| 1 | package de.uka.ipd.sdq.reliability.solver.sensitivity; |
| 2 | |
| 3 | import java.io.BufferedWriter; |
| 4 | import java.io.File; |
| 5 | import java.io.FileWriter; |
| 6 | import java.io.IOException; |
| 7 | import java.util.ArrayList; |
| 8 | import java.util.List; |
| 9 | |
| 10 | import org.apache.log4j.Logger; |
| 11 | import org.eclipse.emf.common.util.EList; |
| 12 | |
| 13 | import de.uka.ipd.sdq.pcm.usagemodel.UsageScenario; |
| 14 | import de.uka.ipd.sdq.pcmsolver.models.PCMInstance; |
| 15 | import de.uka.ipd.sdq.reliability.core.helper.EMFHelper; |
| 16 | import de.uka.ipd.sdq.reliability.solver.pcm2markov.MarkovTransformationResult; |
| 17 | import de.uka.ipd.sdq.sensitivity.DoubleParameterVariation; |
| 18 | import de.uka.ipd.sdq.sensitivity.SensitivityParameterVariation; |
| 19 | import de.uka.ipd.sdq.sensitivity.SensitivityResultSpecification; |
| 20 | import de.uka.ipd.sdq.sensitivity.StringParameterSequence; |
| 21 | |
| 22 | /** |
| 23 | * Base class for (rudimentary) sensitivity analysis. |
| 24 | * |
| 25 | * Further refactorings required. |
| 26 | * |
| 27 | * @author brosch |
| 28 | * |
| 29 | */ |
| 30 | public abstract class MarkovSensitivity { |
| 31 | |
| 32 | /** |
| 33 | * Character used to separate entries in the sensitivity log file. |
| 34 | */ |
| 35 | private static final String LOG_ENTRY_SEPARATOR = "\\"; |
| 36 | |
| 37 | /** |
| 38 | * A logger to give detailed information about the PCM instance |
| 39 | * transformation. |
| 40 | */ |
| 41 | protected Logger logger = null; |
| 42 | |
| 43 | /** |
| 44 | * A calculator for variations and steps during the sensitivity analysis. |
| 45 | */ |
| 46 | protected SensitivityCalculator calculator = new SensitivityCalculator(); |
| 47 | |
| 48 | /** |
| 49 | * The current sensitivity analysis step. |
| 50 | */ |
| 51 | private int currentStepNumber = 0; |
| 52 | |
| 53 | /** |
| 54 | * Provides EMF utility functions. |
| 55 | */ |
| 56 | protected EMFHelper helper = new EMFHelper(); |
| 57 | |
| 58 | /** |
| 59 | * Stores the contents of the log file. |
| 60 | */ |
| 61 | private List<List<String>> logContents = null; |
| 62 | |
| 63 | /** |
| 64 | * Provides a writer to the log file. |
| 65 | */ |
| 66 | protected BufferedWriter logWriter = null; |
| 67 | |
| 68 | /** |
| 69 | * The model on which sensitivity analysis is based. |
| 70 | */ |
| 71 | protected PCMInstance model; |
| 72 | |
| 73 | /** |
| 74 | * The name of this sensitivity (for logging). |
| 75 | */ |
| 76 | protected String name = null; |
| 77 | |
| 78 | /** |
| 79 | * The number of steps to take during sensitivity analysis. |
| 80 | */ |
| 81 | protected int numberOfSteps; |
| 82 | |
| 83 | /** |
| 84 | * The log file for sensitivity results. |
| 85 | */ |
| 86 | private String resultLogfile = null; |
| 87 | |
| 88 | /** |
| 89 | * The list of relevant Markov analysis results. |
| 90 | */ |
| 91 | private EList<SensitivityResultSpecification> resultSpecifications = null; |
| 92 | |
| 93 | /** |
| 94 | * The variation of this sensitivity analysis. |
| 95 | */ |
| 96 | private SensitivityParameterVariation variation = null; |
| 97 | |
| 98 | /** |
| 99 | * The constructor. |
| 100 | * |
| 101 | * Only to be invoked by concrete sub classes. |
| 102 | * |
| 103 | * @param name |
| 104 | * the name of the sensitivity analysis |
| 105 | * @param variation |
| 106 | * the parameter variation |
| 107 | */ |
| 108 | protected MarkovSensitivity(final String name, |
| 109 | final SensitivityParameterVariation variation) { |
| 110 | this.name = name; |
| 111 | this.logger = Logger.getLogger(this.getClass().getName()); |
| 112 | if (variation != null) { |
| 113 | this.variation = variation; |
| 114 | this.numberOfSteps = calculator.calculateNumberOfSteps(variation); |
| 115 | } |
| 116 | } |
| 117 | |
| 118 | /** |
| 119 | * Alters the model according to the next sensitivity analysis step. |
| 120 | * |
| 121 | * @return indicates if the model could be successfully altered |
| 122 | */ |
| 123 | protected abstract boolean alterModel(); |
| 124 | |
| 125 | /** |
| 126 | * Assures a minimal number of three lines for the log headings. |
| 127 | * |
| 128 | * @param list |
| 129 | * the log headings |
| 130 | */ |
| 131 | private void assureLogHeadingsSize(final List<List<String>> list) { |
| 132 | int numColumns = list.get(0).size(); |
| 133 | int numLines = list.size(); |
| 134 | if (numLines < 3) { |
| 135 | for (int i = numLines; i < 3; i++) { |
| 136 | ArrayList<String> newLine = new ArrayList<String>(); |
| 137 | for (int y = 0; y < numColumns; y++) { |
| 138 | newLine.add(""); |
| 139 | } |
| 140 | list.add(0, newLine); |
| 141 | } |
| 142 | } |
| 143 | } |
| 144 | |
| 145 | /** |
| 146 | * Extracts the relevant sensitivity information from the given model. |
| 147 | */ |
| 148 | protected abstract void extractSensitivityInformation(); |
| 149 | |
| 150 | /** |
| 151 | * Fills empty entries of the given log headings list. |
| 152 | * |
| 153 | * @param list |
| 154 | * the log headings list |
| 155 | */ |
| 156 | private void fillEmptyEntries(List<List<String>> list) { |
| 157 | int numLines = list.size(); |
| 158 | int maxNumColumns = 0; |
| 159 | for (int i = 0; i < numLines; i++) { |
| 160 | if (list.get(i).size() > maxNumColumns) { |
| 161 | maxNumColumns = list.get(i).size(); |
| 162 | } |
| 163 | } |
| 164 | for (int i = 0; i < numLines; i++) { |
| 165 | for (int y = list.get(i).size(); y < maxNumColumns; y++) { |
| 166 | list.get(i).add(""); |
| 167 | } |
| 168 | } |
| 169 | } |
| 170 | |
| 171 | /** |
| 172 | * Finalizes the sensitivity analysis. |
| 173 | */ |
| 174 | public void finalize() { |
| 175 | try { |
| 176 | // Do the logging: |
| 177 | for (int lineNumber = 0; lineNumber < logContents.size(); lineNumber++) { |
| 178 | for (int index = 0; index < logContents.get(lineNumber).size(); index++) { |
| 179 | logWriter.append(logContents.get(lineNumber).get(index) |
| 180 | + LOG_ENTRY_SEPARATOR); |
| 181 | } |
| 182 | logWriter.append(System.getProperty("line.separator")); |
| 183 | } |
| 184 | logWriter.flush(); |
| 185 | logWriter.close(); |
| 186 | } catch (IOException e) { |
| 187 | logger.error("Log file could not be written :" + e.getMessage()); |
| 188 | e.printStackTrace(); |
| 189 | } |
| 190 | } |
| 191 | |
| 192 | /** |
| 193 | * Retrieves the current step number. |
| 194 | * |
| 195 | * @return the current step number |
| 196 | */ |
| 197 | protected int getCurrentStepNumber() { |
| 198 | return currentStepNumber; |
| 199 | } |
| 200 | |
| 201 | /** |
| 202 | * Returns the double parameter variation. |
| 203 | * |
| 204 | * @return the double parameter variation |
| 205 | */ |
| 206 | protected DoubleParameterVariation getDoubleVariation() { |
| 207 | return (DoubleParameterVariation) variation; |
| 208 | } |
| 209 | |
| 210 | /** |
| 211 | * Builds the headings strings for logging. |
| 212 | * |
| 213 | * @return the log headings strings |
| 214 | */ |
| 215 | private List<List<String>> getLogHeadings() { |
| 216 | |
| 217 | // Create a result list: |
| 218 | List<List<String>> resultList = getLogHeadingsMulti(); |
| 219 | |
| 220 | // Assure that there are at least three lines of headings: |
| 221 | assureLogHeadingsSize(resultList); |
| 222 | for (UsageScenario scenario : model.getUsageModel() |
| 223 | .getUsageScenario_UsageModel()) { |
| 224 | resultList.get(resultList.size() - 3).add(scenario.getEntityName()); |
| 225 | resultList.get(resultList.size() - 2).add("Success Probability"); |
| 226 | resultList.get(resultList.size() - 2).add("Failure Probability"); |
| 227 | resultList.get(resultList.size() - 1).add(""); |
| 228 | resultList.get(resultList.size() - 1).add("Total"); |
| 229 | for (int i = 0; i < resultSpecifications.size(); i++) { |
| 230 | resultList.get(resultList.size() - 1).add( |
| 231 | resultSpecifications.get(i).getEntityName()); |
| 232 | } |
| 233 | fillEmptyEntries(resultList); |
| 234 | } |
| 235 | |
| 236 | // Return the result: |
| 237 | return resultList; |
| 238 | } |
| 239 | |
| 240 | /** |
| 241 | * Builds the headings strings for logging. |
| 242 | * |
| 243 | * @return the log headings strings |
| 244 | */ |
| 245 | protected abstract List<List<String>> getLogHeadingsMulti(); |
| 246 | |
| 247 | /** |
| 248 | * Builds the results strings for sensitivity logging. |
| 249 | * |
| 250 | * @param markovResults |
| 251 | * the Markov transformation results |
| 252 | * @return the results strings |
| 253 | */ |
| 254 | protected List<String> getLogSingleResults( |
| 255 | final List<MarkovTransformationResult> markovResults) { |
| 256 | |
| 257 | // Create a result list: |
| 258 | List<String> resultList = getLogSingleResultsMulti(); |
| 259 | for (MarkovTransformationResult result : markovResults) { |
| 260 | resultList |
| 261 | .add(((Double) result.getSuccessProbability()).toString()); |
| 262 | resultList.add(((Double) (1.0 - result.getSuccessProbability())) |
| 263 | .toString()); |
| 264 | for (int i = 0; i < resultSpecifications.size(); i++) { |
| 265 | resultList.add(((Double) calculator.calculateFailurePotential( |
| 266 | result, resultSpecifications.get(i))).toString()); |
| 267 | } |
| 268 | } |
| 269 | |
| 270 | // Return the result: |
| 271 | return resultList; |
| 272 | } |
| 273 | |
| 274 | /** |
| 275 | * Builds the results string for sensitivity logging. |
| 276 | * |
| 277 | * @return the results strings |
| 278 | */ |
| 279 | protected abstract List<String> getLogSingleResultsMulti(); |
| 280 | |
| 281 | /** |
| 282 | * Retrieves the PCM instance. |
| 283 | * |
| 284 | * @return the PCM instance |
| 285 | */ |
| 286 | protected PCMInstance getModel() { |
| 287 | return model; |
| 288 | } |
| 289 | |
| 290 | /** |
| 291 | * Retrieves the model to be used for the next step in the sensitivity |
| 292 | * analysis. |
| 293 | * |
| 294 | * @return the model |
| 295 | */ |
| 296 | public PCMInstance getNextModel() { |
| 297 | |
| 298 | // Check if there are still steps to perform: |
| 299 | if (increaseCurrentStepNumber()) { |
| 300 | return null; |
| 301 | } |
| 302 | |
| 303 | // Perform the next step: |
| 304 | if (!alterModel()) { |
| 305 | logger.error("PCM instance could not be successfully altered by Markov sensitivity analysis."); |
| 306 | return null; |
| 307 | } else { |
| 308 | return model; |
| 309 | } |
| 310 | } |
| 311 | |
| 312 | /** |
| 313 | * Returns the string parameter sequence. |
| 314 | * |
| 315 | * @return the string parameter sequence |
| 316 | */ |
| 317 | protected StringParameterSequence getStringSequence() { |
| 318 | return (StringParameterSequence) variation; |
| 319 | } |
| 320 | |
| 321 | /** |
| 322 | * Increases the current step number. |
| 323 | * |
| 324 | * @return indicates an overflow |
| 325 | */ |
| 326 | protected boolean increaseCurrentStepNumber() { |
| 327 | if (currentStepNumber < numberOfSteps) { |
| 328 | currentStepNumber++; |
| 329 | return false; |
| 330 | } |
| 331 | return true; |
| 332 | } |
| 333 | |
| 334 | /** |
| 335 | * Initializes the sensitivity analysis. |
| 336 | * |
| 337 | * @param model |
| 338 | * the PCM instance |
| 339 | */ |
| 340 | public void initialize(final PCMInstance model) { |
| 341 | setModel(model); |
| 342 | try { |
| 343 | new File(resultLogfile).delete(); |
| 344 | logWriter = new BufferedWriter(new FileWriter(resultLogfile, false)); |
| 345 | } catch (IOException e) { |
| 346 | logger |
| 347 | .error("Log file could not be initialized :" |
| 348 | + e.getMessage()); |
| 349 | e.printStackTrace(); |
| 350 | } |
| 351 | logContents = getLogHeadings(); |
| 352 | } |
| 353 | |
| 354 | /** |
| 355 | * Logs the results of the current sensitivity analysis step. |
| 356 | * |
| 357 | * @param markovResults |
| 358 | * the markov transformation results |
| 359 | */ |
| 360 | public void logResults(final List<MarkovTransformationResult> markovResults) { |
| 361 | logContents.add(getLogSingleResults(markovResults)); |
| 362 | } |
| 363 | |
| 364 | /** |
| 365 | * Resets the current step number. |
| 366 | * |
| 367 | */ |
| 368 | protected void resetCurrentStepNumber() { |
| 369 | currentStepNumber = 1; |
| 370 | } |
| 371 | |
| 372 | /** |
| 373 | * Sets the result log file name. |
| 374 | * |
| 375 | * @param logFileName |
| 376 | * the log file name |
| 377 | */ |
| 378 | public void setLogFileName(final String logFileName) { |
| 379 | this.resultLogfile = logFileName; |
| 380 | } |
| 381 | |
| 382 | /** |
| 383 | * Sets the PCM instance. |
| 384 | * |
| 385 | * @param model |
| 386 | * the PCM instance |
| 387 | */ |
| 388 | protected void setModel(final PCMInstance model) { |
| 389 | this.model = model; |
| 390 | extractSensitivityInformation(); |
| 391 | } |
| 392 | |
| 393 | /** |
| 394 | * Specifies the relevant Markov analysis results. |
| 395 | * |
| 396 | * @param resultSpecifications |
| 397 | * specification of results |
| 398 | */ |
| 399 | public void setResultSpecifications( |
| 400 | final EList<SensitivityResultSpecification> resultSpecifications) { |
| 401 | this.resultSpecifications = resultSpecifications; |
| 402 | } |
| 403 | } |