOLDclustQ scores are combined with those from our older ModFOLDclust method to form a new method, ModFOLDclust2, that aims to provide increased prediction accuracy with negligible computational overhead. RESULTS: The ModFOLDclustQ method is competitive with leading clustering based MQAPs for the prediction of global model quality, yet it is up to 150 times faster than the previous version of the ModFOLDclust method at comparing models of small proteins (<60 residues) and over 5 times faster at comparing models of large proteins (>800 residues). Furthermore, a significant improvement in accuracy can be gained over the previous clustering based MQAPs by combining the scores from ModFOLDclustQ and ModFOLDclust to form the new ModFOLDclust2 method, with little impact on the overall time taken for each prediction. AVAILABILITY: The ModFOLDclustQ and ModFOLDclust2 methods are available to download from: http://www.reading.ac.uk/bioinf/downloads/ CONTACT: l.j.mcguffin@reading.ac.uk.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

The ModFOLD server for the quality assessment of protein structural models

The reliable assessment of the quality of protein structural models is fundamental to the progress of structural bioinformatics. The ModFOLD server provides access to two accurate techniques for the global and local prediction of the quality of 3D models of proteins. Firstly ModFOLD, which is a fast Model Quality Assessment Program (MQAP) used for the global assessment of either single or multiple models. Secondly ModFOLDclust, which is a more intensive method that carries out clustering of multiple models and provides per-residue local quality assessment.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.

Improvement of 3D protein models using multiple templates guided by single-template model quality assessment

Motivation: Modelling the 3D structures of proteins can often be enhanced if more than one fold template is used during the modelling process. However, in many cases, this may also result in poorer model quality for a given target or alignment method. There is a need for modelling protocols that can both consistently and significantly improve 3D models and provide an indication of when models might not benefit from the use of multiple target-template alignments. Here, we investigate the use of both global and local model quality prediction scores produced by ModFOLDclust2, to improve the selection of target-template alignments for the construction of multiple-template models. Additionally, we evaluate clustering the resulting population of multi- and single-template models for the improvement of our IntFOLD-TS tertiary structure prediction method. Results: We find that using accurate local model quality scores to guide alignment selection is the most consistent way to significantly improve models for each of the sequence to structure alignment methods tested. In addition, using accurate global model quality for re-ranking alignments, prior to selection, further improves the majority of multi-template modelling methods tested. Furthermore, subsequent clustering of the resulting population of multiple-template models significantly improves the quality of selected models compared with the previous version of our tertiary structure prediction method, IntFOLD-TS.

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

Evaluating the climate and air quality impacts of short-lived pollutants

This paper presents a summary of the work done within the European Union's Seventh Framework Programme project ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants). ECLIPSE had a unique systematic concept for designing a realistic and effective mitigation scenario for short-lived climate pollutants (SLCPs; methane, aerosols and ozone, and their precursor species) and quantifying its climate and air quality impacts, and this paper presents the results in the context of this overarching strategy. The first step in ECLIPSE was to create a new emission inventory based on current legislation (CLE) for the recent past and until 2050. Substantial progress compared to previous work was made by including previously unaccounted types of sources such as flaring of gas associated with oil production, and wick lamps. These emission data were used for present-day reference simulations with four advanced Earth system models (ESMs) and six chemistry transport models (CTMs). The model simulations were compared with a variety of ground-based and satellite observational data sets from Asia, Europe and the Arctic. It was found that the models still underestimate the measured seasonality of aerosols in the Arctic but to a lesser extent than in previous studies. Problems likely related to the emissions were identified for northern Russia and India, in particular. To estimate the climate impacts of SLCPs, ECLIPSE followed two paths of research: the first path calculated radiative forcing (RF) values for a large matrix of SLCP species emissions, for different seasons and regions independently. Based on these RF calculations, the Global Temperature change Potential metric for a time horizon of 20 years (GTP20) was calculated for each SLCP emission type. This climate metric was then used in an integrated assessment model to identify all emission mitigation measures with a beneficial air quality and short-term (20-year) climate impact. These measures together defined a SLCP mitigation (MIT) scenario. Compared to CLE, the MIT scenario would reduce global methane (CH4) and black carbon (BC) emissions by about 50 and 80 %, respectively. For CH4, measures on shale gas production, waste management and coal mines were most important. For non-CH4 SLCPs, elimination of high-emitting vehicles and wick lamps, as well as reducing emissions from gas flaring, coal and biomass stoves, agricultural waste, solvents and diesel engines were most important. These measures lead to large reductions in calculated surface concentrations of ozone and particulate matter. We estimate that in the EU, the loss of statistical life expectancy due to air pollution was 7.5 months in 2010, which will be reduced to 5.2 months by 2030 in the CLE scenario. The MIT scenario would reduce this value by another 0.9 to 4.3 months. Substantially larger reductions due to the mitigation are found for China (1.8 months) and India (11–12 months). The climate metrics cannot fully quantify the climate response. Therefore, a second research path was taken. Transient climate ensemble simulations with the four ESMs were run for the CLE and MIT scenarios, to determine the climate impacts of the mitigation. In these simulations, the CLE scenario resulted in a surface temperature increase of 0.70 ± 0.14 K between the years 2006 and 2050. For the decade 2041–2050, the warming was reduced by 0.22 ± 0.07 K in the MIT scenario, and this result was in almost exact agreement with the response calculated based on the emission metrics (reduced warming of 0.22 ± 0.09 K). The metrics calculations suggest that non-CH4 SLCPs contribute ~ 22 % to this response and CH4 78 %. This could not be fully confirmed by the transient simulations, which attributed about 90 % of the temperature response to CH4 reductions. Attribution of the observed temperature response to non-CH4 SLCP emission reductions and BC specifically is hampered in the transient simulations by small forcing and co-emitted species of the emission basket chosen. Nevertheless, an important conclusion is that our mitigation basket as a whole would lead to clear benefits for both air quality and climate. The climate response from BC reductions in our study is smaller than reported previously, possibly because our study is one of the first to use fully coupled climate models, where unforced variability and sea ice responses cause relatively strong temperature fluctuations that may counteract (and, thus, mask) the impacts of small emission reductions. The temperature responses to the mitigation were generally stronger over the continents than over the oceans, and with a warming reduction of 0.44 K (0.39–0.49) K the largest over the Arctic. Our calculations suggest particularly beneficial climate responses in southern Europe, where surface warming was reduced by about 0.3 K and precipitation rates were increased by about 15 (6–21) mm yr−1 (more than 4 % of total precipitation) from spring to autumn. Thus, the mitigation could help to alleviate expected future drought and water shortages in the Mediterranean area. We also report other important results of the ECLIPSE project.

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

Partitions selection strategy for set of clustering solutions

Clustering is a difficult task: there is no single cluster definition and the data can have more than one underlying structure. Pareto-based multi-objective genetic algorithms (e.g., MOCK Multi-Objective Clustering with automatic K-determination and MOCLE-Multi-Objective Clustering Ensemble) were proposed to tackle these problems. However, the output of such algorithms can often contains a high number of partitions, becoming difficult for an expert to manually analyze all of them. In order to deal with this problem, we present two selection strategies, which are based on the corrected Rand, to choose a subset of solutions. To test them, they are applied to the set of solutions produced by MOCK and MOCLE in the context of several datasets. The study was also extended to select a reduced set of partitions from the initial population of MOCLE. These analysis show that both versions of selection strategy proposed are very effective. They can significantly reduce the number of solutions and, at the same time, keep the quality and the diversity of the partitions in the original set of solutions. (C) 2010 Elsevier B.V. All rights reserved.