Unlock 30% off on Manual Testing Annual Plans this Holiday Season.

Copied to Clipboard!

How to use get_bugs method in Kiwi

Best Python code snippet using Kiwi_python

Diagnosis_Results.py

Source:Diagnosis_Results.py

...59        failed_comps = set(self.get_components_in_failed_tests())60        metrics["num_failed_comps"] = len(failed_comps)61        metrics["only_failed_comps"] = len(failed_comps - passed_comps)62        metrics["only_passed_comps"] = len(passed_comps - failed_comps)63        metrics["num_bugs"] = len(self.get_bugs())64        metrics["wasted"] = self.calc_wasted_components()65        metrics["top_k"] = self.calc_top_k()66        metrics["num_comps_in_diagnoses"] = len(self._get_comps_in_diagnoses())67        metrics["bugs_cover_ratio"] = self._get_bugs_cover_ratio()68        metrics["average_trace_size"] = self._get_average_trace_size()69        metrics["average_component_activity"] = self._get_average_component_activity()70        metrics["average_diagnosis_size"] = self._get_average_diagnosis_size()71        metrics["bugs_scores_average"], metrics["bugs_scores_std"], metrics["bugs_scores_entropy"] = self._get_bugs_scores()72        metrics["non_bugs_scores_average"], metrics["non_bugs_scores_std"], metrics["non_bugs_scores_entropy"] = self._get_non_bugs_scores()73        metrics.update(self.cardinality())74        # metrics["ochiai"] = self.calc_ochiai_values()75        return metrics7677    def _get_comps_in_diagnoses(self):78        return reduce(set.__or__, list(map(lambda x: set(x.diagnosis), self.diagnoses)), set())7980    def _get_bugs_cover_ratio(self):81        bugs = self.get_bugs()82        comps = self._get_comps_in_diagnoses()83        return len(set(comps) & set(bugs)) / (len(bugs) * 1.0)8485    def _get_bugs_scores(self):86        bugs = self.get_bugs()87        comps_prob = dict(self.get_components_probabilities())88        bugs_prob = list(map(lambda x: comps_prob.get(x, 0), bugs))89        return np.mean(bugs_prob), np.std(bugs_prob), entropy(bugs_prob)9091    def _get_average_trace_size(self):92        return np.mean(list(map(len, self.pool.values())))9394    def _get_average_diagnosis_size(self):95        return np.mean(list(map(lambda x: len(x.diagnosis), self.diagnoses)))9697    def _get_average_component_activity(self):98        return np.mean(list(Counter(reduce(list.__add__, self.pool.values(), [])).values()))99100    def _get_non_bugs_scores(self):101        bugs = self.get_bugs()102        comps_prob = dict(self.get_components_probabilities())103        non_bugs_prob = list(map(comps_prob.get, filter(lambda c: c not in bugs, comps_prob)))104        return np.mean(non_bugs_prob), np.std(non_bugs_prob), entropy(non_bugs_prob)105106    def _get_metrics_list(self):107        return sorted(self.metrics.items(), key=lambda m:m[0])108109    def get_metrics_values(self):110        return list(map(lambda m:m[1], self._get_metrics_list()))111112    def get_metrics_names(self):113        return list(map(lambda m:m[0], self._get_metrics_list()))114115    def __repr__(self):116        return repr(self.metrics)117118    @staticmethod119    def precision_recall_for_diagnosis(buggedComps, dg, pr, validComps):120        fp = len([i1 for i1 in dg if i1 in validComps])121        fn = len([i1 for i1 in buggedComps if i1 not in dg])122        tp = len([i1 for i1 in dg if i1 in buggedComps])123        tn = len([i1 for i1 in validComps if i1 not in dg])124        if ((tp + fp) == 0):125            precision = "undef"126        else:127            precision = (tp + 0.0) / float(tp + fp)128            a = precision129            precision = precision * float(pr)130        if ((tp + fn) == 0):131            recall = "undef"132        else:133            recall = (tp + 0.0) / float(tp + fn)134            recall = recall * float(pr)135        return precision, recall136137    def calc_precision_recall(self):138        recall_accum=0139        precision_accum=0140        validComps=[x for x in set(reduce(list.__add__, self.pool.values())) if x not in self.get_bugs()]141142        self.diagnoses.sort(key = lambda x: x.probability, reverse = True)143144        self.diagnoses = self.diagnoses[:5]145146        for d in self.diagnoses:147            dg=d.diagnosis148            pr=d.probability149            precision, recall = Diagnosis_Results.precision_recall_for_diagnosis(self.get_bugs(), dg, pr, validComps)150            if(recall!="undef"):151                recall_accum=recall_accum+recall152            if(precision!="undef"):153                precision_accum=precision_accum+precision154        return precision_accum,recall_accum155156    def get_tests(self):157        return self.pool.items()158159    def get_bugs(self):160        return self.bugs161162    def get_initial_tests_traces(self):163        return list(map(lambda test: (sorted(self.pool[test]), self.error[test]), self.initial_tests))164165    def _get_tests_by_error(self, error):166        by_error = list(filter(lambda test: self.error[test] == error, self.initial_tests))167        return dict(map(lambda test: (test, self.pool[test]), by_error))168169    def get_components(self):170        return set(reduce(list.__add__, self.pool.values()))171172    def _get_components_by_error(self, error):173        return set(reduce(list.__add__, self._get_tests_by_error(error).values(), []))174175    def get_components_in_failed_tests(self):176        return self._get_components_by_error(1)177178    def get_components_in_passed_tests(self):179        return self._get_components_by_error(0)180181    def get_components_probabilities(self):182        """183        calculate for each component c the sum of probabilities of the diagnoses that include c184        return dict of (component, probability)185        """186        compsProbs={}187        for d in self.diagnoses:188            p = d.get_prob()189            for comp in d.get_diag():190                compsProbs[comp] = compsProbs.get(comp,0) + p191        return sorted(compsProbs.items(), key=lambda x: x[1], reverse=True)192193    def calc_wasted_components(self):194        components = list(map(lambda x: x[0], self.get_components_probabilities()))195        if len(self.get_bugs()) == 0:196            return len(components)197        wasted = 0.0198        for b in self.get_bugs():199            if b not in components:200                return len(components)201            wasted += components.index(b)202        return wasted / len(self.get_bugs())203204    def calc_expense(self):205        components = list(map(lambda x: x[0], self.get_components_probabilities()))206        total_expense = None207        total_bugs_in_components = 0208        for bug in self.get_bugs():209            if bug in components:210                if total_expense:211                    total_expense += ((components.index(bug)/len(components)) * 100)212                    total_bugs_in_components += 1213                else:214                    total_expense = (components.index(bug)/len(components)) * 100215                    total_bugs_in_components += 1216        if total_expense:217            total_expense /= total_bugs_in_components218        if total_expense is None:219            return 100220        return total_expense221222    def calc_exam_score(self):223        components = list(map(lambda x: x[0], self.get_components_probabilities()))224225        for component in components:226            if component in self.get_bugs():227                return ((components.index(component)/len(components)) * 100)228229        return 100230231    def calc_top_k(self):232        components = list(map(lambda x: x[0], self.get_components_probabilities()))233        top_k = None234        for bug in self.get_bugs():235            if bug in components:236                if top_k:237                    top_k = max(top_k, components.index(bug))238                else:239                    top_k = components.index(bug)240        if top_k is None:241            return len(components)242        return top_k243244    def calc_entropy(self):245        return entropy(list(map(lambda diag: diag.probability, self.diagnoses)))246247    def calc_component_entropy(self):248        return entropy(list(map(lambda x: x[1], self.get_components_probabilities())))
...

lbench

Source:lbench

...61			put_bug(mock)62	if conc:63		wait(pool)64	print(f"Elapsed time: {time.time() - start}s")65def get_bugs(verbose=True) -> dict:66	resp = req.get(f"{BASE_URL}/get")67	j = json.loads(resp.content)68	for b in j["bugs"]:69		if verbose:70			print(f"ID: {b['id']}, Body: {b['body']}")71	return j["bugs"]72def clear_bugs():73	for b in get_bugs(False):74		print(f"Deleting bug #{b['id']}...")75		resp = req.delete(f"{BASE_URL}/delete?id={b['id']}")76if __name__ == "__main__":77	arg = docopt(__doc__)78	try:79		if arg["put"]:80			upload_bugs(int(arg["<num>"]), arg["--concurrent"])81		elif arg["get"]:82			get_bugs()83		elif arg["clear"]:84			clear_bugs()85	except Exception as e:...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.